Rational Design of Serine Protease Inhibitors

Joakim E. Swedberg Bachelor of Applied Science (Biotechnology) (Honours) Queensland of University of Technology

Submitted for Award of Degree of

Doctor of Philosophy May 2011

Principal Supervisor: Associate Professor Jonathan Harris Associate Supervisor: Associate Professor Lisa Chopin Queensland University of Technology School of Life Science Faculty of Science and Technology Brisbane, Queensland, 4001, Australia

© Copyright by Joakim E. Swedberg All Rights Reserved

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Key Words

Serine protease; Kallikrein; Kallikrein-related peptidase; KLK4, KLK14; Plasmin, Sunflower trypsin inhibitor; SFTI; Inhibitor; Transition state analogue; Sparse matrix library; Positional scanning; PS-SCL; Prostate cancer; Ovarian cancer; Fibrinolysis; Desquamation Molecular dynamics; Computer aided drug design

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Abstract

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Proteases regulate a spectrum of diverse physiological processes, and dysregulation of proteolytic activity drives a plethora of pathological conditions. Understanding protease function is essential to appreciating many aspects of normal physiology and progression of disease. Consequently, development of potent and specific inhibitors of proteolytic enzymes is vital to provide tools for the dissection of protease function in biological systems and for the treatment of diseases linked to aberrant proteolytic activity. The studies in this thesis describe the rational design of potent inhibitors of three proteases that are implicated in disease development. Additionally, key features of the interaction of proteases and their cognate inhibitors or substrates are analysed and a series of rational inhibitor design principles are expounded and tested. Rational design of protease inhibitors relies on a comprehensive understanding of protease structure and biochemistry. Analysis of known protease cleavage sites in proteins and peptides is a commonly used source of such information. However, model peptide substrate and protein sequences have widely differing levels of backbone constraint and hence can adopt highly divergent structures when binding to a protease’s active site. This may result in identical sequences in peptides and proteins having different conformations and diverse spatial distribution of amino acid functionalities. Regardless of this, protein and peptide cleavage sites are often regarded as being equivalent. One of the key findings in the following studies is a definitive demonstration of the lack of equivalence between these two classes of substrate and invalidation of the common practice of using the sequences of model peptide substrates to predict cleavage of proteins in vivo. Another important feature for protease substrate recognition is subsite cooperativity. This type of cooperativity is commonly referred to as protease or substrate binding subsite cooperativity and is distinct from allosteric cooperativity, where binding of a molecule distant

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from the protease active site affects the binding affinity of a substrate. Subsite cooperativity may be intramolecular where neighbouring residues in substrates are interacting, affecting the scissile bond’s susceptibility to protease cleavage. Subsite cooperativity can also be intermolecular where a particular residue’s contribution to binding affinity changes depending on the identity of neighbouring amino acids. Although numerous studies have identified subsite cooperativity effects, these findings are frequently ignored in investigations probing subsite selectivity by screening against diverse combinatorial libraries of peptides (positional scanning synthetic combinatorial library; PS-SCL). This strategy for determining cleavage specificity relies on the averaged rates of hydrolysis for an uncharacterised ensemble of peptide sequences, as opposed to the defined rate of hydrolysis of a known specific substrate. Further, since PS-SCL screens probe the preference of the various protease subsites independently, this method is inherently unable to detect subsite cooperativity. However, mean hydrolysis rates from PS-SCL screens are often interpreted as being comparable to those produced by single peptide cleavages. Before this study no large systematic evaluation had been made to determine the level of correlation between protease selectivity as predicted by screening against a library of combinatorial peptides and cleavage of individual peptides. This subject is specifically explored in the studies described here. In order to establish whether PS-SCL screens could accurately determine the substrate preferences of proteases, a systematic comparison of data from PS-SCLs with libraries containing individually synthesised peptides (sparse matrix library; SML) was carried out. These SML libraries were designed to include all possible sequence combinations of the residues that were suggested to be preferred by a protease using the PS-SCL method. SML screening against the three serine proteases kallikrein 4 (KLK4), kallikrein 14 (KLK14) and plasmin revealed highly preferred peptide substrates that could not have been deduced by PS-SCL screening alone.

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Comparing protease subsite preference profiles from screens of the two types of peptide libraries showed that the most preferred substrates were not detected by PS SCL screening as a consequence of intermolecular cooperativity being negated by the very nature of PS SCL screening. Sequences that are highly favoured as result of intermolecular cooperativity achieve optimal protease subsite occupancy, and thereby interact with very specific determinants of the protease. Identifying these substrate sequences is important since they may be used to produce potent and selective inhibitors of protolytic enzymes. This study found that highly favoured substrate sequences that relied on intermolecular cooperativity allowed for the production of potent inhibitors of KLK4, KLK14 and plasmin. Peptide aldehydes based on preferred plasmin sequences produced high affinity transition state analogue inhibitors for this protease. The most potent of these maintained specificity over plasma kallikrein (known to have a very similar substrate preference to plasmin). Furthermore, the efficiency of this inhibitor in blocking fibrinolysis in vitro was comparable to aprotinin, which previously saw clinical use to reduce perioperative bleeding. One substrate sequence particularly favoured by KLK4 was substituted into the 14 amino acid, circular sunflower trypsin inhibitor (SFTI). This resulted in a highly potent and selective inhibitor (SFTI-FCQR) which attenuated protease activated receptor signalling by KLK4 in vitro. Moreover, SFTI-FCQR and paclitaxel synergistically reduced growth of ovarian cancer cells in vitro, making this inhibitor a lead compound for further therapeutic development. Similar incorporation of a preferred KLK14 amino acid sequence into the SFTI scaffold produced a potent inhibitor for this protease. However, the conformationally constrained SFTI backbone enforced a different intramolecular cooperativity, which masked a KLK14 specific determinant. As a consequence, the level of selectivity achievable was lower than that found for the KLK4 inhibitor.

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Standard mechanism inhibitors such as SFTI rely on a stable acyl-enzyme intermediate for high affinity binding. This is achieved by a conformationally constrained canonical binding loop that allows for reformation of the scissile peptide bond after cleavage. Amino acid substitutions within the inhibitor to target a particular protease may compromise structural determinants that support the rigidity of the binding loop and thereby prevent the engineered inhibitor reaching its full potential. An in silico analysis was carried out to examine the potential for further improvements to the potency and selectivity of the SFTI-based KLK4 and KLK14 inhibitors. Molecular dynamics simulations suggested that the substitutions within SFTI required to target KLK4 and KLK14 had compromised the intramolecular hydrogen bond network of the inhibitor and caused a concomitant loss of binding loop stability. Furthermore in silico amino acid substitution revealed a consistent correlation between a higher frequency of formation and the number of internal hydrogen bonds of SFTI-variants and lower inhibition constants. These predictions allowed for the production of second generation inhibitors with enhanced binding affinity toward both targets and highlight the importance of considering intramolecular cooperativity effects when engineering proteins or circular peptides to target proteases. The findings from this study show that although PS-SCLs are a useful tool for high throughput screening of approximate protease preference, later refinement by SML screening is needed to reveal optimal subsite occupancy due to cooperativity in substrate recognition. This investigation has also demonstrated the importance of maintaining structural determinants of backbone constraint and conformation when engineering standard mechanism inhibitors for new targets. Combined these results show that backbone conformation and amino acid cooperativity have more prominent roles than previously appreciated in determining substrate/inhibitor specificity and binding affinity. The three key inhibitors

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designed during this investigation are now being developed as lead compounds for cancer chemotherapy, control of fibrinolysis and cosmeceutical applications. These compounds form the basis of a portfolio of intellectual property which will be further developed in the coming years.

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List of Publications

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Refereed publications - published 1. Swedberg, J.E. and Harris, J. M. (2011) Plasmin substrate binding site cooperativity guides the design of potent peptide aldehyde inhibitors. Biochemistry DOI: 10.1021/bi201203y (IF 3.2) 2. Swedberg, J.E., de Veer, S. J., Sit, K. C., Reboul, C. F., Buckle, A. M. and Harris, J. M. (2011) Mastering the canonical loop of serine protease inhibitors: enhancing potency by optimizing the internal hydrogen bond network. PLoS ONE 6(4): e19302. doi:10.1371/journal.pone.0019302. (IF 4.4) 3. Swedberg, J. E., de Veer, S. J. and Harris, J. M. (2010) Natural and engineered kallikrein inhibitors: an emerging pharmacopeia. Biol Chem DOI: 10.1515/BC.2010.039. (IF 3.1) 4. Swedberg, J. E., L. V. Nigon, J. C. Reid, S. J. de Veer, C. M. Walpole, C. R. Stephens, T. P. Walsh, T. K. Takayama, J. D. Hooper, J. A. Clements, A. M. Buckle and J. M. Harris. Substrate-guided design of a potent and selective kallikrein-related peptidase inhibitor for kallikrein 4. Chem Biol 16(6): 633-43. (Chosen as journal cover; IF 5.7) Manuscripts in preparation

1. Harris, J. M. and Swedberg, J.E. Natural and engineered plasmin inhibitors: applications and design strategies. 2. de Veer, S.J., Swedberg, J.E., Parker, E.A., Harris, J.M. Optimal subsite occupancy and engineering of internal hydrogen bonds within the sunflower trypsin inhibitor (SFTI) enables potent inhibition of kallikrein-related peptidase 14 (KLK14). 3. Sanchez, W. Y., de Veer, S. J, Swedberg, J. E. Hong, E-J, Reid, R. C., Simmer, J. P., Walsh, T. P., Hooper, J. D., Hammond, J. L., Clements, J. A., and Harris, J. M. Proteolysis of Sex Hormone-binding Globulin (SHBG) by Kallikrein-related Peptidases Modulates Androgen Bioavailability in vitro. 4. Dong, Y., Stephens, C., Walpole, C. Swedberg, J. E., Harris, J. M., Boyle, G. M., Parsons, P. G., McGuckin, M. A. and Clements, J. A. Kallikrein 4 promotes mesenchymalepithelial phenotypic plasticity and taxol resistance in a 3D-model of serous ovarian cancer indicative of the ascites environment (Submitted to Clin Can Res).

Conference publications - oral presentations 1. Swedberg, J.E., Reid, J. C., de Veer, S. J., Hooper, J. D. and Harris, J. M. (2010) Substrate and computer guided design of potent and specific kallikrein 4 inhibitors. Australian Society for Health and Medical Research Queensland - Postgraduate Student Award Finalist. Brisbane, Australia.

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2. Swedberg, J.E., Reid, J. C., de Veer, S. J. and Harris, J. M. (2009) Computer aided design of an enhanced SFTI scaffold KLK4 inhibitor. 3rd International Symposium on Kallireins and Kallikrein-related Peptidases. Munich, Germany,

Conference publications - posters 1. Swedberg, J.E., Reid, J. C., de Veer, S. J. and Harris, J. M. (2010) Substrate and computer guided design of potent and specific kallikrein 4 inhibitors. BIT’s 3rd Annual World Cancer Congress. Singapore. 2. Swedberg, J.E., Reid, J. C., de Veer, S. J. and Harris, J. M. (2010) Substrate and computer guided design of potent and specific kallikrein 4 inhibitors. Advances in Antibody and Peptide Therapeutics. Berlin, Germany. 3. Swedberg, J. E. and Harris, J. M. (2009) Computer aided design of an enhanced SFTI scaffold KLK4 inhibitor. ICCP. Herron Island, Australia. 4. Swedberg, J. E., Laura V. Nigon, Terry P. Walsh, Thomas K. Takayama, Judith A. Clements, Ashley M. Buckle and Jonathan M. Harris (2008) Substrate guided design of a potent and specific kallikrein-related peptidase 4 inhibitor. ASMR student conference, Brisbane, Australia.

Patents 1. Swedberg, J. E. and Harris, J. M. Novel protease inhibitors (2010) International Application number: PCT/AU2009/001031; Publication No.: WO 2010017587; Publication Date: 18.02.2010. 2. de Veer, S. J., Swedberg, J. E. and Harris, J. M. Serine protease inhibitors (2011) United States provisional application No 61/426,651

Media releases 1. Flower power may bring ray of sunshine to cancer sufferers. QUT media release, May 1, 2008. 2. Joakim may have solved cancer riddle (Translated from Swedish: Joakim kan ha löst cancer gåta). Aftonbladet (Swedish national newspaper), May 4, 2008.

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Formatting note: chapters are formatted according to target publication requirements.

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Contents

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Key words

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Abstract

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List of publications

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Figures

xvii

Tables

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Chapters 1

2

Introduction

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1.1

A description of the scientific problem investigated.

24

1.2

The overall objectives of the study.

28

1.3

The specific aims of the study.

28

1.4

An account of scientific progress linking the research papers.

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2.1

Natural and engineered kallikrein inhibitors: an emerging pharmacopoeia.

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Natural and engineered plasmin inhibitors: applications and design strategies.

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Substrate-guided design of a potent and selective kallikreinrelated peptidase inhibitor for kallikrein 4.

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Mastering the canonical loop of serine protease inhibitors: enhancing potency by optimizing the internal hydrogen bond network.

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Optimal subsite occupancy and engineering of internal hydrogen bonds within the sunflower trypsin inhibitor (SFTI) enables potent inhibition of kallikrein-related peptidase 14 (KLK14).

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2.2

3

4

5

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Literature review

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6

7

8

Proteolysis of sex hormone binding globulin (SHBG) by kallikrein-related peptidases modulates androgen bioavailability in vitro.

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Substrate-guided design of potent plasmin peptide aldehyde inhibitors.

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Conclusions

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8.1 Intermolecular cooperativity.

and

intramolecular

subsite 209

8.2 Limitations of the positional scanning synthetic combinatorial library method.

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8.3 The sparse matrix library screening as a method to deconvolute PS-SCL data.

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8.4 Non-equivalence between peptide and protein cut sites.

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8.5

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Conversion of peptide substrates to inhibitors.

8.6 Using molecular dynamics simulations to refine library screening data.

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8.7

Future directions.

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8.8

Summary.

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Appendix I

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Appendix II

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Appendix III

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Appendix IV

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Abbreviations

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Figures

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2.1 2.1

2.1 2.1 2.2 2.2 2.2 2.2 2.2 2.2 3 3 3 3 3

4 4 4 4 4 4 4 5 5 5

Structural alignment of KLK1–15, KLKB1 and β-trypsin. Comparison of the activity of naturally occurring and engineered kallikrein inhibitors and structural overlay of the conserved binding loop of protein kallikrein inhibitors. Phage-display cycle. Tetrahedral transition-state analogues of serine proteases.

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Schematic domain structure of plasminogen. Fibrin clot formation and fibrinolysis. Plasminogen activation by uPA at the cell surface. uPA and plasmin MMP activation and ECM degradation. Structural alignment of the catalytic domains of plasminogen (µ-plasminogen) and related serine proteases. Structure of Kunitz-type and Kazal-type domains.

57 59 60 65

Amidolytic activity of KLK4 against sparse matrix library pNA substrates. Inhibition of serine protease proteolytic activity by SFTI and SFTI-FCQR. Stability of SFTI-FCQR in contact with prostate cancer cells In vitro. Effect of SFTI-FCQR on calcium release in cell-based assays. Structural characteristics of the protease-inhibitor interfaces for the trypsin/SFTI and the modeled KLK4/SFTI-FCQR complex.

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Representation of a trypsin/SFTI-1 complex and internal hydrogen bonding within SFTI variants during MD. RMSD analysis for SFTI variants during MD. Relationship between IC50 and number of internal hydrogen bonds. Assesment of koff for SFTI_FCQR Asn14 Selective inhibition of serine protease proteolytic activity by SFTI-FCQR Asn14. Stability of SFTI variants in contact with prostate cancer cells in vitro. Bioavailability of SFTI-FCQR Asn14 in mice. Positional scanning screen of the extended substrate specificity of KLK14. Sparse matrix screen of the extended substrate specificity of KLK14. Schematic structure of SFTI-1. xviii

38 41 45

67 73

107 108 108 109

120 121 123 123 124 125 125

139 140 142

5 5

6 6 6 6 6 6 6

7 7 7

Inhibition of serine protease digestion of fibrinogen by SFTI variants. Average internal hydrogen bonds during molecular dynamics simulations for SFTI-WCVR N14 residue 12 variants. GST interaction analyses between SHBG and pro-KLKs. SHBG is cleaved by KLK4 and KLK14. N-terminal sequencing of SHBG proteolysis fragments to determine KLK4 and KLK14 cut sites. DHT modulates KLK proteolysis of SHBG. SHBG cleaved by KLK4 has identical steroid binding properties SHBG prolongs androgen bioavailability in cell culture. Proteolysis of SHBG modulates androgen bioavailability in cell culture. Amidolytic activity of plasmin against a sparse matrix library of peptide-pNA substrates. Inhibition of serine protease proteolytic activity by peptide aldehydes. Inhibition of in vitro fibrinolysis by peptide aldehyde inhibitors.

Appendix I

144 145 168 169 170 171 173 174 175

194 198 199

Comparison of actual rates and average rates of hydrolysis (mOD/min) of tetra peptide-pNAs.

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Conformations of cleavable and non-cleavable protein loops.

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Increased paclitaxel chemosensitivity by inhibition of KLK4.

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Appendix IV Amidolytic activity of plasmin against a sparse matrix library of peptide-pNA substrates.

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Appendix IV Inhibition of serine protease proteolytic activity by peptide aldehydes.

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Appendix IV Inhibition of plasmin fibrinolysis in vitro by peptide aldehyde inhibitors.

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Appendix I

Appendix I

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Tables

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2.1.1 Extended substrate specificity of KLK1–15 and KLKB1.

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2.2.1 Substrate specificity of plasmin/μ-plasmin. 2.2.2 Plasmin protein inhibitors.

69 71

3

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3 4 4

5 5 5 5

6 6

7 7 7

KM, kcat and catalytic efficiency (kcat/KM) for para-nitroanilide substrates. Inhibitory properties of wild-Type SFTI and SFTI-FCQR. In silico internal hydrogen bond analysis of SFTI-FCQR residue 14 variants. Inhibitory properties of SFTI-1, SFTI-FCQR and SFTI-FCQR residue 14 Variants.

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122 122

KLK14 kinetic constants for peptide substrates. KLK14 Inhibition constants for SFTI variants. KLK14 inhibition constants for of SFTI-WCVR N14 residue 12 variants. Average internal hydrogen bonds of SFTI-WCVR N14 residue 12 variants.

141 143

Kinetic constants for SHBG and peptide-pNA KLK digests. Cleavage sites for KLK4 and KLK14 proteolysis of SHBG revealed by N-terminal sequencing.

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Design of sparse matrix library of peptides. Plasmin kinetic constants for peptide substrates. Kinetic constants of plasmin inhibitors.

193 195 197

Appendix III

Kinetic Constants of Plasmin Inhibitors

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146 146

171

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Statement of Original Authorship

The work contained in this thesis has not been previously submitted to meet requirements for an award at this or any other higher education institution. To the best of my knowledge and belief, the thesis contains no material previously published or written by another person except where due reference is made.

Signature

Date

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CHAPTER 1

Introduction

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1.1

A description of the scientific problem investigated

Proteases (proteolytic enzymes; peptidases; proteinases) are enzymes that hydrolyse peptide bonds in peptides or proteins. Proteolytic events form a key step in post-biosynthetic processing of polypeptide chains and can dictate the localization and activity of proteins, protein-protein interactions as well as signal initiation and amplification. They are therefore central to many diverse physiological processes including prohormone processing, cell proliferation, tissue morphogenesis, tissue remodelling, immunity, synaptic plasticity, apoptosis, ion transport, homeostasis, and mitochondrial homeostasis. Consequently, a detailed understanding of protease structure and function is essential to appreciate the many aspects of physiological and pathological processes. Consistent with the scope of protease function, aberrant proteolytic activity has been linked to a spectrum of pathologies including cancer, Alzheimer’s disease, cystic fibrosis, allergies, renal fibrosis, inflammatory diseases and chronic wounds, to mention a few. Additionally, proteases commonly mediate host invasion by viruses and animal parasites. Accordingly, the development of potent and specific inhibitors of proteases is of interest both to further the understanding of protease function in various biological systems and as an avenue for treatment of protease-linked diseases. Involvement in such a wide range of processes reflects the diversity of proteases, with the evolution of over 600 known human enzymes of this class (http://merops.sanger.ac.uk/). Proteolytic enzymes have traditionally been classified according to the amino acid and/or cofactor acting as the nucleophile during peptide bond hydrolysis. These include aspartic, cysteine, serine, metallo, glutamic/aspartic and threonine families, while the work in this thesis will focus on the serine type only. However, the increasing number of described proteases has lead to more stringent evolutionary based classification criteria comparing amino acid sequence homology and tertiary structure to subdivide the catalytic groups into clans and 24

families. Proteases within clans share similar tertiary structure while families have significant sequence similarity. Both types of classifications are useful when interpreting protease function and designing high affinity inhibitors to regulate protease activity. Inhibitors may function by acting reversibly or irreversibly on the nucleophile/cofactor or another residue directly involved in the chemistry of peptide bond cleavage as occurs for some small molecule inhibitors. Protein based inhibitors may bind reversibly or by forming covalent complexes while commonly capitalizing on additional specific features of the protease fold and amino acid sequence to differentiate between various targets. Rational design of inhibitors requires detailed knowledge regarding the architecture of the protease and/or its functional chemistry. Numerous sources provide this information, including known protease cut sites in proteins and peptides, cleavage sites determined by screening of combinatorial and non-combinatorial peptide libraries, protein structures determined from crystallised proteases (X-ray diffraction) or in solution (nuclear magnetic resonance) and equivalent structures of known protease inhibitors. The utility and limitations of these various resources for design of potent and selective inhibitors are discussed in detail in Chapter 2.1 with a particular focus on the serine protease family of kallikrein/kallikrein-related proteases. This peer reviewed article, which was published in Biological Chemistry in 2010 and represents the first comprehensive review on this topic, compiled current knowledge regarding naturally occurring and engineered kallikrein inhibitors, kallikrein substrate preferences, kallikrein structures and design strategies to specifically target members of this family of protease. Chapter 2.2 presents a review that discusses similar topics while centering on a single serine protease plasmin. To date this is the first review to bring together the details of plasmin structure, function and inhibition with a focus on ways of applying this information to design inhibitors for this target. Collectively Chapter 2.1 and Chapter 2.2 discuss the potentials and

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limitations of substrate guided inhibitor design methods, which is the principal topic for this thesis. The term substrate in this context is used loosely to include standard mechanism inhibitors, for which cleavage of the scissile bond forms part of the inhibitory mechanism and technically makes them substrates that are extremely slow to hydrolyze. There are three other types of protease substrate encompassed by this investigation. Firstly, short amino acid sequences that do not adopt secondary structures, such as β-sheets or α-helices, are referred to as peptides. These may however form part of the secondary structure of the target protease in the form of an extended β-sheet on complex formation. Secondly, circular peptides are cyclised head-to-tail through a peptide bond and/or via disulfide bond(s), resulting in proteinlike secondary structures. Finally, there are proteins with a defined tertiary structure, which are often constrained by disulfide bonds. Consequently, amino acid sequences in peptides with a high degree of backbone flexibility may interact differently with proteases compared to those that are constrained in the loops of proteins and circular peptides. However, after reviewing current literature regarding serine protease substrate recognition in Chapter 2 it became apparent that protein and peptide cut sites are commonly seen as being equivalent. For example, it is not unusual to identify protein substrates in database searches, based upon protease cleavage of a short peptide sequence alone. Hence, the nuances between peptide and protein cleavage do not seem to be widely appreciated. Another phenomenon evident in protease substrate recognition is protease and substrate subsite cooperativity. This type of cooperativity is distinct from allosteric cooperativity where binding of a molecule to a site distant to the active site changes the binding affinity of a substrate. Rather, subsite cooperativity refers to how the contribution of one amino acid to binding affinity and/or efficiency of substrate cleavage is dependent on its

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immediate or more distant neighbours. Subsite cooperativity may be intermolecular where neighbors of a residue in the substrate modulate the contribution of that particular residue to binding affinity. Alternatively, substrate subsite cooperativity can be intramolecular where interactions between residues affect the rate of cleavage of the scissile bond by the protease. In addition to these clearly defined instances, the two types of cooperativity are inter-related with the possibility that either intramolecular or intermolecular subsite cooperativity affect binding affinity and the rate of hydrolysis. Although a number of instances identifying subsite cooperativity have been reported, this area of research has not been extensively explored (Chapter 2.1 and Chapter 2.2). Protease substrate specificity is either determined using average rates of hydrolysis for combinatorial libraries of peptides (positional scanning synthetic combinatorial library; PS-SCL), or alternatively by screening individual substrates. PS-SCLs consist of a number of sub-libraries. Each of these peptide sub-libraries represents one protease binding site and is used to probe the complementary substrate binding site of the protease. This is achieved by including a single amino acid for a particular subsite while the other subsites of the peptide contain mixtures of all amino acids. Repeating this for all natural amino acids requires 20 sub-libraries for each protease binding site. Preferred protease cleavage sequences are thereby determined by consecutive screening of each substrate binding site using 20 fixed amino acid sub-libraries of peptides. However, since the various binding sites are screened independently of each other, PS-SCLs are inherently unable to identify subsite cooperativity. Prior to this study, there was no critical assessment of the correlation between protease preferences as predicted by screening against PS-SCLs of peptides and cleavage of individual peptides. The literature reviews presented in Chapter 2.1 and Chapter 2.2 suggested that there were significant discrepancies, but they were not generally well appreciated. Results from PS-SCL screens are not commonly

27

subjected to extensive validation, yet are presented as being representative of single peptide cleavage. Interpretation of PS-SCL data is further complicated by a common failure to accurately determine sequence diversity in a given library, which may explain the variability of data sets produced by different laboratories.

1.2

The overall objectives of the study

The overall objective of this study was to expand current understanding of important determinants of serine protease substrate and inhibitor interactions. The project was designed to determine whether currently used combinatorial peptide substrate libraries can accurately describe serine protease specificity for non-combinatorial substrates. The second part of the study was premeditated to define structural features of serine proteases substrates that may be utilised to produce potent and selective inhibitors, with particular focus on different types of intramolecular constraints.

1.3

The specific aims of the study

1.

To critically assess the correlation between combinatorial and non-combinatorial library screening methods for determination of protease substrate specificity (Chapter 3, 5 and 7).

2.

To identify structural determinants of serine protease substrates that produce potent and selective inhibitors (Chapter 3, 5 and 7).

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3.

To define intramolecular inhibitor structural constraints that correlate with more potent and selective inhibitors (Chapter 4, 5 and 6).

1.4

An account of scientific progress linking the research papers

To systematically determine if PS-SCLs could predict the optimal cleavage site of a protease, a peptide library was constructed that contained individually synthesised sequences. The resulting library (sparse matrix library; SML) incorporated all possible combinations of sequences suggested by three independent PS-SCL screens to be preferred by the serine protease kallikrein 4 (KLK4). This approach identified an amino acid sequence that was highly selective for KLK4 as a consequence of intermolecular subsite cooperativity, with an elevated rate of hydrolysis compared to those sequences suggested by either of the previous PS-SCL screens. Production of a peptide aldehyde inhibitor using this sequence resulted in a more potent inhibitor than for the corresponding peptide suggested by PS-SCL. Further, substituting this sequence into the sunflower trypsin inhibitor (SFTI), a 14 amino acid bicyclic peptide, produced a highly potent and selective KLK4 inhibitor. This compound was particularly stable in cell culture and blocked protease activated receptor signalling by KLK4 in vitro. These findings were reported in a peer reviewed article in the journal Chemistry & Biology in 2009 and are presented in Chapter 3. This KLK4 inhibitor subsequently showed a synergistic effect with paclitaxel in reducing growth of ovarian cancer cells in vitro (Appendix I), making this compound a candidate for further therapeutic development. The utility of the SML was confirmed by screening two other serine proteases, kallikrein 14 (KLK14) and plasmin. In a paper presented in Chapter 5, the approximate substrate preference of KLK14 was first determined by a PS-SCL followed by a SML screen to further refine the specificity of this protease. As seen for KLK4, intermolecular subsite cooperativity

29

prevented the PS-SCL from identifying the most preferred substrates, which were ultimately revealed by SML screening. Substituting sequences that incorporated these features into SFTI produced potent KLK14 inhibitors with some selectivity over other serine proteases including KLK5, trypsin and matriptase, but not KLK4. Similarly, Chapter 7 presents a paper detailing the screening of plasmin against a SML based upon three previous PS-SCLs, which identified a small subset of highly preferred substrate sequences dependent on intermolecular cooperativity for efficient hydrolysis. Corresponding peptide aldehydes produced high affinity transition state inhibitors of plasmin. One of these is to date the most potent small molecule plasmin inhibitor available that still maintains selectivity over plasma kallikrein (which is noted for its similar substrate preference). Substitution of a peptide sequence into a protein may have unexpected consequences as a result of reduced backbone flexibility and/or cooperativity. Firstly, constraint provided by the protein loop may alter the conformation of the sequence’s peptide backbone and the spatial distribution of amino acid moieties and thereby intermolecular cooperativity. Secondly, the inserted amino acids can disrupt highly optimised features of the structural arrangement of the binding loop important for intramolecular cooperativity dictating the rate of hydrolysis. For instance, in the case of a standard mechanism inhibitor, the rigidity of the backbone after cleavage at the scissile bond ensures potent inhibition through a stable acyl-enzyme intermediate. Conversely, a protein substrate benefits from a more relaxed loop conformation that allows for an efficient leaving group after catalysis. Consequently, the effect of inserting the preferred peptide substrate sequences of KLK4 and KLK14 into SFTI was further investigated using in silico molecular dynamics simulations. A paper accepted in the journal PlosOne is presented in Chapter 4 and summarises these findings in regards to KLK4. This investigation indicated that, although inserting the KLK4

30

preferred sequence into SFTI made the inhibitor selective, the binding loop conformation and stability of this standard mechanism inhibitor was compromised. In silico molecular dynamics simulations suggested that the extensive intramolecular (internal) hydrogen bond network present in the wild type SFTI was greatly reduced by substitutions to target KLK4. Further, in silico analysis indicated those substitutions that restored the internal hydrogen bond network and binding loop conformation correlated with increased potency of inhibition in vitro. Similarly, an in silico study of the structural consequences of re-engineering SFTI to target KLK14 was carried out. These findings are presented in a paper in Chapter 5 and concurred with data for SFTI-based KLK4 inhibitors, where a similar relationship was identified between internal hydrogen bonds, binding loop stabilization and high affinity binding. Taken in combination, these results highlight how subsite cooperativity dictates differential protease interaction with either peptides or circular peptides/proteins. A related strategy to investigate these phenomena involves concurrent production of a peptide substrate based on a protein cleavage site sequence and substitution of the same residues into the protein-like inhibitor SFTI. This allows for evaluation of substrate sequence recognition in the context of different constraints. In a paper constituting Chapter 6, KLK4 and KLK14 cleavage sites were identified in the sex hormone binding globulin protein (SHBG). Kinetic analyses revealed that these were not highly preferred peptide substrates compared to those deduced by peptide screening methods in Chapter 3 and Chapter 5. However, substitution of the KLK14 SHBG cleavage site into the highly constrained SFTI produced an inhibitor with comparable binding affinity to those based upon sequences highly optimised by peptide substrate screening methods (Appendix II). This demonstrates that for these sequences the backbone constraint provided by the protein context was vital for efficient substrate recognition. Indeed, overlaying the KLK14 cut site in SHBG and SFTI showed very similar

31

backbone topologies with a slightly concave conformation that allowed for formation of an extended β-sheet with the protease (Appendix II). Conversely, the highly optimised KLK4 peptide cleavage site presented in Chapter 3 occurs in a surface exposed loop of the protein laminin, although this protein is not a KLK4 substrate. Comparing this binding loop to those seen for SFTI and SHBG revealed a convex conformation that prevents positioning of the scissile bond for cleavage. These findings collectively indicate that peptide and protein substrates/inhibitors should be considered as separate cases by virtue of their different backbone constraint and suggests that substrate conformation is equivalent in importance to amino acid sequence in substrate recognition. The combined conclusions from this thesis together with plans for further development of the strategies described here are discussed in Chapter 8. These include the limitation of the combinatorial peptide libraries imposed by cooperativity and observations on the utility of the SML technique. Finding sequences that include intermolecular cooperativity is in itself important since these substrates are likely to interact with distinctive features of a protease to enable production of highly potent and selective inhibitors. However, substitution of unconstrained peptide cleavage sites into proteins or highly constrained circular peptides may have a significant effect on how the particular amino acid sequence is displayed. At the same time, sequence exchange may have reciprocal effects on the protein scaffold, significantly altering its conformation. This calls for a holistic view of protease cleavage sites in peptides, protein substrates and standard mechanism inhibitors that recognises the role of backbone constraint and conformation in addition to subsite occupancy. Such an approach is likely to greatly accelerate the development of potent and specific peptide and protein-based inhibitors in the future.

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CHAPTER 2

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Natural and Engineered Kallikrein Inhibitors: an Emerging Pharmacopoeia

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Article in press - uncorrected proof Biol. Chem., Vol. 391, pp. 357–374, April 2010 • Copyright
by Walter de Gruyter • Berlin • New York. DOI 10.1515/BC.2010.037

Review

Natural and engineered kallikrein inhibitors: an emerging pharmacopoeia

Joakim E. Swedberg, Simon J. de Veer and Jonathan M. Harris* Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland 4059, Australia * Corresponding author e-mail: [email protected]

Abstract The kallikreins and kallikrein-related peptidases are serine proteases that control a plethora of developmental and homeostatic phenomena, ranging from semen liquefaction to skin desquamation and blood pressure. The diversity of roles played by kallikreins has stimulated considerable interest in these enzymes from the perspective of diagnostics and drug design. Kallikreins already have well-established credentials as targets for therapeutic intervention and there is increasing appreciation of their potential both as biomarkers and as targets for inhibitor design. Here, we explore the current status of naturally occurring kallikrein protease-inhibitor complexes and illustrate how this knowledge can interface with strategies for rational re-engineering of bioscaffolds and design of small-molecule inhibitors. Keywords: bioscaffold; drug design; inhibitor; phage display; protease positional scanning synthetic combinatorial library; sunflower trypsin inhibitor.

Introduction

ulated activation cascades, suggesting an involvement in a diverse range of physiological processes (Pampalakis and Sotiropoulou, 2007). Both liver-derived KLKB1 and tissuederived KLK1, as well as KLK2 and KLK12 in vitro (Giusti et al., 2005), participate in the progressive activation of bradykinin, a bioactive peptide involved in blood pressure homeostasis and inflammation initiation (Bhoola et al., 1992). Although this is the only demonstration of classical kininogenic activity that was the original hallmark of kallikrein proteases, the contribution of subsets of KLKs to vital physiological processes is well appreciated. Prostateexpressed KLK2, 3, 4, 5 and 14 are involved in seminogelin hydrolysis (Lilja, 1985; Deperthes et al., 1996; Takayama et al., 2001b; Michael et al., 2006; Emami and Diamandis, 2008), KLK6 and 8 have reported functions in defining neural plasticity (Shimizu et al., 1998; Scarisbrick et al., 2002; Tamura et al., 2006; Ishikawa et al., 2008) and KLK5, 7, 8 and 14 assist in epidermal remodelling via controlled proteolysis of corneodesmosomal proteins (Caubet et al., 2004; Brattsand et al., 2005; Stefansson et al., 2006; Kishibe et al., 2007). These kallikrein-driven phenomena are critical processes within the prostate, central nervous system and skin, respectively. In parallel to identification of the kallikrein locus (and serine proteases generally), attempts have been made to produce inhibitors to regulate these enzymes and thus maintain the delicate homeostatic balance between degradation and synthesis in crucial biological pathways. It has been unequivocally shown that failure of inhibition in kallikreinrelated pathways causes detrimental effects that in turn have led to a burgeoning interest in the design and synthesis of kallikrein-specific inhibitors.

The kallikrein peptidase family Kallikrein structure

The extended kallikrein peptidases are defined by homology to either of two ancestral serine proteases, plasma kallikrein or tissue kallikrein, which differ in their gene location, sequence and structure. Whereas plasma kallikrein (KLKB1, located at 4q34-q35) has no related homologue, the tissue kallikrein-related peptidases (KLKs) form a highly conserved multi-gene locus encoding enzymes with either trypsin- or chymotrypsin-like activity (Yousef and Diamandis, 2001; Clements et al., 2004). Fifteen KLKs have been characterised to date, arranged as a tandemly clustered array on chromosome 19q13.3-13.4 (Clements et al., 2004). This represents the largest known continuous collection of proteases within the human genome (Puente et al., 2003). Typically, KLK proteins are produced according to strict temporal and spatial expression patterns and function in reg-

Collectively, the KLKs exhibit a number of structural and functional similarities that need to be considered and can be exploited in targeted inhibitor design. All tissue KLK genes consist of five exons of almost identical size with intermittent introns displaying a fully conserved phase (Yousef and Diamandis, 2001). This has consequences in terms of translated protease sequence; each KLK contains the conserved serine protease catalytic triad (His57, Asp102, Ser195) and N-terminal regulatory pre- and pro- sequences, meaning that KLKs are expressed as inactive precursors (zymogens). Although the sequence homology within the classical KLK cluster (KLK1–3) is markedly higher (62–72%) than similarities with any of the more recently characterised KLKs (25–49%) (Harvey et al., 2000), emerging crystallographic

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studies have revealed that KLK tertiary structure across the locus is highly conserved (Figure 1). Indeed, the kallikrein ‘molecular chassis’ conforms to the canonical trypsin fold, consisting of an almost entirely b-sheet arrangement (SCOP trypsin-like serine proteases; SCOP ID 50493). Furthermore, although the KLKB1 gene encodes four additional N-terminal domains, its level of sequence similarity across the catalytic domain is not dissimilar to that observed for the tissue KLK locus (Figure 1).

Rationale for kallikrein inhibition

Consistent with the important role of kallikrein proteases in normal physiology, defective control of expression or activity is strongly linked to development of disease. Most prominent is the potential significance of KLKs to certain cancers typified by aberrant KLK expression including lung, pancreatic, colon (Yousef et al., 2004) and hormone-dependent cancers, particularly those of the prostate (Magklara et al., 2000;

Figure 1 Structural alignment of KLK1–15, KLKB1 and b-trypsin. (A) Ribbon plot of KLK1 (PDB accession no. 1SPJ) as a representative KLK structure. b-Sheets and a-helices are shown in yellow and blue, respectively, with important features highlighted in green and purple, with catalytic residues displayed as stick models. (B) Sequence similarity between KLK1–15 and KLKB1 mapped onto the surface of b-trypsin with conservation visualised as a gradient from blue (high), cyan, green and light green to yellow (low). The alignment was produced in Swiss-PdbViewer 4.0.1 using the KLK1, 3-7, KLKB1 and btrypsin crystal structures (PDB accession nos. 1SPJ, 2ANY, 2ZCH, 2BDH, 2PSX, 1L2E and 2QXI, 1SFI) and KLK2 and 8–15 models created using Swiss Model (Guex et al., 2009). (C) Structural alignment of sequence conservation between KLK1–15, KLKB1 and btrypsin. Location of b-sheets and a-helices are indicated by yellow arrows and blue cylinders, respectively, with catalytic residues shown in cyan. Important features are highlighted in green and purple and cysteine residues participating in disulfide bonds are shown in yellow. Completely conserved residues and conservative substitutions are shown in dark grey and light grey, respectively.

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Petraki et al., 2003; Veveris-Lowe et al., 2005), ovaries (Dong et al., 2001; Yousef et al., 2003; Prezas et al., 2006) and breast (Yousef et al., 2002; Zhang et al., 2006; Pampalakis et al., 2009). Contrasting effects of KLK overexpression on cancer physiology have been proposed. KLK overexpression can provide a pathway for tumour development and metastasis by degrading the restrictive localised tissue architecture and shifting the cellular signalling axis to drive increased proliferation. Alternatively, differential KLK expression can have a protective function in certain cancers. A considerable amount of research has been devoted to exploring the utility of KLK panels as hormone-dependent cancer biomarkers (Borgono and Diamandis, 2004; Clements et al., 2004). KLK3 (prostate-specific antigen, PSA) remains the gold-standard biomarker for prostate cancer diagnosis and prognosis (Stamey et al., 1987; Catalona et al., 1991), albeit with some degree of controversy. In the context of the skin, a role for KLKs has been identified in the rare but severe disorder Netherton syndrome (OMIM: 256500) (Chavanas et al., 2000; Descargues et al., 2005; Briot et al., 2009), as well as the milder but much more frequent condition acne rosacea (Yamasaki et al., 2007; Stefansson et al., 2008). Furthermore, KLK1 and KLKB1 have been implicated in a number of diseases associated with dysregulation of the kallikrein/kinin system, such as cardiovascular, renal, inflammatory and gastrointestinal tract disease (Devani et al., 2002; Stadnicki et al., 2003). Finally, KLK6 and KLK8 have potential roles in neurodegenerative conditions such as Alzheimer’s disease (Little et al., 1997; Shimizu-Okabe et al., 2001), multiple sclerosis (Terayama et al., 2005; Scarisbrick et al., 2008), epilepsy (Momota et al., 1998), synucleinopathies (Iwata et al., 2003) and general central nervous system inflammation (Blaber et al., 2004). The identification of dysfunctional KLK activity as a major pathological influence suggests that targeted inhibition of relevant KLKs is likely to be an effective therapeutic strategy. Transient inhibition of certain kallikrein-mediated processes has already been explored and the use of aprotinin to reduce peri-operative bleeding in cardiac surgery by inhibiting proteases involved in haemostatic and inflammatory processes was widespread (Fritz and Wunderer, 1983; Terrell et al., 1996). Although initially thought to be successful, this therapy has recently been withdrawn from use following the result of several larger clinical trials that were terminated before completion because of a persistent trend of increased mortality (Murkin, 2009). Since this outcome is very recent, the probable physiological explanation is yet to be determined, although one might speculate that it involves interference with unrelated biological pathways owing to the broad range activity of aprotinin, much like the first-generation matrix metalloprotease (MMP) inhibitors.

Naturally occurring kallikrein inhibitors Although proteases drive numerous vital physiological processes, activity must be tightly regulated to ensure correct spatial and temporal delivery. The function of mature pro-

teases is commonly controlled by protein-based inhibitors that adopt the form of a non-hydrolysable substrate. Whereas almost all inhibitors bind to their cognate protease via an exposed motif, the mechanism by which they achieve inhibition varies from canonical inhibitors that simply block the protease active site to serpins that irreversibly disturb the delicate conformation of the protease (Laskowski and Kato, 1980). A number of canonical and serpin inhibitors of KLK proteases have been identified. These include physiological inhibitors that provide an essential regulatory influence on KLK-mediated processes and activation cascades, as well as broad-range, exogenous inhibitors that function as valuable research tools for determining the significance of KLK activity in experimental systems. Notable KLK inhibitors are discussed in more detail below and a comprehensive inhibitory profile of natural and engineered inhibitors is provided in Figure 2A–D. Canonical inhibitors

Standard-mechanism or canonical inhibitors currently form the largest class of protein-based inhibitors. Here, protease inhibition generally involves contact with the target protease via the canonical loop, a characteristic exposed binding motif on the inhibitor surface that is complementary to the activesite cleft. This interaction is often referred to as analogous to the formation of a protease-substrate complex, since both are non-covalent, tight-binding and reversible with contact occurring across extended b-sheets (Tyndall et al., 2005). However, in the protease-inhibitor complex, hydrolysis of the reactive-site P1-P19 peptide bond is rare, preventing subsequent dissociation of the complex and temporarily removing the ability of the protease to bind substrate (Laskowski and Kato, 1980). The importance of this binding mechanism is highlighted by the fact that the conformation of the canonical loop is very similar, even among diverse families of protease inhibitors (Figure 2E). Kunitz-domain inhibitors

Canonical inhibitors of this class are characterised by the Kunitz domain, a motif spanning 50–60 residues that contains the inhibitory binding loop within a central anti-parallel b-sheet (Figure 2E). Considerable rigidity across the domain is imparted by a network of conserved disulfide bonds (Hynes et al., 1990; Perona et al., 1993). Most prominent is bovine pancreatic trypsin inhibitor (BPTI), also previously referred to as kallikrein inactivator, aprotinin or trasylol. Following isolation and crystallisation from bovine pancreatic tissue extracts, biochemical characterisation revealed that BPTI was a potent inhibitor of not only bovine trypsin, but also KLKB1 (Kraut et al., 1930). Later studies that extended to the classical tissue kallikrein locus reported inhibitory activity against KLK1 (Hofmann and Geiger, 1983) and KLK2 (Geiger et al., 1980). More recently, BPTI/aprotinin has been widely used as a non-specific reagent to block the activity of kallikrein proteases in vitro, including KLK7 (Lundstrom and Egelrud, 1988), KLK5 and 14 (Brattsand et al., 2005), and KLK2 and 4 (Mize et al., 2008).

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BPTI has no homologue expressed in humans and therefore is not an endogenous modulator of kallikrein proteases, but several potent inhibitors of KLKB1 and KLK1 have been isolated from human tissue, including tissue factor pathway inhibitor-2 (TFPI-2) (Petersen et al., 1996) and Kunitz-type protease inhibitor domains from Alzheimer amyloid precur-

sor protein (APP) and its homologue APPH (Petersen et al., 1994). A further KLKB1 and KLK1 inhibitor, serine peptidase inhibitor Kunitz-type 2 (SPINT2) was later isolated from human placental tissue and termed bikunin because of its double-headed Kunitz domain structure (Delaria et al., 1997). Plant material has also proven to be a rich source of

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.

Figure 2 Comparison of the activity of naturally occurring and engineered kallikrein inhibitors and structural overlay of the conserved binding loop of protein kallikrein inhibitors. Representation of the relative kallikrein inhibitory activity for an extensive selection of reported naturally occurring (blue), engineered protein (orange) and synthetic small-molecule (green) inhibitors. Data were compiled using the reported Ki (canonical inhibitors, panel A and synthetic inhibitors, panel B), IC50 (metal ions, panel C) or ka (covalent inhibitors, panel D) value for each kallikrein-inhibitor complex. Importantly, the relative inhibition values encompass different modes of inhibition and, undoubtedly, different experimental conditions, and therefore solely provide a relative comparison and should not be taken as absolute. Abbreviations: APP(H) KPI, Alzheimer amyloid precursor protein (homologue) Kunitz protease inhibitor; BbTI, Bauhinia bauhinioides trypsin inhibitor; BfTI, Bauhinia forficata trypsin inhibitor; BuXI, Bauhinia ungulate factor Xa inhibitor; BvTIp, Bauhinia variegata trypsin inhibitor, purple variety; CeKI, Caesalpinia echinata kallikrein inhibitor; CMTI, Cucurbita maxima trypsin inhibitor; EcTI, Enterolobium contortisiliquum trypsin inhibitor; LlTI, Leucaena leucocephala trypsin inhibitor; PAI-1, plasminogen activator inhibitor-1, STI, soybean trypsin inhibitor; SFTI, sunflower trypsin inhibitor; SLPI, secretory leukocyte protease inhibitor; SwTI, Swartzia pickellii trypsin inhibitor. (E) Overlay of the binding loops from various classes of naturally occurring kallikrein inhibitors (inhibitor/class/PDB accession number): LEKTI domain 6/Kazal/1HOZ; aprotinin/Kunitz/2FTL; Barley Bowman-Birk inhibitor/Bowman-Birk inhibitor/1TX6; a1-antitrypsin/Serpin/1OPH; SFTI/Bowman-Birk-like/1SFI; E. coli trypsin inhibitor/Ecotin/1EZU; bound to the active site of b-trypsin. Trypsin is shown as grey ribbons, with catalytic residues as stick models. The inhibitors are shown as yellow b-sheets and green coils. Note that all inhibitors interact with the protease via an extended b-sheet (black arrow).

Kunitz-type compounds that inhibit KLKs; KLKB1 (Oliva et al., 1999), KLK7 (Lundstrom and Egelrud, 1988), KLK5 and 14 (Brattsand et al., 2005) are inhibited by soybean trypsin inhibitor (SBTI). Inhibition of KLKB1 has also been demonstrated using novel compounds from Enterolobium, Leucaena, Swartzia and several Bauhinia species (Sampaio et al., 1996), as well as Caesalpinia echinata kallikrein inhibitor (CeKI) (Cruz-Silva et al., 2004). Kazal-domain inhibitors

Lympho-epithelial Kazal-type-related inhibitor (LEKTI) is produced as a multi-domain serine protease inhibitor encoded by the SPINK5 gene (chromosome 5q31-32) (Magert et al., 1999). Within the skin and thymus, the LEKTI pro-protein is processed into up to 15 individual subunits. Structurally, the resulting fragments are typified by a Kazal-like domain arrangement; an anti-parallel b-sheet bordered by two short a-helices is held together by conserved disulfide links. Most LEKTI domains carry basic residues (Arg or Lys) at their putative P1 sites, suggesting that trypsin-like proteases are likely targets for LEKTI-derived peptides (Magert et al., 1999). A range of LEKTI fragments can modulate KLK activity, albeit with differing efficiency; KLK5, 7 and 14 are inhibited by LEKTI D8–11 and LEKTI D5 (Deraison et al., 2007), and KLK5 and 7 are inhibited by LEKTI D6–99 (Schechter et al., 2005) and LEKTI D6 (Egelrud et al., 2005). This activity, in synergy with physiological factors such as pH, provides an essential regulatory influence on the cascade of kallikrein proteases associated with desquamation (Borgono et al., 2007b; Deraison et al., 2007). An additional SPINK-related product, LEKTI2 encoded by SPINK9, has recently been identified within the skin and shows KLK5-specific inhibition restricted to the palmoplantar epidermis (Brattsand et al., 2009; Meyer-Hoffert et al., 2009). Other canonical inhibitors

Aside from the classical Kunitz- and Kazal-type inhibitors, several other prominent canonical inhibitors of KLKs have

been identified. Purified from the periplasm of Escherichia coli, ecotin is a 32-kDa dimeric serine protease inhibitor with broad-range activity. Characterisation revealed that it is a very potent inhibitor of proteases of the contact activation system, including KLKB1 (Ulmer et al., 1995). Hirustasin, a serine protease inhibitor isolated from the medical leech Hirudo medicinalis, contains a single antistasin-like domain and is a potent inhibitor of KLK1, but not KLKB1 (Sollner et al., 1994). A detailed investigation of KLK inhibitors isolated and purified from stratum corneum extracts identified the elafin-like protease inhibitor antileukoprotease as a skinexpressed KLK7 inhibitor and the potato type-1 inhibitor eglin C as an exogenous inhibitor (Franzke et al., 1996). More recently, several KLK inhibitors have been isolated from plant material; Cucurbita maxima trypsin inhibitor (CMTI) -I and -II exhibit inhibitory activity against serine proteases of the clotting cascade, including KLKB1 (Grzesiak et al., 2000a), and sunflower trypsin inhibitor (SFTI) is a non-specific Bowman-Birk-like inhibitor of KLK4 (Swedberg et al., 2009). Serpins

Abundant in circulating human plasma, serpins are large protein-based inhibitors that irreversibly attenuate the activity of their target protease. Like canonical inhibitors, contact with the protease is made via an extended b-sheet (Figure 2E). However, the serpin mechanism of inhibition is unique in that it is characterised by catalysis of the P1-P19 peptide bond, which causes both a change in the serpin conformation and formation of a protease-inhibitor covalent bond (Loebermann et al., 1984). Recent crystallographic studies have further clarified this phenomenon. Since the protease is tightly linked to the inhibitor, the serpin structural change due to cleavage at the reactive centre induces a shift in conformation of the bound protease (Huntington et al., 2000). The resulting loss of protease structure has terminal effects on catalytic ability, namely distortion of the catalytic triad via displacement of Ser195 and collapse of vital interactions formed during zymogen activation (Huntington et al., 2000).

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Several endogenous serpin KLK inhibitors have been identified to date. Best characterised are those found in the circulating plasma, such as a2-macroglobulin, antithrombin III, a1-antitrypsin, a2-antiplasmin and protein C inhibitor, which inhibit KLKB1 (Gallimore et al., 1979; Schapira et al., 1982), KLK2 (particularly protein C inhibitor) (Deperthes et al., 1995; Frenette et al., 1997) and KLK3 (Christensson et al., 1990). The search for additional serum-based inhibitors for KLK1 other than a1-antitrypsin (Geiger et al., 1981) led to the isolation and characterisation of kallistatin, a novel 58-kDa serpin that complexes with KLK1 in vitro more readily than other circulating inhibitors (Zhou et al., 1992). Furthermore, the recently identified interaction between KLK8 and serpin B6 (Scott et al., 2007) is of particular interest since inhibition of KLK8 by common skin-based inhibitors (such as LEKTI fragments) is yet to be successfully achieved. Serpin inhibition of KLK5, 7, 8 and 11–14 has also been examined in vitro using a1-antitrypsin, a1-antichymotrypsin, kallistatin, antithrombin-III, protein C inhibitor, plasminogen activator inhibitor-1, a2-antiplasmin and C1 inhibitor (Luo and Jiang, 2006). Divalent ions

Although not strictly defined as protease inhibitors, several divalent ion species also show an ability to modulate KLK protease activity. Initially, studies were confined to the classical KLK cluster and it was demonstrated that prostateexpressed KLK2 and KLK3 are inhibited by zinc (Lovgren et al., 1999; Malm et al., 2000). KLK3 is also inhibited by copper, mercury, cobalt and cadmium ions in vitro, although the extent of inhibition is considerably weaker (Malm et al., 2000). More recently, zinc inhibition of KLK4 (Debela et al., 2006a), KLK5 (Michael et al., 2006; Debela et al., 2007a), KLK7 (Debela et al., 2007b), KLK8 (Kishi et al., 2006) and KLK14 (Borgono et al., 2007c) was demonstrated and corresponding crystallographic approaches suggest a potential molecular mechanism for inhibition, at least for certain KLKs. For both KLK5 and KLK7, metal ion binding is coordinated by exposed His residues (His96 or His99 for KLK5 and His99 for KLK7) (Debela et al., 2007a,b). The bound divalent ion subsequently interacts with the catalytic His57 residue, displacing it from the active site. KLK4 is subtly different in that the metal ion binding site is produced by His25 and Gln77 (Debela et al., 2006a). Naturally occurring inhibitors have evolved over time to function in a temporal and spatial manner that elegantly offsets their broad-range activity. However, since disease pathogenesis is highly complex and can involve partial or even multiple protease cascades, and since treatments are often administered systemically, therapeutic inhibition must be highly specific with low levels of off-target inhibition. This explains why natural inhibitors, although effective at regulating key physiological processes, very rarely have appreciable value as therapeutics. Therefore, the focus has shifted to engineered inhibitors that can deliver the require selectivity.

Inhibitor engineering Design challenges: potency and specificity

Protease inhibitors require high affinity if they are to be successful as therapeutic agents. The evolution of HIV-1 protease inhibitors revealed important design strategies when analysed from a thermodynamic viewpoint (Freire, 2006). The affinity of the inhibitor for the protease is determined by the Gibbs free energy of binding, with enthalpy and entropy changes corresponding to different types of atomic interactions (Freire, 2006). The change in enthalpy is proportional to the strength of binding between the inhibitor and the protease, such as hydrogen bonds, van der Waals interactions and salt bridges. However, in aqueous medium the entropy increases on binding because water molecules are freed from solvation layers around hydrophobic areas and thus become less ordered. Therefore, to achieve maximum affinity, hydrophobic repulsion from the aqueous medium must be combined with strong inhibitor-protease interactions achieving favourable entropy and enthalpy. The first-generation HIV-1 protease inhibitors (indinavir, nelfinavir and saquinavir) were characterised by favourable entropy but unfavourable enthalpy (Velazquez-Campoy et al., 2001), whereas second-generation inhibitors exhibited both favourable enthalpy and entropy with resulting higher affinity (Ohtaka and Freire, 2005). It thus appears that finding a balance between enthalpic and entropic changes on inhibitor-protease binding is vital for high-affinity inhibitors. The importance of inhibitor selectivity is underlined by the high profile failure in clinical trials of a series of MMP inhibitors. These were designed to block MMP-mediated remodelling of the cellular microenvironment and thus halt tumour growth and metastasis (Zucker et al., 2000). Unfortunately, the majority have been terminated following Phase III trials because of a lack of or even negative survival benefits. Critical evaluations of MMPI performance concluded that this was due, at least in part, to their broad-spectrum activity (Zucker et al., 2000; Coussens et al., 2002; Overall and Lopez-Otin, 2002; Turk, 2006). This resulted in blockade of important off-target cellular processes that were in fact anti-tumourigenic (Vazquez et al., 1999), as well as activation of pro-tumorigenic signalling pathways (Maquoi et al., 2002) or interference with unrelated functions with detrimental side effects, such as tendonitis-like musculoskeletal pain (Giavazzi et al., 1998). Selective inhibitors can be designed by exploiting unique structural features within the active site. These can be identified by screening high-affinity ligands against a panel of the most closely related proteases to establish selectivity, which, in the case of a KLK, should include all related tryptic or chymotryptic members of the family. Design challenges: mapping the KLK active site

The twin goals of specificity and potency described above are attainable provided the engineered inhibitor has a completely complementary fit with the active site of its target protease. Accordingly, irrespective of the inhibitor being

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designed, the first step is to probe the active site of the target enzyme. The most common strategies revolve around mapping the active site of the target protease through bacteriophage display, positional scanning and sparse matrix substrate libraries. Bacteriophage display (or biopanning) exploits the physical link between peptides on the exterior of the bacteriophage particle and the genetic material that carries the code for it. In its simplest form, phage display parallels natural evolution, with subpopulations of genetically diverse bacteriophage libraries iteratively selected and amplified by binding to an immobilised target; see Smith and Petrenko (1997) for a review. This technique has been spectacularly successful as a tool for sampling the chemical landscape of short peptides and monoclonal antibodies, resulting in a series of drugs currently available in the clinic, including Avastin, Rituxan and Lucentis (Dimitrov and Marks, 2009). An ingenious twist in the application of phage display has refocused this technique as a tool for discovering protease cleavage specificities. This strategy turns the affinity maturation concept on its head so that non-selected sequences are immobilised on a solid support and sequences are selected following cleavage from the solid support. This technique, which was pioneered by Matthews and Wells (1993) revolves around expression of the bacteriophage pIII protein as a fusion protein with an affinity tag, with the pIII portion of the fusion protein being separated from the affinity tag by a randomised sequence. The resulting bacteriophage library is then immobilised on an affinity matrix specific for the fusion partner on the modified pIII protein. Bacteriophages that have linker sequences that are substrates for a given protease will be cleaved off the solid support and can be harvested by filtration and subject to affinity maturation through iterative cycles of amplification, immobilisation and cleavage (Figure 3). To date, this technology has been applied to KLKB1 (Dennis et al., 1995), KLK2 (Cloutier et al., 2002), KLK3 (Coombs et al., 1998), KLK6 (Sharma et al., 2008) and KLK14 (Felber et al., 2006). These studies in turn guided the design of the engineered bioscaffolds discussed below. The strength of phage display lies in the magnitude and diversity of the libraries that can be screened. However, the screening technique itself is not without inherent bias and blind spots. In particular, pIII fusion peptides have the potential to modulate bacteriophage infectivity. In turn, this can lead to under- or over-representation of particular sequences during screening through their ability to propagate during reamplification rather than by virtue of their affinity for an immobilised ligand (Wilson and Finlay, 1998). Peptide sequences can also be strongly selected by the solid support used for immobilisation of the target protease. Immobilised metal affinity chromatography (IMAC) is notorious for its ability to select for pIII fusion proteins with multiple histidine residues. These issues are highlighted by studies by Cloutier et al. (2002) that identified peptide substrates for KLK2 using phage display. Although a number of substrates for the enzyme were identified, none of these achieved the catalytic efficiency of the control substrate (TFRSA), nor was this sequence selected. However, this may reflect the

Figure 3 Phage-display cycle. Genetic diversity is generated by ligating degenerate oligonucleotides into the genome of filamentous bacteriophage (typically M13) to produce fusion proteins with pIII, pV or pVII bacteriophage coat proteins. The resultant bacteriophage library is then allowed to interact with an immobilised bait molecule (BINDING) after which weakly bound bacteriophages are removed by washes of increasing stringency (WASH) prior to harvesting of more specifically bound bacteriophage particles by cycles of high- and low-pH washing (ELUTE). The resulting eluate is then reamplified in an E. coli bacteriophage propagation strain (AMPLIFY) and iteratively screened and amplified through a further three or four cycles to produce a final library through pseudo-evolutionary selection. Individual clones from this library are then sequenced and validated through interaction or inhibition assays.

fact that assays were based on peptide hydrolysis whereas selection was carried out on the basis of protein cleavage. Selection bias inherent in biological libraries is circumvented by the positional scanning synthetic combinatorial library (PS-SCL) approach, which uses solid-phase chemistry to generate diversity. It consists of sub-libraries of peptides for each binding subsite of the protease; thus, if the P1–P4 sites are to be investigated, four sub-libraries are needed. These contain 20 pools of peptides, each with a different fixed amino acid for that protease subsite (P1, P2, P3 or P4), whereas the other positions have a mixture of all amino acids (Dooley and Houghten, 1993). By screening the rate of proteolysis against all 80 pools, the individual contribution of each amino acid at each subsite to substrate recognition or inhibitor binding is revealed. Positional scanning has been used to probe the active site of a number of KLKs; the outcomes are summarised in Table 1. Although this information is invaluable, it is important when interpreting PS-SCL data to be conscious of the assumptions on which the method is based. First, it is assumed that the contributions of each position to biological activity are independent of each other. One argument against this is what can be termed P-site overlap: although the results from the screen indicate that the same residue is favoured in adjacent positions, when assayed as an individual peptide, this is not the case. Two PS-SCL studies of KLK4 ranked Gln favourably for the P2 and P3 positions (Matsumura et al., 2005; Debela et al., 2006b), whereas assays of individually synthesised peptides revealed that Gln is only favoured

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at these subsites if one but not both Gln are present (Swedberg et al., 2009). This suggests that the residue interacts with an area of the protease accessible from both subsites. Another misconception is that PS-SCL results can be universally applied to protein substrates. A PS-SCL study of KLK3 revealed a strong preference for Met at the P1 site (Table 1), although comparison with known cleavage sites for protein substrates indicates that Tyr and Gln are preferred (Merops database, http://merops.sanger.ac.uk/). An inspection of the S1 pocket of the KLK3 structure suggests that it is too narrow to fit Tyr or Gln, but not Met. Therefore, it may well be that binding of a larger protein substrate, which occurs over a considerably larger surface area, causes an induced fit and enables access to larger residues such as Tyr and Gln. A final inherent problem of the PS-SCL method is the assumption that all amino acid couplings occur with the same efficiency. Considering the popularity of the PS-SCL method, it is surprising that very few examinations of differential reaction rates in mixtures of amino acids have been made. Early solid-phase experiments noted differential reaction rates (Bayer and Hagenmaier, 1968; Ragnarsson et al., 1971, 1974; Sandberg and Ragnarsson, 1974) and compensation methods were later used to solve this problem (Kramer et al., 1993; Ostresh et al., 1994; Ivanetich and Santi, 1996). This issue has been highlighted by Boutin et al. (1997), who found ten-fold variations in concentration between different sequences and an absence of 35% of all theoretical sequences. These findings may explain why two PS-SCL (Matsumura et al., 2005; Debela et al., 2006b) screens did not detect the strong preference of KLK4 for Phe at P4 (Swedberg et al., 2009). To overcome these problems, positional preferences suggested by PS-SCL can be verified by screening against a sparse matrix library, a small sub-library of individually syn-

thesised and verified peptides (typically 50–200 members) selected from the PS-SCL (Swedberg et al., 2009). This strategy is complementary to the positional scanning approach, but circumvents the problems of subsite cooperativity and incomplete and under-represented sequences. In addition, since each peptide is individually assayed, there is often far greater selectivity apparent for each position in the peptide. Design challenges: bioavailability and stability

For protease inhibitors to be viable therapeutic agents, they must be not only potent and specific towards their target protease, but also readily bioavailable (Fear et al., 2007). The bioavailability of a drug in a particular tissue is governed by its ability to cross biological barriers to reach the site versus its rate of degradation and excretion. Orally bioavailable drugs in humans commonly fulfil Lipinski’s rule of five, which states that the compound should contain not more than five hydrogen bond donors or ten acceptors, an octanol-water partition coefficient of less than five and a molecular mass below 500 Da (Lipinski et al., 2001). Conversely, the potency of inhibition depends on the number and nature of contact points between the protease and inhibitor, whereas specificity relies on their uniqueness. Therefore, the design of potent, specific and bioavailable KLK inhibitors represents quite a challenge, especially considering the high level of conservation among the KLKs described earlier (Figure 1). Methods that both reduce enzymatic degradation and renal clearance of peptide and protein drugs include polysialylation and PEGylation, in which polysialic acid or poly (ethylene glycol) is attached to one or both termini of the peptide/protein. Polysialylation is a natural strategy to improve peptide and protein half-life (Jain et al., 2004) and was recently used to increase the in vivo availability of an antitumour monoclonal antibody (H17E2 Fab fragment) by

Table 1 Extended substrate specificity of KLK1–15 and KLKB1.

KLKB1 KLK1 KLK2 KLK3 KLK4 KLK5 KLK6 KLK7 KLK8 KLK9 KLK10 KLK11 KLK12 KLK13 KLK14 KLK15

P1

P2

P3

P4

Method

Reference

R F/K/Y R M)n)A R)K R R)A/n/M Y)A/M/n R/K n/a R)K/n/M M)n)K/R)A K)R R)N R R

n/a L/F H/L/R L)A/M/Q)n Q)T/L)V)P S)A/N/T)P R)K Y)L)T/F/n n/a n/a D)E/R)K/M R)K/D)E)S n/a N)L)F)Y/A N/A)P)H/S n/a

n/a n/a n/a Y)V)M/n/I V)Q)T)S/A M)Y)K/F/n A)K/S/Y/M T/M)H/A/V n/a n/a E/D)S/Y/M D/E/M)Y)S n/a R K/A)R/S/n n/a

n/a n/a n/a V)M/A/Q)T F)I)V)Y/W G)Y)V/P/W V)Y/I/M/G K/Q/M/V n/a n/a M)D/E/V/n M)D/E/V/M n/a V)Y)I/P/G Y)W)F/V/I n/a

PDL PDL Peptides PS-SCL SML PS-SCL PS-SCL PS-SCL Peptides n/a PS-SCL PS-SCL Peptides PS-SCL PS-SCL Peptide

Dennis et al., 1995 Li et al., 2008 Janssen et al., 2004 Debela et al., 2006b Swedberg et al., 2009 Debela et al., 2006b Debela et al., 2006b Debela et al., 2006b Rajapakse et al., 2005 n/a Debela et al., 2006b Debela et al., 2006b Memari et al., 2007 Borgono et al., 2007a Borgono et al., 2007a Takayama et al., 2001a

Amino acids are shown in one-letter code, with ‘n’ representing norleucine. Bold font indicates the most preferred residue at each subsite. When several sources of data were available, selections were made according to the following priority order: Sparse Matrix Library (SML), Positional Scanning Synthetic Combinatorial Library (PS-SCL), Phage Display Library (PDL) and peptides. n/a, not applicable.

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a factor of five (Constantinou et al., 2008). PEGylation is approved by the FDA as a vehicle for pharmaceuticals (Harris and Chess, 2003) and is used in a number of proteinbased drugs currently on the market (Veronese and Harris, 2008) with an annual market value of over $US4 billion (Krishan, 2007). Peptide-based inhibitors particularly suffer from short half-lives since they are often hydrophilic and thus show poor oral absorption and are rapidly cleared by the kidneys (Werle and Bernkop-Schnurch, 2006). In addition, peptide drugs are often quickly degraded by the numerous exo- and endo-proteases present in most tissues (Werle and BernkopSchnurch, 2006). Even if intravenously administered, most peptides are cleared from the bloodstream within minutes. To overcome these particular challenges, peptide lead compounds often need to be modified in various ways, depending on the route of administration and the target tissue. N- and C-terminal modifications such as N-acetylation and C-amidation can reduce degradation by exoproteases (McGregor, 2008). For example, the natural peptide thymopoietin involved in T-cell maturation has a half-life of 1 min in plasma, whereas a double end-capped version shows no detectable degradation (Heavner et al., 1986). Similarly, capping with fatty acids can improve both the half-life and lipophilicity of a peptide, a technique used to improve serum stability of an anti-proliferative somatostatin analogue (Dasgupta et al., 2002). Backbone- and/or disulfide bond-circularised peptides are intrinsically stable to degradation, a common feature in naturally occurring peptides. A diverse range of plants produce cyclotides, circular miniproteins with a cysteine knot of three intertwined disulfides, believed to be involved in host defence (Craik et al., 2002; Gruber et al., 2008). Many bacteria also produce circular peptides (bacteriocins) to target competing species (Mercedes et al., 2008), as do many marine microorganisms (Hamada and Shioiri, 2005). This approach was recently used by Clark et al. (2005) to produce a backbone-cyclised snail venom peptide (a-conotoxin) analogue with improved stability in serum. A more significant challenge is to improve peptide resistance to endoprotease activity, since this involves peptide backbone and/or side chain modifications that are likely to have major effects on inhibitor potency and specificity. One strategy involves the substitution of certain amino acids that are known to be targets of proteolysis with non-natural Damino acids, as has been used to produce a variety of protease-resistant reagents including small peptides (Silvia et al., 2008) and antibodies (Webb et al., 2005). Alternatively, substitution of peptide backbone atoms, in particular participants of the amide bond, can be used to produce what are commonly referred to as pseudopeptides. For example, the amide nitrogens of scissile bonds can be methylated (N-methylation) to prevent hydrolysis, as for the fungal peptide immunosuppressant cyclosporine A. This peptide has seven N-methylations, as well as one D-amino acid, and is highly bioavailable since it is chiefly degraded by the hepatic cytochrome P450 3A enzyme system rather than by proteases (Dunn et al., 2001). Recent advances in methods for

synthesis of multi N-methylated peptides (Biron et al., 2006) have yielded a somatostatin analogue with four-fold higher half-life after oral administration (Biron et al., 2008). A number of less commonly used amide bond surrogates also exist, including retro bonds (NH-CO), carba bonds (CH2CH2), aza bonds (CO-NH-NR-CO), reduced amide (CH2NH) and urea bonds (HN-CO-NH). These have previously been reviewed elsewhere (Adessi and Soto, 2002; Lozano et al., 2006). Curiously, certain naturally occurring small protein inhibitors that deviate from Lipinski’s rule of five are readily bioavailable. For example, orally administrated Bowman-Birk inhibitors (;8 kDa) are readily bioavailable (Kennedy, 1998) and the same is true for cyclotides (;3 kDa), at least in insects (Whetstone and Hammock, 2007). There is a growing realisation that many of the issues above can be solved at a stroke by using naturally occurring inhibitors of serine proteases. For example, the inhibitors aprotinin (Terrell et al., 1996) and hirudin (Zeymer, 1998) have seen clinical use as modulators of bleeding after thoracic surgery and thrombolysis, respectively. The obvious next step for these naturally occurring inhibitors is to produce variants with redirected inhibitory specificity and enhanced potency. Use of these bioscaffolds is becoming increasingly common as their advantages in terms of stability, specificity and potency are recognised.

Engineered inhibitors: bioscaffolding Bioscaffolding revolves around the use of natural template structures (bioscaffolds) in contrast to more conventional small-molecule approaches. Extensive use is made of preexisting natural protease inhibitors, which are re-engineered using recombinant DNA techniques or solid-phase peptide synthesis. The chief features of successful bioscaffolds are a structure that is both robust and flexible enough to tolerate multiple amino acid substitutions, and a template structure that has intrinsic protease inhibitor activity. Thus, the engineering goal is simply to redirect and enhance existing inhibitory activity. Further advantages come from facile production of inhibitor molecules in living systems, thus facilitating biopanning (phage display) and cheap and efficient large-scale bioproduction in microbial or plant systems. Currently there are four classes of bioscaffold with relevance to kallikreins: serpins, Kunitz-domain inhibitors, ecotin and SFTI derivatives. All four classes of inhibitor interact with their target proteases through the canonical loop described above (Tyndall et al., 2005; Figure 2E), forming an extension of the protease b-sheet structure. However, the scaffolding presenting the reactive loop shows considerable structural diversity and plays varying roles in stabilising the protease-inhibitor complex. In addition to these four established bioscaffolds, there is also a move towards production of specific monoclonal antibodies that can inhibit kallikreins, with Dyax developing a specific KLK1 inhibitor for treatment of asthma (Sexton et al., 2009). This antibody was selected from a so-called Fab-on-phage library (Steukers et al., 2006), which contains genes encoding the antibody

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heavy- and light-chain variable regions that are then displayed on the phage surface as Fabs and selected using surface plasmon resonance screening. Other non-clinical examples include antibody-mediated inhibition of KLK13 in a cell-based model of extracellular matrix degradation (Kapadia et al., 2004) and use in biochemical characterisation of KLK12 (Memari et al., 2007). Both the bioscaffold and monoclonal antibody approaches make extensive use of phage display as a primary design tool. However, bioscaffold design is also driven by information from positional scanning and sparse matrix libraries, as outlined below. Serpins

To date, three serpins have been exploited as bioscaffolds; C1-inhibitor protein, which inhibits the complement system (Kase and Pospisil, 1983); human a1-antitrypsin (AAT), which protects lung tissue from the effects of human neutrophil elastase (Sun and Yang, 2004); and human a1-antichymotrypsin (ACT), which is associated with the development of Alzheimer’s disease (Potter et al., 2001). All three inhibitors are high-molecular-weight ()50 kDa) plasma proteins that contact their target proteases via a canonical loop, which is termed a reactive loop since it is cut by the target protease. Although the reactive loop does in theory control the majority of the specificity of a given serpin, there is also a significant contribution from serpin exosites such that swapping reactive loops alone between serpin subtypes is not sufficient to completely redirect their inhibitory activity (Djie et al., 1997). Nonetheless, the reactive loop is very tolerant of substitution and this has led to the development of a series of recombinant kallikrein inhibitors. Initially, an inhibitor for KLKB1 was developed using a variant of C1-inhibitor (Sulikowski et al., 2002). C1-inhibitor effectively blocks KLKB1 activity and the aim of the reengineering was to increase the inhibition specificity and prevent the blockade of other complement proteases. Accordingly, a reactive loop variant was designed on the basis of the plasma KLK substrate specificity, which was previously assessed using a relatively small pool of arginine methyl esters (Levison and Tomalin, 1982). The resulting variant showed the specificity required and maintained potency, with ka of 382 180 M-1 s-1. Following this success, a KLK2 inhibitor was designed using ACT as bioscaffold (Cloutier et al., 2004). The ACT reactive loop was substituted with a KLK2specific sequence found through phage display (Cloutier et al., 2002), yielding an inhibitor with a ka value of 6261 M-1 s-1. More recently, Felber et al. (2006) re-engineered the reactive loop of both AAT and ACT serpins using pentapeptides derived from a phage display scan against immobilised KLK14 (Felber et al., 2005). Currently, KLK2 ACT-derived inhibitors are being developed by Med Discovery, with the lead compound, MDKP67b, close to entering clinical trials as a targeted treatment for prostate cancer. The success of this approach owes much to the adaptability of the serpin reactive loop. In addition, using a human serpin as a bioscaffold, the problem of patient immune response to a protein therapeutic is neatly avoided.

Kunitz domain

Originally identified in BPTI, the Kunitz-domain inhibitory motif is remarkably compact and shows considerable thermal stability (Moses and Hinz, 1983; Makhatadze et al., 1993). Both BPTI and the Alzheimer’s amyloid b-protein precursor (APPI), which has a similar structure to BPTI, have been exploited as bioscaffolds. APPI was the first bioscaffold subjected to phage display. Screening against KLKB1 achieved a Ki value of 15 pM (Dennis et al., 1995). A later study searched for potent inhibitors of six distinct serine proteases, including KLKB1. This study focused on the BPTI canonical loop, substituting positions P1, P3 and P4 with amino-acid side chains gauged to explore the diversity of charge, shape and hydrophobicity. The best inhibitor against KLKB1 showed a ki value of 5.4 nM, a modest 2.2-fold improvement over the wild-type inhibitor; considerable thermal destabilisation was observed when P4 mutations were undertaken (Grzesiak et al., 2000b). The Kunitz-domain approach has also had some success in the world of commercial drug design and development, with a Dyax product, ecallantide (DX-88), reaching Phase III clinical trials for treatment of hereditary angioedema. Ecallantide was derived from a phage display screen of the Kunitz domain of human lipoprotein-associated coagulation inhibitor (LACI) using immobilised KLKB1 as bait. It has a reported Ki value of 44 pM and is highly specific for KLKB1 (Williams and Baird, 2003). At the time of writing, FDA approval for use of ecallantide was awaiting completion of a risk evaluation and mitigation strategy. Ecotin

Ecotin (E. coli trypsin inhibitor) was isolated from the periplasmic space of E. coli and is a dimeric, bidentate protease inhibitor (Chung et al., 1983). It is thought to provide protection against the effects of neutrophil elastase (Eggers et al., 2004), which it inhibits with a Ki value of 12 pM. Interaction between the protease and ecotin is driven by four loops (two from each ecotin monomer) and results in the formation of a heterotetramer with a very extensive buried ˚ 2. Interestingly, binding by the contact surface area of 2850 A loops is not restricted to the trypsin active site, but also includes residues that are highly divergent within the trypsin superfamily. Accordingly, these secondary contacts have the potential to provide greater selectivity than that of inhibitors that bind at the active site alone. This prompted Craik and co-workers (Stoop and Craik, 2003) to re-engineer the ecotin bioscaffold to produce a series of variant molecules that can inhibit KLKB1, thrombin, MT-SP1 and FXIIa. Two distinct design strategies were used, a simple progressive substitution of the ecotin apparent P1 residue and biopanning using phage display. Ecotin, like the C1-inhbitor bioscaffold, is a potent inhibitor of KLKB1 but lacks selectivity against other contact activation proteases. Given the role of the contact loops, as well as the canonical loop, in protease complex formation, a library of ecotin variants was produced by gene shuffling to target all five motifs. This library was screened against immobilised KLKB1 as described above and, in a novel

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deviation from the normal phage display procedure, the library was pre-blocked with soluble proteases from classes against which inhibitory activity was to be selected. This led to the isolation of an ecotin variant with a Ki value for KLKB1 of 11 pM but with activity against factor Xa, factor XIa, urokinase-type plasminogen activator thrombin, and membrane-type serine protease 1 that is four to seven orders of magnitude lower (Stoop and Craik, 2003). Sunflower trypsin inhibitor

SFTI belongs to the Bowman-Birk serine protease inhibitor family and is a potent inhibitor of trypsin, cathepsin G and suppressor of tumourigenesis (14 ST14/matriptase/MT-SP1). It was originally discovered in sunflower (Helianthus annuus) seeds and characterised by determination of its three-dimensional structure in complex with bovine b-trypsin (Luckett et al., 1999). Consisting of just 14 cyclised amino acids bisected by a disulfide bond, SFTI is intermediate between the macromolecular scaffolds represented by the bioscaffolds above and the small-molecule inhibitors described below. Its smaller size allows for facile chemical synthesis (Zablotna et al., 2002; Korsinczky et al., 2005) and rapid generation of variants. In addition, a very recent publication described expression of a library of fully cyclic SFTI variants in E. coli (Austin et al., 2009), opening up the possibility of rapid in vivo screening. Similar to the other bioscaffolds described above, SFTI interacts with its target proteases via a canonical-type loop. However, unlike the larger molecules, SFTI has essentially no molecular scaffolding behind it, relying on its fully cyclic backbone and a disulfide bond for stability. Interestingly, the structure of SFTI is maintained even when the disulfide is removed (by substituting glycine or aminobutyric acid), being preserved by an internal hydrogen bond network (Korsinczky et al., 2005). However, this variant is not stable to cleavage by proteases. Surprisingly, there have been few attempts to use the SFTI molecule as a bioscaffold and the small number of variants produced have not been tested in cell culture or animal systems. To date, only KLK4 has been actively targeted; Swedberg et al. (2009) used a sparse matrix library approach to probe the KLK4 active site, and then substituted the optimal sequence obtained into the SFTI bioscaffold. This strategy improved both the potency and specificity of KLK4 inhibition by SFTI, increasing its potency by nearly two orders of magnitude to give a Ki value of 3.6 nM. Moreover, the specificity of inhibition improved to give 500-fold selectivity against the closely related KLK14. Thus, in contrast to the situation for serpins described above, re-engineering of just three residues is sufficient to completely redirect the inhibitory activity of SFTI. This reflects the lack of interactions with regions outside the active-site cleft in the SFTI/protease complex. Despite the inhibitory potency of these bioscaffolds, only ecallantide has successfully made the transition to clinical use. This may reflect the fact that ecotin, Kunitz-domain and serpin-based inhibitors are all macromolecular inhibitors requiring intravenous administration. Although the much smaller SFTI may yet prove to be readily bioavailable, detailed

Figure 4 Tetrahedral transition-state analogues of serine proteases. (A) Structure of the P1-P19 residues and adjoining peptide bond on a typical amide substrate (left) and putative tetrahedral intermediate formed coordinately with the Ser195 (catalytic) side chain prior to cleavage of the peptide bond (right). (B) Representation of a boronic acid inhibitor (e.g., P8720, Figure 2B) (left) and subsequent complex formation via covalent bond formation with the Ser195 (catalytic) hydroxyl group (right). (C) Structure of a peptide aldehyde inhibitor (e.g., hK2p01, Figure 2B) (left) and covalent bond formation with the Ser195 (catalytic) hydroxyl group (right). (D) Representation of a chloromethyl ketone inhibitor (e.g., CH-2856, Figure 2B) (left) and mechanism of inhibition via dual linkage to the target protease at Ser195 (catalytic) as well as the adjacent His57 (catalytic) by the exposed CH2-Cl group (right).

pharmacokinetics are currently unavailable for either wildtype or engineered versions of this scaffold. In addition, the other bioscaffold-based inhibitors show considerable crossreactivity between the kallikreins. Clearly there is considerable scope for further investigation focused on these remarkable reagents, which have the potential to become as successful as the small-molecule approaches conventionally applied to protease inhibitor design.

Engineered inhibitors: small-molecule inhibitors The most commonly used small-molecule kallikrein inhibitors are serine protease-specific tetrahedral transition-state analogues. These include peptides in which the C-terminal carboxyl acid is substituted for boronic acid, an aldehyde or halogenated methyl ketones to form a tetrahedral adduct with Ser 195 (Figure 4). For example, Fareed et al. (1981) used KLK2 and KLKB1 kininogen cleavage sites to design peptide aldehyde inhibitors with Ki values of 10–20 mM, although these inhibitors showed little specificity against a number of serine proteases of the blood clotting cascade. A boronic acid inhibitor based on a similar peptide sequence produced a potent (Ki 150 pM) and more specific KLKB1

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inhibitor (Dela Cadena et al., 1995). Concurrently, Evans et al. (1996a,b) reported conservative non-natural amino acid substitutions of KLKB1 kininogen cleavage sites combined with a fluoroalkyloxymethyl ketone functionality to develop a series of specific KLK1 inhibitors with Ki values in the lower nM range. These inhibitors attenuated breast cancer cell invasion in a Matrigel-based model (Wolf et al., 2001). More recently, the boronic acid approach was used to develop inhibitors to PSA; the best has a Ki value of 65 nM (LeBeau et al., 2008). However, there are limited specificity data available for these compounds and their biological impact is ambiguous. Using a different strategy, Wanaka et al. (1990) capped phenylalanine N-terminally with benzylamine to yield a competitive KLKB1 inhibitor (Ki 810 nM). This strategy, previously used to produce trypsin, plasmin and thrombin inhibitors (Markwardt et al., 1968), capitalises on mimicking the P1 arginine by the benzylamine group; the ‘peptide bond’ is displaced, resulting in a non-hydrolysable compound. Various derivatives of this compound were later screened to produce a more potent KLKB1 inhibitor with a Ki value of 130 nM (Teno et al., 1993), although it suffers from the same lack of specificity as previous benzylamine derivatives (Markwardt et al., 1968). b-Lactam analogues have also been used to produce a number of serine protease inhibitors (Konaklieva, 2002), including a series of KLK3 inhibitors with inhibition in the nM range, although the specificity of this inhibition was not evaluated (Adlington et al., 1997, 2001). Recently, phage display has been used to identify a series of KLK2 peptide inhibitors with inhibition constants in the lower micromolar range and selectivity over a number of tryptic serine proteases, including KLKB1 (Hekim et al., 2006). The stability of these peptides was later improved by head-to-tail cyclisation and/or internal disulfide bond formation, without loss of potency (Pakkala et al., 2007). The same group also produced three non-peptide KLK3 inhibitors with inhibition in the nanomolar range by screening against a library of small drug-like molecules (Koistinen et al., 2008b). The development of these inhibitory peptides has recently been reviewed (Koistinen et al., 2008a). Small-molecule kallikrein inhibitors have not had the same clinical success as bioscaffold-based inhibitors. However, transition-state analogues are currently being investigated for use as activity-based probes, utilising the platform initially established for organophosphate peptide inhibitors (Liu et al., 1999), which were developed to detect KLK6 (Oikonomopoulou et al., 2008). Clearly, the bioscaffold approach and conventional small-molecule design techniques are complementary.

Conclusions There is increasing appreciation of the potential roles played by the kallikrein proteases as regulators of human physiology, as biomarkers in disease diagnosis and as points for

therapeutic intervention. With application of the strategies we have discussed here, the next decade could see a blossoming of research in this area and the production of a new generation of protease inhibitor drugs to rival the antiviral protease inhibitors.

Acknowledgements Work in the corresponding author’s laboratory is supported by the Cancer Council Queensland (Grant 44323) and the Prostate Cancer Foundation of Australia (Grant PR09). SJD receives funding from the Smart Futures Fund (Queensland Government, Australia).

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Received October 16, 2009; accepted January 5, 2010

CHAPTER 2

2.2

Natural and Engineered Plasmin Inhibitors: Applications and Design Strategies.

53

54

Natural and Engineered Plasmin Inhibitors: Applications and Design Strategies.

Joakim E. Swedberg and Jonathan M. Harris* Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland 4059, Australia *Corresponding author: [email protected]

Abstract The serine protease plasmin is ubiquitously expressed throughout the human body in the form of the zymogen plasminogen. Conversion to active plasmin occurs through enzymatic cleavage by plasminogen activators. The plasminogen activator/plasmin system has a well established function in the removal of intravascular fibrin deposition through fibrinolysis and inhibition of plasmin activity, which have found widespread clinical use to reduce perioperative bleeding. Increasing evidence also suggests diverse while currently less defined rolls for plasmin in a number of physiological and pathological processes relating to extracellular matrix degradation, cell migration and tissue remodelling. In particular, dysregulation of plasmin has been linked to cancer invasion/metastasis and various chronic inflammatory conditions prompting efforts to develop inhibitors of this protease. Although a number of plasmin inhibitors exist, these commonly suffer from poor potency and/or specificity of inhibition that results in either reduced efficacy or prevention of clinical use. Consequently, there is a need for further development of high affinity plasmin inhibitors that maintain selectivity over other serine proteases. This review summarises clearly defined and potential applications for plasmin inhibition. Properties of naturally occurring and engineered plasmin inhibitors are discussed in 55

the context of current knowledge regarding plasmin structure, specificity and function. This includes design strategies to obtain potency and specificity of inhibition in addition to the controlled temporal and spatial distribution tailored for the intended use.

Keywords: Plasmin; Fibrinolysis; Inhibitor; Drug design; Aprotinin; Substrate specificity

Introduction Plasmin is the primary enzyme responsible for dissolution of fibrin in the circulatory system. Plasminogen, the zymogen of plasmin is expressed ubiquitously in the human body (Zhang et al. 2002), with the predominant source being the liver (Bohmfalk and Fuller 1980; Saito et al. 1980). Plasminogen is produced as an 810 amino acid protein with a 19 amino acid leader peptide, which is cleaved during secretion to produce the mature 791 amino acid one-chain zymogen. This is converted to plasmin by cleavage of the Arg561 - Val562 scissile bond (Robbins et al. 1967), resulting in an active protease consisting of two disulfide linked chains. The aminoterminal heavy chain (residues Glu1-Arg561) is comprised of a plasminogen/apple/nematode (PAN) domain (Tordai et al. 1999) and five kringle domains of approximately equal sise (Claeys et al. 1976) while the light chain (residues Val562-Asn791) contains a serine protease domain homologous to trypsin with a catalytic triad comprising His603, Asp646 and Ser741 (Wiman 1977). Both plasmin and plasminogen occur in two forms, full length and a Lys77-Lys78 activated variant produced through self catalysis (Figure 1). The former exists in a tight conformation through binding of Lys50 and/or Lys62 to kringle domain 5 (Cockell et al. 1998; Zoller et al. 1998) while Lys78-plasminogen assumes a more relaxed conformation rendering it more susceptible to plasmin conversion (Marshall et al. 1994; Castellino and Ploplis 2005).

56

Figure

1:

Schematic

domain

structure of plasminogen. The Nterminal

plasminogen

/apple/nematode (PAN) five kringle (KR) domains and the C-terminal serine

protease

domain.

Numbering starts from Glu1 of the mature protein according to NCBI protein (accession

sequence number:

data

base

AAA36451).

The Lys77-Lys78 and plasminogen to plasmin

cleavage

sites

are

highlighted with arrows.

The plasminogen activation system (PAS) Production of active plasmin primarily occurs through two physiological plasminogen activators, urokinase-type plasminogen activator (uPA) (Robbins et al. 1967) and tissue-type plasminogen activator (tPA) (Hoylaerts et al. 1982). uPA is released from endothelial cells as an inactive single-chain zymogen uPA (sc-uPA) which can be converted to the active two-chain uPA (tc-uPA) by plasmin (Skriver et al. 1982; Petersen et al. 1988). tPA is also released as a single-chain zymogen tPA (sc-tPA) before activation by plasmin and contact factors (prekallikrein, kininogen, factor XIIa) into two-chain tPA (tc-tPA) (Hoffman 2005). Both plasminogen activators are regulated by plasminogen activator inhibitors (PAIs), with PAI type1 being most the prominent (Schneiderman and Loskutoff 1991; Carmeliet et al. 1995). tPA is considered the primary intravascular plasminogen activator while uPA is believed to be main activator in extravascular compartments, although some cross activation occurs. For example, tPA-deficient mice only show a low level of fibrin deposition (Bugge et al. 1996) while tPA and

57

uPA double deficient mice suffer from generalised thrombosis, inflammation and a shortened life span (Carmeliet et al. 1994). Fibrin formation and blood coagulation is regulated by proteolytic cascades involving numerous serine proteases, cell surface receptors and inhibitors and has been reviewed previously (Booth and Bennett 1994; Walsh and Ahmad 2002; Moran and Viele 2005; Platt 2007). Briefly, coagulation may be initiated through tissue damage and exposure of tissue factor (extrinsic pathway) or at the negatively charged surface of platelets (intrinsic pathway). Both pathways involve the serial activation of serine protease zymogens, amplification and convergence, ultimately resulting in the conversion of pro-thrombin to active thrombin at the surface of platelets. Thrombin subsequently processes fibrinogen into monomers which are cross-linked by factor XIIIa to form the insoluble fibrin meshwork that constitute the matrix of blood clots (Figure 2) (Hantgan et al. 2001). Dissolution of fibrin by tPA activation of plasmin only occurs at an appreciable rate when both proteases are bound to fibrin through lysine binding sites on their kringle domains (Lerch et al. 1980). In particular, plasminogen and tPA bind to C-terminal lysine residues of partially degraded fibrin, greatly increasing the rate of plasmin generation (Hoylaerts et al. 1982; Christensen 1985; Fleury and Angles-Cano 1991; Sakharov and Rijken 1995). In a positive feedback loop, plasmin cleaves fibrin exposing more Cterminal lysine residues and thus promoting its own formation (Figure 2). This process is counter balanced by the activity of the carboxypetidase thrombin activatable fibrinolysis inhibitor (TAFIa) (Bajzar et al. 1995) which removes the plasminogen and tPA binding lysine residues (Redlitz et al. 1995; Wang et al. 1998) to prevent clot dissolution during clot formation (Bouma and Mosnier 2003). As a result, intravascular plasmin activity is largely confined to the surface of the fibrin clot rather than circulating in plasma (Lucas et al. 1983). Additionally, any unbound plasmin has a considerably shorter half life (Wiman and Collen 1978) and is rapidly

58

Figure 2: Fibrin clot formation and fibrinolysis. During clot formation thrombin activates TAFI and processes fibrinogen into monomers that are cross-linked by factor XIIIa into insoluble fibrin. In addition, thrombin converts TAFI to TAFIa which removes fibrin kringle domain binding lysine (K) residues, preventing fibrinolysis during coagulation. Upon initiation of fibrinolysis, plasminogen and two-chain tPA (tc-tPA) bind via their kringle domains to lysine residues of fibrin, greatly accelerating plasminogen activation. Plasmin degrades fibrin exposing lysine binding sites and converts single-chain tPA (sc-tPA) into tc-tPA, resulting in a positive feedback loop with amplification of fibrinolysis. Any unbound plasmin is rapidly inactivated by the potent plasmin inhibitor α-antiplasmin (α-AP).

inactivated by the potent plasmin inhibitor α-antiplasmin, present at high concentrations in the blood (Collen 1976; Aoki et al. 1978). Plasmin activation by uPA is a cell surface receptor meditated process (Figure 3) associated with extracellular matrix (ECM) remodelling, cell migration, repair, macrophage function, ovulation and embryo implantation (Blasi 1993; Blasi and Carmeliet 2002; Brownstein et al. 2004). uPA binds to the urokinase receptor (uPAR) through its epidermal growth factor-like amino terminal domain while plasminogen binds via a heterogeneous population of cell surface proteins with low affinity (Plow et al. 1995; Ulisse et

59

Figure 3: Plasminogen activation by uPA at the cell surface. Two-chain uPA (tc-uPA) bound to the urokinase protease activated receptor (uPAR) converts plasminogen bound to a plasminogen receptor (Plg R) into plasmin. Plasmin in turn converts single chain uPA into tc-uPA amplifying its own activation. Any plasmin not bound to a Plg R is rapidly inactivated by the potent plasmin inhibitor α-antiplasmin (αAP). uPA bound to both plasminogen activating inhibitor (PAI) and uPAR result in endocytosis of the complex, a process mediated by members of the low-density lipoprotein receptor (LDLR) family. Post endocytosis, uPAR is recycled to a new location of the cell membrane and thereby regulating the direction of uPA and plasmin activity

al. 2009) to all cell types excluding erythrocytes (Plow and Miles 1990). No single receptor is thought to account for the high plasminogen binding capacity of any one cell type and this may reflect the diversity of plasmin functions (Miles et al. 2005). Co-localization of receptor bound uPA and plasminogen is needed for the formation of plasmin at an appreciable rate (Vassalli et al. 1985; Appella et al. 1987). uPA bound to PAI-1 also binds uPAR resulting in endocytosis of the complex (Nykjaer et al. 1997), a process mediated by members of the low-density lipoprotein receptor (LDLR) family (Gliemann 1998; Rodenburg et al. 1998). Following this, the

60

uPA/PAI-1 complex is degraded while uPAR is recycled and relocated to another site at the cell surface, directing PAS driven ECM degradation and cell migration (Moonen et al. 1982; Knox et al. 1987; Tarui et al. 2002; Majumdar et al. 2004). Recently, a high affinity plasminogen receptor was identified in monocytes, plasminogen receptor with C-terminal lysine (Plg-RKT) (Andronicos et al. 2010). Plg-RKT colocalises with uPAR at the cell surface and dramatically accelerates plasminogen activation (Andronicos et al. 2010). Although not confirmed at the protein level, the mRNA of the receptor is widely expressed in a number of other migratory cell types including leukemic, neuronal and breast cancer cells as well as leukocytes (Andronicos et al. 2010). The importance of this high affinity plasminogen receptor and its different function(s) compared to other low affinity counterparts has yet to be established (Strickland 2010).

Rationale for plasmin inhibition to regulate fibrinolysis Generally, non-surgical clinical conditions relating to poor fibrin formation during clotting are due to an absence or low levels of a component of the clotting cascade (Goodnough and Shander 2007). Current treatments focus on replacement therapy of these proteins rather than on the inhibition of fibrin degradation by plasmin (Platt 2007). Nevertheless inhibition of plasmin has found widespread use to reduce perioperative bleeding and to minimise the need of transfusions during surgery (Beierlein et al. 2005), particlarly during organ transplantation (Patrassi et al. 1994; Kesten et al. 1995), orthopaedic (Capdevila et al. 1998) and cardiac surgery (Royston et al. 1987). Excessive bleeding requires blood transfusion which is associated with a risk of allergic reactions, mismatched transfusion and transmission of infections (Blajchman and Vamvakas 2006). However, the most widely used plasmin inhibitor to reduce perioperative bleeding, aprotinin (Trasylol®), was discontinued from general use in November

61

2007 after a large multicenter study from the Blood Conservation using Antifibrinolytics in a Randomised Trial (BART) found higher mortality rates associated with this drug compared to alternative treatments during high risk cardiac surgery (Fergusson et al. 2008). Aprotinin is a Kunitz-type inhibitor originally isolated from bovine lung tissue (Kunitz and Northrop 1936) that inhibits virtually all serine proteases (Ascenzi et al. 2003), and was, prior to its withdrawal, the most effective antifibrinolytic agent. Clinical use of aprotinin has been linked to increased incidence of myocardial infarction (Bukhari et al. 1995; Mangano et al. 2006), vein graft hypercoagulation (Cosgrove et al. 1992), renal failure (Karkouti et al. 2006; Mangano et al. 2006; Mangano et al. 2007; Shaw et al. 2008) and mortality (Mangano et al. 2007; Fergusson et al. 2008; Olenchock et al. 2008; Schneeweiss et al. 2008; Shaw et al. 2008) as well as anaphylactic shock upon reuse of the drug (Wuthrich et al. 1992; Cohen et al. 1999; Beierlein et al. 2005). However, numerous other studies have found no significant increase in morbidity and mortality rates and the detrimental effects of aprotinin use remains a controversial topic (Van der Linden et al. 2007; Hausenloy et al. 2008; Lindvall et al. 2008; Pagano et al. 2008). Nonetheless, considering all the findings as a whole, some harmful effects on renal function are evident (Dietrich 2009) and aprotinin is not likely to make its way back in to the clinic in the near future. Currently, another group of fibrinolysis inhibitors commonly referred to as lysine analogues are clinically available, including ε-aminocaprioic acid (EACA) (Okamoto et al. 1959) and tranexamic acid (TXA) (Okamoto et al. 1964). This class of compounds bind to the lysine binding sites of kringle 1 and 4 (Lerch and Rickli 1980; Lerch et al. 1980) preventing plasminogen binding to fibrin (Lucas et al. 1983) and efficient activation by the plasminogen activators (Lucas et al. 1983). Previously considered to have unproven efficacy in reducing bleeding during surgery (Royston 1998), recent investigations and meta-analyses of clinical

62

trials demonstrate the effectiveness of these compounds in reducing the need for blood products. However, the reported level of efficacy for these lysine derivatives is variable (Henry et al. 2001; Carless et al. 2005; Brown et al. 2007; Mannucci and Levi 2007; Fergusson et al. 2008; Henry et al. 2009; Kagoma et al. 2009; Koster and Schirmer 2010). Additionally, the efficacy of the lysine analogues in reducing bleeding and potential risks associated with their use have not been studied to the same degree as aprotinin (Mannucci et al. 2007). Furthermore, this class of compounds are commonly given at a much higher dose (1-20 g) than aprotinin (half Hammersmith dose, 420 mg - full Hammersmith dose, 840 mg) (Royston 1998; Koster et al. 2010) and the consequences of this practice have not been evaluated against alternative established agents (Koster et al. 2010). In contrast to the lysine analogues, aprotinin has been associated with some desirable secondary characteristics relating to the inhibition of serine proteases other than plasmin. In particular, aprotinin inhibits a number of procoagulant proteases as well as proteases involved in inflammation and therefore exerts both anticoagulant and anti-inflammatory properties (Hill et al. 1997; Asimakopoulos et al. 2000; Landis et al. 2001; Ascenzi et al. 2003; Poston et al. 2006; McEvoy et al. 2007; Sperzel and Huetter 2007). This is of particular importance during cardiac surgery involving cardiopulmonary bypass procedures. Contact with the artificial surfaces of the heart-lung machine activates both coagulation and systemic inflammatory responses (Butler et al. 1993; de Mendonca-Filho et al. 2006; Ferraris et al. 2007). These complications may be reduced by aprotinin (Asimakopoulos et al. 2000; Landis et al. 2001; Poston et al. 2006; Royston et al. 2006) but not lysine analogues (Hill et al. 1997; Sperzel et al. 2007). Still, the precise mechanisms behind the anticoagulant and anti-inflammatory properties of aprotinin are not fully understood (McEvoy et al. 2007; Ide et al. 2009; Vande Vusse et al. 2010) and need to be fully elucidated to enable the development of replacement therapies.

63

Rationale for plasmin inhibition to regulate cell migration/tissue remodelling In addition to the well established role of plasmin in fibrinolysis, binding and activation of plasminogen at the cell surface and subsequent plasmin ECM degradation are important features of many (patho)physiological processes involving cell migration (Saksela 1985; Blasi 1993). These include tissue remodelling (Solberg et al. 2001; Krishnan et al. 2004), wound healing (Romer et al. 1991; Romer et al. 1996; Creemers et al. 2000; Frossing et al. 2010; Kawao et al. 2010), macrophage recruitment during inflammation (Plow et al. 1999; Das et al. 2007), skeletal myogenesis (Suelves et al. 2002; Lopez-Alemany et al. 2003), chronic inflammation (Inman and Harpel 1986; Kummer et al. 1992; Wallace et al. 1997) prohormone processing (Parmer et al. 2000; Jiang et al. 2001; Lay et al. 2002), hematopoietic regeneration (Heissig et al. 2007), neurite outgrowth (Jacovina et al. 2001), tumour cell invasion and metastasis (Palumbo et al. 2003; Gonzalez-Gronow et al. 2005; Kwaan and McMahon 2009). Although current knowledge is somewhat limited regarding the degree and diversity of PAS involvement in normal physiology and various disease states (Syrovets and Simmet 2004; Zorio et al. 2008), inhibition of plasmin activity may provide a novel avenue for the treatment of a variety of conditions. The role of PAS dysregulation in the progression, invasion and metastasis of various cancers has received particular interest in the last few decades (Kwaan 1992; Dano et al. 2005; Killeen et al. 2008). The utility of the different components of the PAS as prognostic cancer markers, their role(s) in cancer aetiology and their promise as therapeutic targets have recently been reviewed extensively (Kwaan et al. 2009; Mekkawy et al. 2009; Ulisse et al. 2009; Hildenbrand et al. 2010) and will therefore only be discussed briefly. The uPA/uPAR complex recruits various ECM components (including vitronectin and fibronectin) as well as the epidermal growth factor receptor (Kirchheimer et al. 1987; Kirchheimer et al. 1987) and α5β1 64

integrin (Aguirre Ghiso et al. 1999; Ossowski and Aguirre-Ghiso 2000), resulting in the activation of tyrosine kinase receptors and increased proliferation (Kirchheimer et al. 1988; Kirchheimer et al. 1989). Plasmin and uPA may also directly drive proliferation through proteolytic activation of growth factors, including hepatocyte growth factor (Mars et al. 1993; Shanmukhappa et al. 2009; Sisson et al. 2009), transforming growth factors (Lyons et al. 1990; Yehualaeshet et al. 1999; Katsura et al. 2000; Maeda et al. 2009) and a fibroblast growth factor (Odekon et al. 1992; Herbert et al. 1997; George et al. 2001). The proliferative effects of uPA and plasmin are consistently observed in both normal cells (Jensen and Lavker 1996; Akao et al. 2002) and various cancer cell lines (Konno et al. 1993; Festuccia et al. 1998; Schmidt and Grunsfelder 2001; Gandhari et al. 2006) and are reversible by inhibition of uPA or plasmin (Hibino et al. 1999; Morita et al. 1999; George et al. 2001; Yu et al. 2002; Roztocil et al. 2005; Chen et al. 2006). Both uPA and plasmin degrade most ECM components directly or through the activation of matrix metalloprotease (MMP) zymogens (Figure 4) (Andreasen et al. 1997; Lijnen 2001; Pepper 2001; Kucharewicz et al. 2003; Dano et al. 2005; Henke 2007; Kwaan et al. 2009). In vitro, uPA activates pro-MMP-2 while plasmin activates pro-MMP-1, pro-MMP-3, pro-MMP-

Figure 4: uPA and plasmin MMP activation and ECM degradation. Both uPA and plasmin recruit and degrade various ECM components and activate a number of growth factors through proteolytic processing. uPA and plasmin

also

convert

pro-

matrix

metalloproteases (pro-MMPs) to active MMPs that in turn may activate other pro-MMPs, with amplified ECM degradation, proteolytic growth factor processing and tissue remodelling as a result.

65

9, pro-MMP-10, pro-MMP-13 (Eeckhout and Vaes 1977; He et al. 1989; Saito-Taki et al. 1990; Okada et al. 1992; Knauper et al. 1996) and MT1-MMP, an intermediate of pro-MMP-2 activation (Keski-Oja et al. 1992). A number of MMPs can then activate other pro-MMPs in a positive feedback mechanism, resulting in further degradation of ECM components (Lijnen 2001; Pepper 2001).

Plasmin structure, function and specificity To date, a number of plasmin(ogen) structures have been determined. These include the serine protease domains of plasminogen (µ-plasminogen, PDB accession no. 1QRZ and 1DDJ) (Peisach et al. 1999; Wang et al. 2000) and plasmin (µ-plasmin) in complex with staphylokinase (PDB accession no. 1BUI) (Parry et al. 1998) as well as streptokinase (PDB accession no. 1BML, 1L4Z, 1L4D and 1RJX) (Wang et al. 1998; Wakeham et al. 2002; Terzyan et al. 2004). Overall, the μplasminogen/µ-plasmin structures exhibit a typical trypsin-like serine protease fold (Figure 5AB) (Wang et al. 1998) with highest sequence similarity to the transmembrane serine proteases including lipoprotein a (86%), hepsin (43%), matriptase (43%) and transmembrane peptidase serine 3 (42%) (Figure 5G). Some structural features differentiate plasmin from even closely related serine proteases including a unique activation loop restrained by a disulfide bridge between the P4 (Cys558) and P5’ (Cys566) residues of the zymogen activation site. Removal of this disulfide bond results in markedly reduced activation by plasminogen activators while making plasminogen susceptible to activation by other proteases (Linde et al. 1998). This feature has most likely evolved to ensure specific control of fibrinolysis. Upon activation most serine protease zymogens undergo conformational changes resulting in functional active sites, as has been demonstrated structurally for chymotrypsin (Matthews et al. 1967; Freer et al. 1970) and

66

Figure 5: Structural alignment of the catalytic domains of plasminogen (µ-plasminogen) and related serine proteases. Ribbon plot of (A) hepsin, sc-tPA, uPA and β-trypsinogen (PDB accession nos 1Z8G,1BDA, 3MHW and 1TGN) and (B) µ-plasmin (PDB accession no. 1DDJ) with β-sheets and α-helices shown in yellow and blue respectively and catalytic residues displayed as stick models. The structures were aligned in SwissPdbViewer 4.0.1 using iterative magic fit. µ-plasminogen is shown without the pro-region for visibility. A close-up view of the S1 entrance frame loop of hepsin, tPA, uPA and β-trypsinogen with an open S1 site without substrate (C) and with a bound peptide (D). Hydrogen bonds are shown in green. A close-up view of the S1 entrance frame loop of µ-plasmin from a streptokinase complex (PDB accession no. 1BML) has a similar open S1 site (E) while µ-plasminogen has a different loop conformation and the (continued page 68)

67

Figure 5: (Continued from page 66): position of Trp761 blocks the S1 site (F). Sequence alignments of the structures from (A-B) highlight important structural features while using the same graphics as above (G). Residue numbering over and under alignment refers to plasminogen and chymotrypsin respectively while loop nomenclature refers to the latter. The catalytic triad, disulfide forming cysteines, conserved residues and conservative substitutions are highlighted in cyan, yellow, dark grey and light grey respectively.

trypsin (Stroud et al. 1974; Bode et al. 1976) amongst others. This change is more dramatic in plasminogen compared to other proteases, since the zymogen S1 entrance frame completely lacks the β-sheet secondary structure needed for substrate recognition (Figure 5C and 5F). Proteases commonly bind their substrates and inhibitors through an extended β-sheet across the S1 entrance frame (Figure 5D) (Madala et al. 2010) and its absence in the zymogen may contribute to the extremely low activity of plasminogen. When in complex with streptokinase, the plasmin S1 entrance frame adopts a typical β-sheet (Figure 5E). However, it is well known that the plasminogen-streptokinase complex has a fundamentally different substrate specificity allowing for autolysis of plasminogen (Boxrud et al. 2000; Boxrud et al. 2004). Consequently, the precise native plasmin active site architecture is currently unknown making structural predictions regarding substrate and inhibitor selectivity a particular challenge. However, other sources of information may give clues to the substrate preference of plasmin, including protein/peptide substrate cleavage sites, the screening of various peptide libraries and sequences of known inhibitors. The available data from the former two are summarised in Table 1 while the latter will be discussed in the sections on plasmin inhibitors below. Known peptide cleavage sites suggest that plasmin has rather diverse substrate specificity excluding the P1 preference for basic residues. However, conflicting results have been reported regarding the preferences of the various substrate binding subsites. This may be 68

explained in light of the experimental method used and its limitations. Three studies probed the active site using positional-scanning synthetic combinatorial libraries (PS-SCL). These consist of pooled sub-libraries of peptides for each binding subsite of the protease (Backes et al. 2000; Harris et al. 2000; Gosalia et al. 2005) and poorly predict subsite cooperativity (Schneider and Craik 2009; Swedberg et al. 2009; Swedberg et al. 2010). In addition, since the sub-libraries are produced with mixtures of amino acids with differential reaction rates, equal representation of all amino acids is unlikely and strongly depends on synthesis conditions (Boutin et al. 1997). Consequently, the precise peptide substrate preference of plasmin is yet to be fully defined. Plasmin’s substrate specificity for cleavage of larger peptides and proteins differs considerably from that of small peptides, as indicated by over 100 documented cleavage sites in the MEROPS database (Table 1; http://merops.sanger.ac.uk) (Rawlings et al. 2009). Apart from a strict P1 preference for basic residues, most amino acids are well tolerated at P2-P4 as well as P1’-P4’. In contrast to reported results from PS-SCL screens, substrates with aromatic residues at P2 only account for around 25%. This may reflect plasmin subsite cooperativity between the prime and non-prime sites, exosite interactions with larger protein substrates and steric constraints on the protein binding loops to fit the active site of plasmin. Consequently, Table 1: Substrate specificity of plasmin (μ-plasmin) Method P4 P3 P2 P1 PS-SCL K>R>Q>F Q>A>R/K W>F>Y K PS-SCL K>n>V/F T>-/I F>Y>W K

P1’ ACC ACC

P2’ -

P3’ -

P4’ -

PS-SCL

-

M>Q>L

Y>F/N

K

ACC

-

-

-

PS-SCL

-

M/Q/R

F>Y>H

R

ACC

-

-

-

S/R>V

P/A>G

L/P/G

Protein P/A>R R>S/G L>S>V/A K/R S>A>G substrates Amino acids are shown in the one letter code (n = norleucine)

69

Reference (Harris et al. 2000) (Backes et al. 2000) (Gosalia et al. 2005) (Gosalia et al. 2005) MEROPS (Rawlings et al., 2009 )

different considerations of plasmin specificity need to be made when designing small molecule or protein based inhibitors.

Plasmin protein inhibitors Most naturally occurring plasmin inhibitors belong to a class of serine protease inhibitors commonly referred to as ‘standard’ or Laskowski mechanism inhibitors (Laskowski and Kato 1980; Laskowski and Qasim 2000). These inhibitors bind their targets through a highly conserved and constrained canonical loop in a substrate-like manner to form a reversible yet tight binding complex. Standard mechanism canonical binding loops are typified by a high degree of rigidity due to an internal network of stabilising hydrogen and disulfide bond(s). This allows for positioning the P1’ free amine for peptide bond reformation after the scissile bond is cleaved (Radisky and Koshland 2002; Zakharova et al. 2009) and an acyl-enzyme intermediate with largely unchanged conformation (Shaw et al. 1995; Radisky et al. 2002). As the products of hydrolysis are still associated with the protease, resynthesis of the peptide bond is more favored than the intermolecular reaction with lower local reactant concentrations (Radisky et al. 2002; Zakharova et al. 2009). A number of standard mechanism inhibitors of plasmin are known with the majority containing one or more Kunitz- or Kazal-type domains. Canonical loop sequences for plasmin inhibitors with determined inhibition constants are listed in Table 2. The most prominent Kunitz-type plasmin inhibitor is aprotinin (Figure 6A), which potently inhibits the protease with a Ki of 0.18 nM (Delaria et al. 1997). Infestin from the blood sucking Hemiptera (True bug) is the most potent Kazal-type plasmin inhibitor known (Figure 6B; domains 3 and 4; Ki = 1.1 nM (Campos et al. 2002)). The alignment of canonical loops from these inhibitors suggests that plasmin has a similar preference across the S4-S4’ pockets for protein-based inhibitors as for

70

protein substrates, in contrast to the preference for small peptide substrates (Table 1). Therefore cleavage sites in both protein substrates and inhibitors, for which many structures

Table 2: Plasmin Protein Inhibitors Inhibitor type Source Organism Kunitz-type Inhibitors

Ki (nM)

P4

P3

P2

P1

P1’

P2’

P3’

P4’

References

Amyloid precursorlike protein 2, Kunitz domain Aprotinin

Human

81

G

P

C

R

A

V

M

P

(Petersen et al. 1994)

Bos taurus

0.18

G

P

C

K

A

R

I

I

Bikunin

Human

100

G

P

C

R

A

F

I

Q

Kunitz-type protease inhibitor 2, domain 1 Kunitz-type protease inhibitor 2, domain 2 Leucaena-type trypsin inhibitor Protease nexin 2, Kunitz domain TdPI tryptase inhibitor

Human

1.04

G

R

C

R

A

S

M

P

(Delaria et al. 1997) (Gebhard and Hochstrasser 1986) (Delaria et al. 1997)

Human

0.54

G

P

C

R

A

S

F

P

(Delaria et al. 1997)

Leucaena leucocephala Human

0.32

S

P

Y

R

L

G

S

N

(Oliva et al. 2000)

42

G

P

C

R

A

V

M

P

(Petersen et al. 1994)

Rhipicephalus appendiculat us Pseudonaja textilis Human

55

G

L

C

K

A

R

F

T

(Paesen et al. 2007)

3.5

G

P

C

R

V

R

F

P

(Flight et al. 2009)

26

G

P

C

K

A

I

M

K

(Petersen et al. 1996)

Human

10

G

P

C

R

A

L

L

L

(Kong et al. 2004)

Human (Engineered) Human (Engineered)

0.087

G

P

C

R

A

R

F

D

(Markland et al. 1996)

G

P

C

R

A

R

L

L

(Bajaj et al. 2010)

Textilinin-1 Tissue factor pathway inhibitor-1, unit 1 Tissue factor pathway inhibitor-2, unit 1 DX-1000 KD1-L17R Kazal-type Inhibitors Aedes aegypti trypsin inhibitor Bdellin

Aedes aegypti

3.8

A

C

P

R

I

Y

M

P

(Watanabe et al. 2010)

Hirudo nipponia Canis familiaris

1.56

V

C

T

K

E

L

L

R

(Kim et al. 2001)

Bikazin salivary inhibitor, unit 1 Chicken liver trypsin Mleagris inhibitor-1 gallopavo Infestin, domains Triatoma 3 and 4 infestans Subtilisin inhibitor-like

2000

A

C

P

R

L

H

Q

P

(Hochstrasser and Fritz 1975)

127

G

C

P

R

D

Y

S

P

(Kubiak et al. 2009)

1.1

A A

C C

T F

K R

M N

Y Y

K V

P P

(Campos et al. 2002)

Plasminostreptin

0.49

A

C

T

K

Q

F

D

P

(Kakinuma et al. 1978)

S. antifibrinolyticus

71

are available (Madala et al. 2010), may be used to guide the reengineering of protein based plasmin inhibitors. To date, possibly due the previously dominant position of aprotinin, only two engineered protein inhibitors targeting plasmin have been reported (Ley et al. 1996; Markland et al. 1996; Bajaj et al. 2010). Markland et al. (1996) used phage display methods to modify the first Kunitz-like domain of the lipoprotein-associated coagulation inhibitor to produce a plasmin inhibitor. The resulting compound (DX-1000) inhibited plasmin with a Ki of 0.087 nM with more than 2800-fold specificity over plasma kallikrein, neutrophile elastase, factor Xa, chymotrypsin, uPA and thrombin (Ley et al. 1996; Markland et al. 1996). The inhibitor also showed remarkable stability to changes in pH, temperature and redox reactions (Markland et al. 1996). Since DX1000 was designed to target plasmin activity in cancer progression, rapid plasma clearance rates of the protein led to the development of a second generation PEGylated variant (4PEGDX-1000; Ki = 0.99 nM) with a 25-fold increase in serum half-life to 11 hours. A model of DX-1000 in complex with µ-plasmin provides insights into the potency and specificity of this inhibitor (Figure 6C). The conserved binding loop of this Kunitz-type inhibitor appeared to interact through backbone hydrogen bonds across P3 to P2’ including an extended β-sheet across P1-P2, as is typical for this class of inhibitor (Rawlings et al. 2004; Madala et al. 2010). Unique to DX-1000 are the binding loop side chain interactions. These included the guanidino nitrogens of the P2’ Arg that formed one and two hydrogen bonds with the plasmin backbone carbonyl of His586 and the carboxyl group of Glu623 respectively. In addition, both the backbone carbonyl group and the carboxylic side chain of the P4’ Asp in DX-1000 seemed to form hydrogen bonds with Lys607 of plasmin with additional aromatic ring stacking (π-π interaction) between the inhibitor P3’ Phe and plasmin Phe587. No amino acid side chain interactions beyond P1 were visible in the non-prime side of the inhibitor.

72

Figure 6: Structure of Kunitz-type and Kazal-type domains. Ribbon plot of (A) the Kunitz-type inhibitor aprotinin (PDB accession no 3FP6) and (B) the Kazal-type inhibitor infestin1 (PDB accession no. 2F3C) with β-sheets and α-helices shown in red and blue respectively. Carbon, oxygen, nitrogen and sulfur are represented by grey, red, blue and yellow respectively in stick model while hydrogens are excluded. The N- and C- terminal as well as protein binding sites (P-sites) of the inhibitors binding loops are labelled. (C) Stick model of the binding loop of the engineered Kunitz-type plasmin inhibitor DX-1000 bound to the solvent accessible surface of µ-plasmin. This model of DX-1000 was produced employing Swiss Model (Guex et al. 2009) using the second Kunitz domain of tissue factor pathway inhibitor (PDB ID: 1TFX) as a template. The complex was created by an overlay of DX-1000 with µ-plasmin (PDB ID: 1L4Z) in SPDBV 2

4.01 (RMSD 0.85 Å ) (Guex and Peitsch 1997) before energy minimization in YASARA Dynamics (Krieger et al. 2002) using the AMBER 2003 force field with default settings.

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Based upon the above findings regarding plasmin’s P2’ preference for Arg, investigators recently substituted a single amino acid (P2’ Leu to Arg) in the tissue factor pathway inhibitor-2 (TFPI-2) producing a potent (Ki = 0.9 nM) plasmin inhibitor (Bajaj et al. 2010). The inhibitor (KD1-L17R) also showed more than 3000-fold selectivity over all proteases screened including plasma kallikrein, tPA, factor XIa, factor VIIa and factor IIa. In addition, KD1L17R exhibited similar efficacy to aprotinin in a mouse liver laceration bleeding model (Bajaj et al. 2010).

Plasmin small molecule inhibitors Originally developed as an inhibitor of thrombosis, the synthetic basic P1 residue analogue ONO-3307 (4-sulfamoyl phenyl-4-guanidinobenzoate methanesulfonate) also inhibited plasmin (Ki = 330 nM) with similar potency to that of thrombin, trypsin and plasma kallikrein (Matsuoka et al. 1989). Directly targeting plasmin, Okada et al. (1998) used substrate guided design methods to produ(ce a series of peptide chloromethyl ketone inhibitors. Most potent of these variants was D-Ile-Phe-Lys-CH2Cl which inhibited plasmin with a Ki of 570 nM, while neither of the inhibitors showed much selectivity over thrombin, plasma kallikrein or trypsin (Okada et al. 1988; Tsuda et al. 1989). These investigators also produced a range of compounds with P1 Arg and Lys in conjunction with an assortment of phenyl derivates at the P2, P1’ and P2’ sites that resulted in plasmin inhibitors (Ki ≥ 500 nM) with some selectivity over plasma kallikrein, uPA, thrombin and trypsin (Teno et al. 1991; Teno et al. 1993). More recently, the same group also designed a series of inhibitors targeting the S1-S2’ pockets of plasmin using 4aminomethylcyclohexanecarbonyl as the P1 basic residue analogue. The most potent and specific variants had plasmin inhibition constants around 500 nM and exhibited between twoto sixty-fold specificity over plasma kallikrein, urokinase, thrombin and trypsin (Okada et al.

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2000; Okada et al. 2000). A somewhat different strategy was used by Xue and Seto who employed a P1 cyclohexanone group designed to react with the active site Ser to form a reversible hemiketal (Abato et al. 2002; Xue and Seto 2005; Xue and Seto 2005; Xue and Seto 2006). One successful strategy involved the synthesis of a 400 member peptide library made up of fixed Trp residues at the P2 and P2’ positions, while combining all possible combinations of the 20 natural amino acids at P3 and P3’. The most suitable inhibitor from this library (IC50 = 2.7 μM) inhibited plasmin with a 150-fold selectivity over plasma kallikrein, thrombin and trypsin (Xue et al. 2005). Recently, a small (700 Da) and potent plasmin inhibitor (CU-2010) with peptide-like properties was reported (Dietrich et al. 2009). Although its structure is yet to be published, it belongs to the class of amidine inhibitors that binds to Ser190 (chymotrypsin numbering) at the bottom of the S1 pocket (Katz et al. 2001). This inhibitor potently inhibited plasmin (Ki = 2.2 ± 0.2 nM), showed similar antifibrinolytic properties compared with aprotinin in vitro (Dietrich et al. 2009) and significantly reduced postoperative blood loss in a canine model of cardiopulmonary bypass (Szabo et al. 2010; Szabo et al. 2010). However, CU-2010 appeared to be a rather non-specific serine protease inhibitor with similar inhibition levels for factor Xa and XIa and was a 100-fold more potent towards plasma kallikrein. The investigators suggest that the off-target properties of CU-2010 are desirable since they may confer similar antiinflammatory properties as seen for aprotinin that could counteract systemic inflammatory responses during cardiopulmonary bypass (Dietrich et al. 2009). However, others have proposed that aprotinin inhibition of plasma kallikrein and/or tissue kallikrein could explain aprotinin associated increases in the incidence of myocardial infarction, stroke and renal failure (Vio et al. 1998; Saxena et al.)

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Conclusions There is a need for alternative, more potent and specific inhibitors of plasmin to regulate fibrinolysis. Although, lysine analogues adequately reduce perioperative bleeding, their low affinity requires the administration of very large doses. In addition, they bind non-specifically to various lysine binding sites which may include the S1 pocket of various tryptic serine proteases. The consequences of non-specific binding has been evaluated in comparison to established alternatives in a large independent study (Koster et al. 2010). Non-specific inhibitors have an inherent disadvantage since interaction with many physiological components is more likely to produce further variability in response across a diverse population of individuals. This may to some extent explain the large variation seen in the dosing regimen of lysine analogues (Royston 1998; Mannucci et al. 2007). In contrast, potent and specific plasmin inhibitors would provide an exquisite regulation of plasmin activity during surgery. Aprotinin inhibition of serine proteases other than plasmin has been shown to result in desirable anticoagulant and anti-inflammatory properties. Moreover, the precise mechanism(s) behind these effects are poorly understood (McEvoy et al. 2007; Ide et al. 2009; Vande Vusse et al. 2010) and aprotinin use has been associated with increased morbidity and mortality rates. Since aprotinin is a non-specific inhibitor it is also more likely to produce a variable response across a dissimilar population of individuals. Therefore, a better understanding of which aprotinin targets give the most desired anticoagulant and anti-inflammatory properties is needed. This may enable design of potent and selective inhibitors to regulate coagulation and inflammatory responses during surgery that may be adjusted according to the particular need of an individual. There is also a growing interest in the development of plasmin inhibitors to control tissue remodelling, particularly in relation to cancer progression, metastasis and angiogenesis 76

(Abato et al. 2002; Xue et al. 2005; Xue et al. 2005; Xue et al. 2006; Devy et al. 2007). Although more research is needed to understand the precise roles of the different components of the PAS in various (patho)physiological processes (Syrovets et al. 2004; Zorio et al. 2008), potent and specific inhibitors may well prove to be viable options for the treatment of a number of diseases relating to cell migration/tissue remodelling in the future. Additionally, such inhibitors would provide researchers with essential tools to further deconstruct the different roles of the various components of the PAS system both in vitro and in animal models. Although inhibitors targeting fibrinolysis and cell migration/tissue remodelling have the common goal of blocking plasmin activity, different properties are needed relating to spatial and temporal action. For inhibitors regulating tissue remodelling, desirable attributes are the systemic distribution (or targeted to a particular site) and prolonged retention times. In contrast, plasmin inhibitors confined to the plasma with more rapid clearance time are suitable to provide delicate regulation of bleeding during the perioperative period. Although it is unclear why aprotinin treatment during cardiac surgery may be associated with increased mortality rates (Fergusson et al. 2008), there seems to be a link to kidney damage through an incompletely understood mechanism(s) (Dietrich 2009). Exogenous aprotinin (in contrast to the endogenous human counterpart) rapidly accumulates in vesicles of proximal tubule cells and colocalises with tissue kallikrein in connecting tubule cells in rat kidneys (Vio et al. 1998). It has been suggested that aprotinin inhibition of tissue and plasma kallikrein may account in part for observed increases in myocardial infarction, stroke and renal failure (Feindt et al. 1995; Vio et al. 1998; Saxena et al.). Consequently, to maximise the chance of clinical success of future plasmin inhibitors, desirable properties are likely to include high selectivity of inhibition combined with low accumulation in the kidneys.

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Candidate plasmin inhibitors may include naturally occurring proteins as is the case for textilinin-1 (Flight et al. 2009) or re-engineered versions as in the case of DX-1000 (Ley et al. 1996; Markland et al. 1996) and KDI-L17R (Bajaj et al. 2010). The advantage of this approach is that the structure and large binding surface are pre-optimised for high affinity binding. As a result, specificity of inhibition may be compromised as most protein based serine protease inhibitors have more than one target. For example, textilinin-1 inhibits tissue kallikrein at a similar level to plasmin, while the DX-1000 inhibition constant for this kallikrein has not been reported (Devy et al. 2007). The TFPI-2 based inhibitor KD1-L17R shows sufficient selectivity over blood clotting enzymes screened, although tissue kallikrein inhibition is yet to be evaluated (Bajaj et al. 2010). However, protein based inhibitors with properties similar to aprotinin, including short retention times in serum, may accumulate at high levels in the kidneys. DX-1000 exhibits renal concentration at similar levels as for aprotinin, although polyethylene glycol labelling of the inhibitor increased tissue retention times and therefore reduced kidney buildup (Devy et al. 2007). In the case of DX-1000 and other inhibitors that target plasmin activity in the tumor environment, decreasing inhibitor clearance rates are advantageous. In contrast to plasmin inhibitors targeting cell migration and/or tissue remodelling, regulators of fibrinolysis may benefit from a short serum half-life and rapid elimination. This makes potent and specific small molecule inhibitors a more attractive alternative to minimise any risk of side effects seen for aprotinin. However, small molecule peptide and peptide mimetic plasmin inhibitors produced to date, mostly suffer from a lack of selectivity. This highlights both the structural similarities between the various serine proteases present in the serum and the particular challenge of designing specific inhibitors for this group of enzymes.

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Therefore, structures of µ-plasmin in its native conformation are urgently needed to enable the design of inhibitors capitalising on minor while significant differences between these proteases.

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Article Substrate-Guided Design of a Potent and Selective Kallikrein-Related Peptidase Inhibitor for Kallikrein 4 Joakim E. Swedberg,1 Laura V. Nigon,1 Janet C. Reid,1 Simon J. de Veer,1 Carina M. Walpole,1 Carson R. Stephens,1 Terry P. Walsh,1 Thomas K. Takayama,2 John D. Hooper,1 Judith A. Clements,1 Ashley M. Buckle,3 and Jonathan M. Harris1,* 1Institute

of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland 4059, Australia of Biochemistry and Urology, University of Washington, Box 357350, Seattle, WA 98195-7350, USA 3Department of Biochemistry and Molecular Biology, School of Biomedical Sciences, Faculty of Medicine and Victorian Bioinformatics Consortium, Monash University, Clayton, Victoria 3800, Australia *Correspondence: [email protected] DOI 10.1016/j.chembiol.2009.05.008 2Departments

Due to copyright restrictions, the published version of this article is not available here. Please consult the hardcopy thesis available from QUT Library or view the author version online at: http://dx.doi.org/10.1016/j.chembiol.2009.05.008

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Mastering the Canonical Loop of Serine Protease Inhibitors: Enhancing Potency by Optimising the Internal Hydrogen Bond Network

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Mastering the Canonical Loop of Serine Protease Inhibitors: Enhancing Potency by Optimising the Internal Hydrogen Bond Network Joakim E. Swedberg1, Simon J. de Veer1, Kei C. Sit1, Cyril F. Reboul2, Ashley M. Buckle2, Jonathan M. Harris1* 1 Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia, 2 Department of Biochemistry and Molecular Biology, School of Biomedical Sciences, Faculty of Medicine and Victorian Bioinformatics Consortium, Monash University, Clayton, Victoria, Australia

Abstract Background: Canonical serine protease inhibitors commonly bind to their targets through a rigid loop stabilised by an internal hydrogen bond network and disulfide bond(s). The smallest of these is sunflower trypsin inhibitor (SFTI-1), a potent and broad-range protease inhibitor. Recently, we re-engineered the contact b-sheet of SFTI-1 to produce a selective inhibitor of kallikrein-related peptidase 4 (KLK4), a protease associated with prostate cancer progression. However, modifications in the binding loop to achieve specificity may compromise structural rigidity and prevent re-engineered inhibitors from reaching optimal binding affinity. Methodology/Principal Findings: In this study, the effect of amino acid substitutions on the internal hydrogen bonding network of SFTI were investigated using an in silico screen of inhibitor variants in complex with KLK4 or trypsin. Substitutions favouring internal hydrogen bond formation directly correlated with increased potency of inhibition in vitro. This produced a second generation inhibitor (SFTI-FCQR Asn14) which displayed both a 125-fold increased capacity to inhibit KLK4 (Ki = 0.038660.0060 nM) and enhanced selectivity over off-target serine proteases. Further, SFTI-FCQR Asn14 was stable in cell culture and bioavailable in mice when administered by intraperitoneal perfusion. Conclusion/Significance: These findings highlight the importance of conserving structural rigidity of the binding loop in addition to optimising protease/inhibitor contacts when re-engineering canonical serine protease inhibitors. Citation: Swedberg JE, de Veer SJ, Sit KC, Reboul CF, Buckle AM, et al. (2011) Mastering the Canonical Loop of Serine Protease Inhibitors: Enhancing Potency by Optimising the Internal Hydrogen Bond Network. PLoS ONE 6(4): e19302. doi:10.1371/journal.pone.0019302 Editor: Bostjan Kobe, University of Queensland, Australia Received December 2, 2010; Accepted March 29, 2011; Published April 27, 2011 Copyright: ß 2011 Swedberg et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: Work in the corresponding author’s laboratory is supported by the National Health and Medical Research Council (grant #497270), Cancer Council Queensland (Grant #44323) and the Prostate Cancer, Foundation of Australia (Grant #PR09). SJD receives funding from the Smart Futures Fund (Queensland Government, Australia). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: Authors Swedberg and Harris have filed an Australian patent on the composition of a potent and selective KLK4 inhibitor (WO/2010/ 017,587). This does not alter the authors’ adherence to all the PloS ONE policies on sharing data and materials. * E-mail: [email protected]

biomarkers and therapeutic targets [4,5], particularly in hormonedependent cancers [6]. One KLK of interest, KLK4, is principally expressed in basal and secretory cells of the prostate gland and is commonly overexpressed in malignant prostate tumours [7,8]. Recent studies indicate that the proteolytic activities of KLK4 closely align with events central to cancer development and progression. Firstly, KLK4 has been shown to degrade components of the extracellular matrix in vitro [9], as well as cleave insulin-like growth factor binding protein 3-6 [10] and urokinase plasminogen activator receptor [11]. Secondly, cell culture experiments have demonstrated that KLK4 enhances a diverse array of strongly tumourigenic functions. Of note, KLK4 stimulates proteaseactivated receptors 21 and 22 which are also overexpressed in prostate cancer, resulting in cytoskeletal remodelling and increased cell migration and proliferation [12,13,14]. These findings complement earlier studies which found overexpression of KLK4 was associated with an epithelial-to-mesenchymal transi-

Introduction Prostate cancer is the most commonly diagnosed male cancer in western countries, accounting for more than 32,000 deaths last year in the United States alone [1]. Although current treatments for localized prostate cancer are highly successful, less than one third of patients with metastatic disease survive five years following diagnosis [1]. This emphasises the urgent need for effective treatments for patients suffering from late stage disease. Prostate cancer is primarily detected using serum levels of kallikrein-related peptidase 3 (KLK3, prostate-specific antigen, PSA), which is the established biomarker for diagnosis and prognosis [2]. KLK3 belongs to the kallikrein-related peptidase (KLK) multi-gene family which encodes fifteen homologous serine endopepti dases with trypsin or chymotrypsin-like substrate specificity. It is well documented that KLK proteases significantly contribute to several important (patho)physiological functions [3]. Consequently, there is a growing interest in the utility of KLKs in certain pathologies as

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affinity for KLK4 similar to that of SFTI-1 for trypsin while selectivity was markedly improved. These findings underline the importance of binding loop rigidity in canonical serine protease inhibitors and the need to maintain structural stability when modifying compounds of this class.

tion in prostate cancer cells [8] and that KLK4 may modulate interactions between tumour cells and osteoblasts in the development of bone metastases [15]. Therefore, targeted inhibition of KLK4 may present an avenue to new treatments for advanced prostate cancer. It has previously been reported that the naturally occurring sunflower trypsin inhibitor (SFTI-1) inhibits KLK4 [16], in addition to known targets such as trypsin [17], cathepsin G [18] and matriptase (ST14/MT-SP1) [19]. SFTI-1 is a 1.4 kDa cyclic Bowman-Birk serine protease inhibitor (BBI) isolated from sunflower (Helianthus annuus) seeds. Its three-dimensional structure in complex with trypsin [17] reveals a dual anti-parallel b-sheet arrangement stabilized by a disulfide bridge and an extensive internal hydrogen bonding network [20]. SFTI-1 binds to target proteases by an extended b-sheet across the P1-P4 residues to form a tight binding complex (trypsin/SFTI-1 Ki = 0.1 nM) [21]. This mode of binding is not only common to canonical serine protease inhibitors [22] but forms the basis of protein substrate and inhibitor recognition across all families of proteases [23]. Another important feature of SFTI-1 is that its scissile bond (P1–P19) can be cleaved and reformed with an equilibrium of 1:9 in favour of the intact bond [24]. This phenomenon is evident in at least 19 convergently evolved serine protease inhibitor families [25] and is referred to as ‘standard’ or Laskowski mechanism of inhibition [26,27]. Standard mechanism binding loops are typified by a high degree of rigidity due to an internal network of stabilising hydrogen and disulfide bond(s). This has particular significance to inhibitor function; not only does it allow for a lower entropic debt upon protease binding [28], it also permits formation of an acyl-enzyme intermediate with largely unchanged conformation [29,30]. As the products of hydrolysis are still associated with the protease, resynthesis of the peptide bond is more favoured than the intermolecular reaction with lower local reactant concentrations [30,31]. To harness the favourable structural features of SFTI-1 and redirect inhibition towards KLK4, the contact b-sheet of SFTI was recently re-engineered using a sparse matrix peptide library to guide amino acid substitutions. The resulting inhibitor, SFTIFCQR (P1 Lys to Arg, P2 Thr to Gln and P4 Arg to Phe) selectively inhibited KLK4 (Ki = 3.5960.28 nM) and uniformly showed low inhibition of other SFTI-1 targets and closely related KLKs [16]. However, the constrained geometry of SFTI prevents the use of linear peptide libraries to optimise interactions beyond the P1–P4 residues, while producing a synthetic SFTI library is prohibitively costly and time consuming. Therefore, it is more practical to screen a virtual library of SFTI-FCQR variants. Conventional in silico scoring functions rely on docking algorithms that treat the bonds of the ligand and receptor as rigid or semi-flexible to reduce the computational costs. However, these methods only have an acceptable degree of accuracy when considering ligands with few conformational states [32,33]. Molecular dynamics (MD) offers a solution to the problem of structural flexibility. Indeed, several studies have successfully used MD to predict inhibitor performance, yielding new lead compounds or improving existing inhibitors [34,35]. Recent advances in graphics card processors (GPUs) [36] have enabled GPU-implementation of MD algorithms, making them more accessible for flexible receptor-ligand analysis. Here the GPU-implemented MD algorithms ACEMD [37] and NAMD [38] are used to explore the SFTI-1/trypsin complex and analyse an in silico library of SFTI-FCQR variants. Increased internal hydrogen bond frequency showed a high degree of accordance with enhanced inhibition in vitro. The most favourable substitution produced a second generation inhibitor with a binding PLoS ONE | www.plosone.org

Methods Protein expression and purification Recombinant KLK4 and KLK14 were produced using Sf9 insect cell expression constructs as previously reported [14,16]. These expression vectors generate the complete KLK amino acid sequence followed by a V5 epitope (GKPIPNPLLGLDST) and polyhistidine tags. Pro-KLKs were purified from conditioned media using Ni2+-nitrilotriacetic acid agarose (Qiagen) according to the manufacturer’s instructions. After confirming the identity of purified proteins by Western blot analysis, pro-KLKs were aliquoted and stored at 280uC.

Molecular dynamics SFTI-FCQR variant/KLK4 complexes were generated by overlay of KLK4 (PDB ID 2BDG) and the trypsin/SFTI-1 ˚ ) [39] complex (PDB ID 1SFI) in SPDBV v4.01 (RSMD 0.96 A while mutations were made in YASARA Dynamics 9.12.13 [40]. Systems were solvated with TIP3P water and neutralized by Na+/ Cl2 counterions to a final concentration of 100 mM in VMD 1.8.7 [41]. This generated systems of approximately 28000 atoms including 9000 water molecules. Each protease–inhibitor complex was equilibrated using a stepwise relaxation procedure. In the first stage, all heavy-atoms were harmonically restrained with a force constant of 2 kcal/ ˚ 2) before a conjugate gradient minimization of 5000 steps (mol A was applied using NAMD 2.6 [38] and CHARMM27 force fields parameters. This was followed by heating to 298 K before simulating 500 ps under NPT conditions with periodic boundary conditions. A Langevin thermostat with a damping coefficient of 0.5 ps21 was used to maintain the system temperature. The system pressure was maintained at 1 atm using a Langevin piston barostat. The particle mesh Ewald algorithm was used to compute long-range electrostatic interactions at every time step and non˚ and bonded interactions were truncated smoothly between 7.5 A ˚ . All covalent hydrogen bonds were constrained by the 9A SHAKE algorithm (or the SETTLE algorithm for water), permitting an integration time step of 2 fs. For the second stage, the restraints were retained on the protease and inhibitor acarbons (Ca) only, while all constraints were released in the third stage. Three independent production runs of 5 ns were carried out for each system using ACEMD [37]. These simulations were performed under NVT with otherwise identical force field and simulation parameters as above. Coordinates were saved every 500 simulation steps producing 5000 frames per run. Analyses were performed using VMD 1.8.7 with hydrogen bond lengths ˚ respectively, chosen to align with and angles set to 40u and 3.3 A the reported trypsin/SFTI-1 complex [17].

Synthesis of SFTI variants All reagents were obtained from Auspep and all solvents from Merck unless stated otherwise. Inhibitors were synthesised as linear peptides on 2-chlorotrityl resin (1.3 mmol/g) derivatized with 0.9 mmol/g of the first residue, Ser (P19). Coupling of the following nine residues was achieved using four-fold excess of Fmoc-protected amino acids dissolved in 0.25 M each of 2(1H-benzotriazole-1-yl)-1,1,3,3-tetramethyluronium hexafluoropho2

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inhibition as previously described [44] using assay conditions as above and 500 mM substrate. Assays for inhibition of fibrinogen proteolysis used the same buffer and enzyme concentrations as above with 7 mM fibrinogen substrate. Proteolysis proceeded for 15 min (trypsin), 90 min (KLK4 and 14) or 180 min (KLK12) before termination by boiling in SDS-PAGE sample buffer. Proteolysis fragments were separated on 10% polyacrylamide gels.

sphate (HBTU), 1-hydroxybenzo-triazole (HOBt), and N,N-diisopropylethylamine (DIPEA) in N,N-dimethylformamide (DMF). Fmoc protecting groups were removed by incubation in 50% piperidine and 5% 1,8-diazabicyclo[5.4.0]undec-7-ene (DBU) in DMF. Addition of the final four residues occurred as above, except that DMF was replaced with ‘magic mix’ solvent to prevent aggregation (Zhang et al., 1994). This contained equal parts of DMF, DCM and N-methyl-2-pyrrolidone (NMP) or DMF, toluene and NMP for coupling and Fmoc removal respectively. Linear peptides were liberated from the solid support by successive changes of 0.5% trifluoroacetic acid (TFA) in dichloromethane (DCM). Cyclisation of the peptide backbone was achieved in solution using 125 mM each of 1-hydroxy-7-azabenzotriazole (HOAt) and benzotriazol-1-yl-oxytripyrrolidinophosphonium hexafluorophosphate (PyBOP) dissolved in DMF containing 0.25 M DIPEA. Cyclization proceeded for 48 hr before dilution with an equal volume of DCM and extraction with H2O to remove residual reactants. Side chain protecting groups were removed from the dry product by cleavage for 2 hr in 93.75% TFA, with scavengers; 1.25% triisopropylsilane (TIS), 1.25% H2O and 3.75% thioanisole. Cleaved peptides were purified from remaining synthetic by-products by reverse phase HPLC (rp-HPLC) across a gradient of 20-100% isopropanol using a Jupiter 4 m Proteo 90A C-18 column (Phenomenex). Formation of the internal disulphide bond was achieved by overnight stirring in an aqueous redox buffer (150 mM Tris-HCl pH 8.0, 1 mM EDTA, 10 mM reduced glutathione, 1 mM oxidised glutathione) while monitoring the reaction progress by MALDI-TOF mass spectrometry. Completed SFTI variants were purified, lyophilised and stored at -20uC.

Stability of SFTI variants in cell culture The half-life in cell culture for SFTI-FCQR Asn14 and SFTIFCQR Lys14 was determined using previously described methods [16]. Briefly, monolayers of LNCaP, 22Rv1 and PC3 cells were established in RPMI 1640 medium supplemented with 10% foetal calf serum (HyClone), 100 U/ml penicillin (Invitrogen) and 100 mg/ml streptomycin (Invitrogen). Cells were treated 61 mM inhibitor (SFTI-FCQR Asn14 or SFTI-FCQR Lys14) in fresh serum-containing media. Samples of media were taken at 24 hr intervals and boiled at 97uC for 15 min to denature serum protein. Residual inhibition by SFTI-FCQR variants was determined in competitive kinetic assays (as above), adding a volume of media to give 10 nM SFTI-FCQR Asn14 or 25 nM SFTI-FCQR Lys14 at 0 hr. Media without inhibitor was used to adjust for any endogenous media inhibition and data represent the mean 6 SEM of three triplicate experiments.

Assessment of bioavailability in mice Stability and bioavailability of SFTI-FCQR Asn14 in vivo was assessed in BALB/cFoxn1/Arc mice by oral, intravenous and intraperitoneal delivery (3 mg/kg). Inhibitor was dissolved in PBS at a concentration of 0.6 mg/ml prior to dosing. Serum levels of SFTI-FCQR Asn14 were subsequently measured by Liquid Chromatography-Mass Spectrometry (LC-MS) at Tetra Q laboratories (University of Queensland, Brisbane, Australia). This study was carried out in strict accordance to the recommendations of the Australian Code of Practice for the Care and Use of Animals for Scientific purposes (7th edition 2004) and the protocol was approved by the University of Queensland Animal Ethics Committee (ABS group) which assigned the project approval code TetraQ/479/09/Bluebox. All efforts were made to minimize suffering by experimental animals.

Synthesis of peptide substrates Peptide para-nitroanilide (pNA) substrates were synthesised on pphenylenediamine (Sigma-Aldrich) derivatised 2-chlorotrityl resin (1.3 mmol/g) according to previously described methods [16,42]. Completed substrates were purified by rp-HPLC, validated by MALDI-TOF/MS and lyophilised before storage at 220uC.

Inhibition assays Bovine b-trypsin, bovine a-chymotrypsin and human thrombin were obtained from Sigma while KLK12 and matriptase were from R&D Systems. Increasing concentrations of inhibitors were incubated with various concentration of protease (final concentrations: KLK4, 1.5 nM; KLK12, 15 nM; KLK14, 2 nM; trypsin, 1 nM; matriptase, 4 nM; thrombin, 25 nM; a-chymotrypsin 25 nM) for 20 min in 200 ml assay buffer (100 mM Tris-HCl, 100 mM NaCl2, 0.005% triton-X, pH 8.0). Assays with thrombin and trypsin included 10 mM CaCl2. Enzyme activity was initiated by addition of substrate in 100 ml assay buffer (final concentration 100 mM; see Table 2). The rate of hydrolysis was measured at 405 nm over 7 min and was linear over this period. The extended assay period allowed for identification of inhibitors that were degraded. For SFTI-FCQR Asp14, Ki was determined by inhibition at various substrate concentrations using the competitive inhibition model and non-linear regression in Prism 5 (GraphPad Software Inc). The Ki for this inhibitor was also determined using the Morrison equation for tight binding inhibitors [43] (FVQR-pNA KM = 679.96113.1 mM [16]) and non-linear regression in Prism 5. Both methods produced comparable results (Table 2) and subsequent Ki values were determined with the Morrison method. Since SFTI-FCQR Asn14 had an IC50 below the concentration of KLK4, assays for this inhibitor were repeated with 0.15 nM KLK4 over 2 hr. The kon and koff were determined from the lag phases and steady state of PLoS ONE | www.plosone.org

Results Molecular dynamics reveals a reduction in internal hydrogen bonds for SFTI-FCQR Asp14 compared to SFTI-1 The contribution of various SFTI-1 residues to inhibitor rigidity and complex stability was examined by molecular dynamics simulations on the trypsin/SFTI-1 complex (Figure 1A; PDB ID 1SFI). Post-simulation analysis of the internal hydrogen bond network agreed with the reported structure [17] regarding the reactive loop while differing in the side loop (Figure 1B). Most notably, rather than acting solely as a proton acceptor for the backbone amide nitrogen atom of Arg2, the Asp14 side chain more often formed hydrogen bonds with the guanidino nitrogens of Arg2. These hydrogen bonds are evident in 20% of conformations in a solution structure of SFTI-1 [21]. Additionally, it appeared that the Asp14-Arg2 side chain hydrogen bonds subtly altered the backbone conformation meaning that the hydrogen bond between the amide of Gly1 and carbonyl oxygen of Phe12 seen in the crystal structure was infrequent. Consistent with this, the Ca RMSD values of SFTI-1 from the MD trajectory showed that the reactive loop conformation closely aligned with the starting structure while the side loop deviated markedly (Figure 2A). Determining Ca RMSD values using the 3

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Figure 1. Representation of a trypsin/SFTI-1 complex and internal hydrogen bonding within SFTI variants during MD. Ribbon plot of SFTI-1 in complex with trypsin (A) with b-sheets and a-helices coloured in yellow and blue respectively, excluding SFTI-1 which is displayed in magenta. The residues of the catalytic triad of trypsin and the P1 Lys of SFTI-1 are shown in stick models with carbon in green, nitrogen in blue and oxygen in red. The structure of SFTI variants are shown in ball and stick 2D model with intramolecular hydrogen bond networks for (B) SFTI-1, (C) SFTI-FCQR Asp14 and (D) SFTI-FCQR Asn14. Amino acids are labelled with one letter code and residue number in subscript while the frequency of hydrogen bonds per residue is in brackets (rounded to nearest tenth). Carbons, oxygen, nitrogen and sulphur are represented by gray, red, blue and yellow respectively while hydrogens are excluded for clarity. Bond lengths and angles are intentionally unrealistic to enable easy viewing of hydrogen bonds, represented by dotted green line. Only hydrogen bonds occurring in more than 50% of trajectory frames are shown. Data is represented as mean from three independent 5 ns MD trajectories. doi:10.1371/journal.pone.0019302.g001

Asp14 in the side loop no longer formed any recurrent internal hydrogen bonds. Perhaps as a result of the latter, the backbone hydrogen bonding pairs Phe2-Phe12 (Arg2-Phe12 in SFTI-1) and Gly1-Phe12 seen in the trypsin/SFTI-1 structure were again prevalent. These changes in internal hydrogen bonding pattern were accompanied by an altered conformation that poorly aligned with the SFTI-1 starting structure (Figure 2A) and reduced rigidity across the scaffold (Figure 2B and C).

simulation average structure as a reference indicated that although the change in conformation in the side loop varied from the SFTI1 structure, the new conformation was stable (Figure 2B and C). The most rigid backbone atoms were found in residues that formed an extended b-sheet with trypsin (P3-P1) and as a result were flanked by both internal and intermolecular hydrogen bonds. Overall, the average number of internal hydrogen bonds for trypsin/SFTI-1 was 7.0060.07, equivalent to the total number identified in the crystal structure. Previously, SFTI-1 was re-engineered to produce a selective KLK4 inhibitor (SFTI-FCQR Asp14) by optimising protease/ inhibitor interactions [16]. To examine the impact of modifying the contact b-sheet of SFTI on the distribution of internal hydrogen bonds, corresponding simulations were performed on KLK4 (PDB ID 2BDG) in complex with a model of SFTI-FCQR Asp14. The resulting analysis suggested a marked reduction (mean = 3.7060.11) and rearrangement of the internal hydrogen bond network compared to SFTI-1 (Figure 1B). In the reactive loop, the side chain Thr4-Ser6 hydrogen bond was replaced by one between the carbonyl oxygen of Gln4 and the amide of Ser6 while PLoS ONE | www.plosone.org

Substitution at Asp14 alters internal hydrogen bonding in SFTI Inspection of the KLK4/SFTI-FCQR Asp14 simulation trajectories revealed that Asp14 showed a high level of disorder and was too far from KLK4 to make contact and thus appeared not to contribute to complex stability. This suggested that substitution of Asp14 could present an opportunity to restore the internal hydrogen bonding network of the inhibitor. Structural imperatives restricted the opportunities for further replacements around the SFTI backbone and so no further substitutional analyses of these positions were undertaken. Accordingly, a library of SFTI-FCQR 4

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Figure 2. RMSD analysis for SFTI variants during MD. RMSD values between Ca of SFTI-1, SFTI-FCQR Asp14 and SFTI-FCQR Asn14 during MD and the (A) SFTI-1 starting structure or (B) calculated average simulation structures. (C) Ribbon plot showing the average simulation structures coloured according to Ca RMSD from low to high as blue, purple, magenta, orange, and red, labelled with odd residue numbers. Data is represented as mean from three independent 5 ns MD trajectories. doi:10.1371/journal.pone.0019302.g002

variants containing all naturally occurring amino acids (excluding cysteine) at residue 14 was simulated followed by hydrogen bonds analysis (Table 1). The frequency of internal hydrogen bonds in the starting structure (SFTI-FCQR Asp14) was only slightly above the median. Further, modifying residue 14 had a considerable effect on the internal hydrogen bond network across the nineteen SFTI-FCQR variants, ranging from 2.2860.07 (His14) to 4.2960.31 (Asn14) average hydrogen bonds. In contrast, these substitutions had little effect on the number of intermolecular hydrogen bonds, producing a slight decrease for the majority of variants. To verify these in silico results, six variants representative of the diverse residue side chains and the number of hydrogen bonds were synthesised: Asn14 (amide), Tyr14 (aromatic), Lys14 (basic), Gly14 (flexible), Ala14 (less flexible) and Ser14 (alcohol). These were screened against KLK4 in vitro to determine respective inhibition constants (Table 2). SFTI-FCQR Asn14, predicted to have the most internal hydrogen bonds, was also the most potent KLK4 inhibitor with PLoS ONE | www.plosone.org

a Ki of 0.038660.0060 nM, exceeding that of SFTI-1 for trypsin (Ki = 0.1 nM). Furthermore, there was a consistent correlation between increasing number of internal hydrogen bonds during MD simulation and decreasing inhibition constants in vitro (Figure 3). However, it should be noted that SFTI-FCQR Lys14 assays were carried out immediately after addition of inhibitor since this variant was degraded after prolonged incubation with KLK4 (tK = 56.366.2 minutes). This may reflect the introduction of a second potential cut site for trypsin-like proteases (Lys) on the side loop of SFTI. Although the Arg5-Ser6 scissile bond can be cleaved on SFTI without detrimental effect, the side loop does not have the features of a canonical loop and cleavage of the Gly1-Lys14 peptide bond may be irreversible. Examining the internal hydrogen bonding network of SFTIFCQR Asn14 revealed that substitutions at position 14 influenced their frequency and distribution across the entire scaffold (Figure 1C). In the side loop, the Asn14 side chain formed 5

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Table 1. In silico Internal Hydrogen Bond Analysis of SFTI-FCQR Residue 14 Variants.

SFTI variant

Internal Hydrogen Bonds (Mean ± SEM)

% Change from SFTI-FCQR Asp14

Intermolecular Hydrogen Bonds (Mean ± SEM)

% Change from SFTI-FCQR Asp14 2.1

SFTI-FCQR Asn14

4.6860.086

26.5

8.4660.10

SFTI-FCQR Val14

4.2660.14

15.1

8.1760.18

0.1

SFTI-FCQR Tyr14

4.0760.24

9.9

8.2260.30

20.7

SFTI-FCQR Met14

3.9860.12

7.6

8.1160.20

22.0

SFTI-FCQR Lys14

3.9160.47

5.6

8.1160.17

22.1

SFTI-FCQR Phe14

3.8960.15

5.1

7.5860.08

28.5

SFTI-FCQR Ile14

3.8560.43

4.2

7.3060.35

211.8

SFTI-FCQR Asp14

3.7060.11

0

8.2860.19

0

SFTI-FCQR Gly14

3.6760.30

20.9

7.8660.17

25.1

SFTI-FCQR Pro14

3.6660.43

21.0

6.4960.23

221.7

SFTI-FCQR Glu14

3.5960.50

23.0

7.8360.36

25.5

SFTI-FCQR Arg14

3.5160.51

25.1

7.6560.04

27.6

SFTI-FCQR Gln14

3.3660.25

29.2

7.5260.14

29.2

SFTI-FCQR Leu14

3.3360.26

210.0

8.1160.17

27.7

SFTI-FCQR Trp14

3.1260.22

215.6

7.9260.36

24.3

SFTI-FCQR Thr14

2.9360.093

221.0

7.3460.06

211.3

SFTI-FCQR Ala14

2.8960.085

221.8

7.2560.16

212.4

SFTI-FCQR Ser14

2.5660.048

230.8

7.5260.10

29.1

SFTI-FCQR His14

2.2860.068

238.2

8.07 6 0.11

22.5

doi:10.1371/journal.pone.0019302.t001

Table 2. Inhibitory Properties of SFTI-1, SFTI-FCQR and SFTI-FCQR Residue 14 Variants.

Enzyme KLK4

KLK14

b-Trypsin

Matriptase

Thrombin

Chymotrypsin

Inhibitor

IC50 (nM)

Ki (nM)

Morrison Ki (nM)

Theoretical Mass

Determined Mass

Substrate (100 mM) FVQRpNA

SFTI-FCQR Asn14

0.063560.0024

-

0.038660.0060

1559.75

1560.40

SFTI-FCQR Tyr14

3.476 0.20

-

2.5560.43

1610.77

1610.56

SFTI-FCQR Lys14

6.0760.13

-

3.5660.27

1573.80

1574.93

SFTI-FCQR Asp14

7.9761.08 [16]

3.6260.26

3.8960.40

1560.73

1559.94

SFTI-FCQR Gly14

14.7461.089

-

10.3962.87

1502.73

1504.77

SFTI-FCQR Ala14

26.2360.85

-

18.316 3.36

1516.74

1517.99

SFTI-FCQR Ser14

29.2361.081

-

21.24 63.81

1532.74

1533.94

SFTI-1

221610.1 [16]

-

-

1514.75

1514.84

SFTI-FCQR Asp14

1506637.1 [16]

-

-

-

-

SFTI-FCQR Asn14

2516 21.9

-

-

-

-

Ac-GSLR-pNA

SFTI-FCQR Asp14

40646109 [16]

-

-

-

-

SFTI-FCQR Asn14

21786145

-

-

-

-

SFTI-1

-

0.1 [17]

-

-

-

SFTI-FCQR Asn14

.10,000

-

-

-

-

Bz-FVRpNA

SFTI-1

-

0.92 [19]

-

-

-

N-t-Boc-QAR-AMC

BAPNA

SFTI-FCQR Asn14

.10,000

-

-

-

-

Bz-FVRpNA

SFTI-1

-

5050 [19]

-

-

-

N-t-Boc-LRR-AMC

SFTI-FCQR Asn14

.10,000

-

-

-

-

WpNA

SFTI-1

-

23006100 [51]

-

-

-

N-succinylAAPPpNA

Amino acids are represented by the one letter code. doi:10.1371/journal.pone.0019302.t002

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Figure 3. Relationship between Ki and number of internal hydrogen bonds. Plot of the average number of internal (circles), intermolecular (squares) and total (triangles) hydrogen bonds of SFTIFCQR variants (Asn14, Tyr14, Lys14, Asp14, Gly14, Ala14 and Ser14) from Table 1 versus Morrison Ki values from Table 2. doi:10.1371/journal.pone.0019302.g003

hydrogen bonds with the backbone amides of Phe2 and Gly1 with similar prevalence as seen for corresponding residues in SFTI-1. In comparison to SFTI-FCQR Asp14, the hydrogen bonds between Phe2-Phe12 and Gly1-Phe12 were similarly frequent while a further hydrogen bond was prevalent between the backbone amide of Asn14 and the carbonyl oxygen of Phe12. Overall, it appeared that changes in the hydrogen bonding pattern in the side loop of SFTI-FCQR Asn14 restored the frequency of the hydrogen bonds in the reactive loop to the level determined for SFTI-1. A previous study also reported that hydrogen bonds of the side loop, in particular the one formed between carboxylic oxygen of Asp14 and the Gly2 amide, were necessary to provide rigidity to the SFTI-1 reactive loop [20]. Consequently, this resulted in a reactive loop that closely aligned with the SFTI-1 starting structure both in terms of conformation (Figure 2A) and structural stability (Figure 2B and C). Consistent with a highly rigid scaffold, koff was found to be 0.03160.010 s-1 with a calculated second order rate constant (koff/Ki) of 8.036108 M21 s21 (Figure 4), suggesting that SFTI-FCQR Asn14 binding to KLK4 is diffusion controlled. Collectively, these findings indicate that residue 14 of the side loop is instrumental for maintaining conformational stability of the SFTI reactive loop, a requirement for potent standard mechanism inhibition.

SFTI-FCQR Asn14 is a selective KLK4 inhibitor

Figure 4. Assessment of koff for SFTI-FCQR Asn14. Lag phases and steady state for inhibitor binding to KLK4: (A) uninhibited reaction progress (B) simultaneous addition of substrate and inhibitor (C) preformed enzyme inhibitor complex. The koff rate was calculated graphically from the absolute difference between the steady states at y = zero. Rates shown are the average of three independent experiments. doi:10.1371/journal.pone.0019302.g004

Screening SFTI-FCQR Asn14 against a panel of serine protease targets revealed that this variant was more selective than SFTIFCQR Asp14. The most closely related enzyme to KLK4 is ˚ of the catalytic KLK14 with 85% sequence identity within 5 A triad, while trypsin is a high affinity target for SFTI-1. Although SFTI-FCQR Asn14 more potently inhibited KLK14 and trypsin, the relative increase in inhibition was only six-fold and two-fold respectively, compared to 125-fold improvement for KLK4 (Table 2). This likely reflects that increasing hydrogen bonds, and therefore binding loop rigidity, produces a more potent inhibitor in general. Matriptase, thrombin and a-chymotrypsin which are also inhibited by SFTI-1, showed no inhibition with SFTI-FCQR Asn14 at 10,000 nM. PLoS ONE | www.plosone.org

Further, it has been demonstrated that amidolytic inhibition of a small peptide substrate does not necessarily equate to proteolytic inhibition. For example, SFTI-1 inhibits KLK4 in amidolytic assays (IC50 = 221610.1 nM) but not in fibrinogen digestion assays with 2 mM inhibitor [16]. Consequently, the ability of 7

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SFTI-FCQR Asn14 to inhibit proteolysis of fibrinogen by KLK4, KLK12, KLK14 and trypsin was assessed. KLK4 proteolysis was blocked at inhibitor concentrations as low as 62.5 nM for SFTIFCQR Asn14 compared to 250 nM for SFTI-FCQR Asp14, with

more robust inhibition of degradation of the KLK4-preferred fibrinogen a-chain (Figure 5A–B). No inhibition of KLK12, KLK14 or trypsin fibrinogen proteolysis by SFTI-FCQR Asn14 occurred up to 10,000 nM (Figure 5C–F).

Figure 5. Selective inhibition of serine protease proteolytic activity by SFTI-FCQR Asn14. Examination of fibrinogen proteolysis by trypsin and kallikreins by SDS-PAGE. Bands were visualised with Coomassie blue staining after resolving on 10% polyacrylamide gels. Images are representative of three separate experiments. Inhibition of KLK4 proteolytic activity by (A) SFTI-FCQR Asp14 and (B) SFTI-FCQR Asn14. Inhibition of trypsin proteolytic activity by (C) SFTI-1 and (D) SFTI-FCQR Asn14. Inhibition of proteolytic activity of (F) KLK12 and (F) KLK14 by SFTI-FCQR Asn14. doi:10.1371/journal.pone.0019302.g005

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samples taken over time were quantified by LC-MS. Orally delivered SFTI-FCQR Asn14 did not result in detectable levels of inhibitor in serum. In contrast IV and IP administered SFTIFCQR Asn14 at a dosage of 3 mg/kg had a serum half-life of 25– 28 mins with a residual inhibition concentration of 10.060.8 nM after 4 hours irrespective of delivery route (Figure 7).

SFTI-FCQR Asn14 is stable in culture with prostate cancer cells Previous evaluation of SFTI-FCQR Asp14 stability in culture with prostate cancer cells revealed that it was highly resistant to breakdown [16]. Whether replacing Asp14 with Asn markedly altered inhibitor stability in a cellular environment was assessed by calculating the half-life of SFTI-FCQR Asn14. Additionally, the SFTI-FCQR Lys14 half-life was determined given that this variant seemed to be degraded in competitive kinetic assays (see above). For SFTI-FCQR Asn14, inhibition of KLK4 gradually declined over time indicating a slow rate of decay that was comparable across each cell line (figure 6A). Despite an average reduction in stability compared to SFTI-FCQR Asp14, a half-life 55–70 hours is still well above the expected clearance time for peptide-based therapeutics in vivo. Further, in agreement with previous observations, SFTI-FCQR Lys14 was rapidly degraded with twothirds of the initial activity lost within the first 24 hr (figure 6B).

Discussion This study has shown that when re-engineering a canonical serine protease inhibitor preserving binding loop rigidity and conformation is essential to maintain high binding affinity. Indeed, inhibitor variants with more frequent internal hydrogen bonds in silico correlated with more potent inhibition in vitro, emphasising their role in tight binding complexes. This guided production of an inhibitor with 125-fold improved potency for KLK4 and enhanced selectivity over off-target proteases, including closely related KLKs. Further, SFTI-FCQR Asn14 was stable in a cancer cell milieu and bioavailable by intraperitoneal perfusion in mice, making it an attractive candidate for further therapeutic development. The suitability of SFTI as a generic scaffold for inhibitor design and its properties for maintaining structural integrity within a cell environment have previously been discussed in detail [4,16]. Although SFTI-FCQR Asn14 was less stable than SFTI-FCQR Asp14 in culture with prostate cancer cells, it was sufficiently resistant to degradation, highlighting the robustness of the SFTI scaffold. The fact that SFTI-FCQR Asn14 was also bioavailable by IP indicates that the inhibitor had the ability to diffuse across tissues in vivo. This suggests that using a slow release depot implant is a viable mode of delivery. Alternatively there are numerous methods available for improving the retention of peptide drugs as previously reviewed [4]. Most notably, MD analysis indicated that Ile10 did not make contact with KLK4 and is positioned to provide an anchoring point for PEGylation [46] unlikely to markedly affect inhibitory properties.

SFTI-FCQR Asn14 is bioavailable in mice when administered by intraperitoneal perfusion While other BBIs are readily bioavailable [45] whether this applies to SFTI-1 or previously produced variants is yet to be determined. To establish the pharmacokinetic profile of SFTIFCQR Asn14, the inhibitor was delivered via intravenous (IV), intraperitoneal (IP) and oral routes to BALB/c mice before serum

Figure 6. Stability of SFTI variants in contact with prostate cancer cells in vitro. Residual activity of (A) SFTI-FCQR Asn14 and (B) SFTI-FCQR Lys14 in cell culture media from prostate cancer cells treated with a single dose of inhibitor. Endogenous inhibitors were removed by boiling and centrifugation. Stability was assessed against LNCaP (closed circles), 22Rv1 (triangles), and PC3 cells (open circles). Data are mean 6 SEM from three experiments in triplicate. doi:10.1371/journal.pone.0019302.g006

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Figure 7. Bioavailability of SFTI-FCQR Asn14 in mice. Serum levels of SFTI-FCQR Asn14 administered at 3 mg/kg via the intravenous (IV), intraperitoneal (IP) routes in mice. Serum half life was 25-28 minutes with 10.060.8 nM inhibitor serum levels at 4 hours. The data is expressed as mean 6 SEM (IV, n = 3; IP, n = 2). doi:10.1371/journal.pone.0019302.g007

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Producing potent and selective standard mechanism inhibitors depends on fully realizing the highly conserved and successful structural features of the canonical loop. These inhibitors share two important properties. First, their reactive sites occur in constrained binding loops with similar structure and conformation [25]. Second, rigidity is maintained by intrinsic structural determinants allowing for positioning the P19 free amine for peptide bond reformation after the scissile bond is cleaved [30,31]. Structural comparison delineates 19 families of inhibitors (I1-I3, I7, I8, I10-13, I15-20, I36 and I40) that belong to 13 clans comprising distinct protein folds and evolutionary origins [25]. The fact that the conformation of the canonical binding loop has evolved numerous times independently highlights its versatility as a starting structure for inhibitor design. However, whilst most tight binding standard mechanism inhibitors with large, flexible contact surfaces are slow binding, the SFTI scaffold is reduced to a simple canonical loop allowing for both fast and tight binding. Strategies to re-engineer serine protease inhibitors commonly focus on the active site binding b-sheet of the canonical loop. The previous production of a selective KLK4 inhibitor utilised this approach by grafting a preferred substrate sequence into the bsheet of SFTI-1 [16]. While the importance of canonical loop rigidity is well appreciated in naturally occurring structures, it has not received similar attention when modifying these inhibitors for new targets. The present study focused on restoring the internal hydrogen bonding network of the SFTI scaffold, generating an inhibitor with considerably increased affinity. Indeed, modifications of residue 14 that enhanced internal hydrogen bonding increased potency of inhibition across all variants assayed in vitro. This may also explain the modest increase in affinity for trypsin and KLK14 by SFTI-FCQR Asn14. Consistent with the importance of residue 14 to hydrogen bonding, a previous study found that substituting Asp14 for Ala in SFTI-1 resulted in a marked reduction in potency for trypsin [47]. Thus two complementary strategies for enhancing inhibitor performance are evident; re-engineering the active site binding b-sheet of SFTI is instrumental in achieving selectivity while modulating the internal hydrogen bonding network engenders increased potency. Bringing these two components together in SFTI-FCQR Asn14 resulted in an inhibitor rivalling SFTI-1 in terms of potency without its promiscuity. The findings presented here are in agreement with a previous in silico study on SFTI-1 using graph representation [48] to analyse how various internal hydrogen bonds contribute to structural rigidity [20]. Similarly, it was observed that the hydrogen bonds within the side loop were important for maintaining rigidity of the SFTI-1 reactive loop. The strongest contribution was conferred by the hydrogen bonding pairs of Asp14-Gly1 followed by Phe12-Gly1

and Phe12-Arg2. Although the findings from both studies closely align, graph representation is confined to structurally determined hydrogen bonding patterns. As a result, hydrogen bonds are either present or absent, preventing prediction of how subtle changes in these patterns and frequencies will affect binding affinities. The prominent role of internal hydrogen bonding in maintaining canonical loop rigidity is not only limited to the SFTI scaffold. The same study by Costa and co-workers showed that hydrogen bonds are vital for stabilising the binding loop for BBIs (Family I12) in general [20]. Further, studies on Eglin C (Family I13) assessed point mutations by NMR and competitive binding assays, highlighting the relationship between inhibition constants and hydrogen bonds within the binding loop [49]. In fact the importance of the internal hydrogen bonding network in maintaining the conformation of the canonical loop has been demonstrated structurally across most families of standard mechanism inhibitors [50]. Preservation of these interactions is a key, yet often overlooked, property to consider when reengineering this class of inhibitors. In contrast to small-molecule inhibitors with few rotational bonds, conventional docking and scoring of protein-based inhibitors and their receptors have markedly lower rates of success [32]. The alternative is to calculate average binding affinities across MD trajectories including conformations of many low energy-state complexes [32]. These methods fail to recapitulate the most important aspect of standard mechanism serine protease inhibitors: the conformation and rigidity of the canonical loop before and after cleavage of the scissile bond as well as during the acyl-enzyme intermediate. Therefore, it is more effective to use computer-aided design methods to optimize structural features supporting the binding loop conformation to more closely replicate the native starting structure. This study focused on analysing one of these intrinsic canonical loop properties, namely hydrogen bonds, to accurately predict relative binding affinities of SFTI variants. We suggest that this simple approach is generally applicable as a tool to enhance binding affinity when reengineering standard mechanism inhibitors. Used in conjunction with traditional peptide library screens to sample protease subsite preferences, this strategy is likely to produce both highly selective and potent inhibitors.

Author Contributions Conceived and designed the experiments: JES SJdV CFR JMH. Performed the experiments: JES SJdV KCS. Analyzed the data: JES SJdV JMH. Contributed reagents/materials/analysis tools: AMB JMH. Wrote the paper: JES SJdV AMB JMH.

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CHAPTER 5

Optimal Subsite Occupancy and engineering of Internal Hydrogen Bonds within the Sunflower Trypsin Inhibitor (SFTI) Enables Potent Inhibition of Kallikrein-Related Peptidase 14 (KLK14)

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Optimal Subsite Occupancy and engineering of Internal Hydrogen Bonds within the Sunflower Trypsin Inhibitor (SFTI) Enables Potent Inhibition of Kallikrein-Related Peptidase 14 (KLK14)

de Veer, S.J., Swedberg, J.E., Parker, E.A., Harris, J.M. Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland 4059, Australia *Corresponding author: [email protected]

Abstract Human skin forms a vital protective frontier for the body against physical, chemical and microbial assault. The kallikrein related peptidases play an important, but incompletely understood role in the maintenance of this barrier. In this study, inhibitors for the skinexpressed kallikrein KLK14 were constructed using substrate-guided and computer-aided design methods. Firstly, broad subsite preferences indicated by positional scanning were resolved by a non-combinatorial substrate screen to determine the refined substrate specificity of KLK14. The optimal substrate, Ac-YASR-pNA, was hydrolysed with a higher kcat/Km than substrates predicted by positional scanning. Substitution of this peptide sequence and related sequences into the contact β-sheet of the naturally occurring sunflower trypsin inhibitor (SFTI) produced potent KLK14 inhibitors. Molecular dynamic simulations of these inhibitors in complex with KLK14 indicated that substitutions within the inhibitor’s contact β-sheet had disrupted the molecule’s internal hydrogen bond network. Restoration of critical internal hydrogen bonds produced a 13-fold increase in potency and yielded a second generation KLK14 inhibitor with a Ki of 1.46 ± 0.13 nM. This

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inhibitor will be a vital tool in further investigations into the synergistic relationship between skin-expressed kallikreins and pathophysiological processes such as aberrant desquamation and skin barrier failure. Depending on the deconvolution of the roles of individual kallikreins, a KLK14 inhibitor may also be an important therapeutic lead compound.

Key words: Inhibitor; Kallikrein; SFTI; KLK14; Protease; Positional scanning; peptide library

Introduction As the interface between the human body and the external environment, the skin forms an essential protective barrier. Maintenance of epidermal integrity is reliant on the activity of skin-expressed proteases which contribute several important functions. Best established is the role of proteases in desquamation, the process by which corneocytes at the apical surface are progressively shed by proteolysis of desmosomal cell-cell contacts (Egelrud et al. 1988; Lundstrom and Egelrud 1988). Proteases also process pro-form protein substrates into functional monomers, such as filaggrin (List et al. 2003) and cathelicidin antimicrobial peptides (Yamasaki et al. 2006). Finally, proteases are capable of modulating keratinocyte function through intracellular signalling mediated by protease-activated receptors (PARs), particularly PAR-2 which is associated with inflammation, initiation of immune responses, pruritus and nociception (Steinhoff et al. 2005). The epidermis is a rich source of kallikrein-related peptidases (KLKs), a highly conserved multi-gene family encoding fifteen serine proteases with either trypsin- or chymotrypsin-like activity (Borgono and Diamandis 2004; Clements et al. 2004). Eight KLKs are expressed at varying levels within the uppermost layer of the epidermis, the stratum corneum (KLK5-8, 10-11, 13-14) (Komatsu et al. 2006), four of which have been detected in active form: KLK5 (Hansson et al. 1994), KLK7 (Brattsand and Egelrud 1999), KLK8 (Kishibe 131

et al. 2007) and KLK14 (Stefansson et al. 2006). Similar to other physiological processes mediated by proteolytic activity, the KLKs expressed within the skin are proposed to function in a protease activation cascade (Caubet et al. 2004; Brattsand et al. 2005). However, the significance of individual KLKs and how they combine remains to be precisely defined. An additional layer of complexity has been added by very recent studies revealing KLKs can be activated by matriptase (Sales et al. 2010) and meprin metalloproteases (Ohler et al. 2010), suggesting that the putative epidermal protease cascade(s) extend beyond KLK proteases alone. Epidermal proteolysis requires exquisite regulation. Endogenous control of active KLKs is provided by broad range inhibitors such as lympho-epithelial Kazal-type inhibitor (LEKTI, Spink5) (Magert et al. 1999) and related inhibitors with more specific inhibition profiles including LEKTI2 (Spink9) (Brattsand et al. 2009; Meyer-Hoffert et al. 2009) and Spink6 (Meyer-Hoffert et al. 2010). However, an imbalance between proteolysis and inhibition contributes to several skin pathologies as exemplified by Netherton syndrome, an autosomal recessive disease produced by the loss of function mutation in LEKTI (Chavanas et al. 2000). The result is a disfiguring condition characterised by severely peeled, dehydrated and inflamed skin due to over-digestion of desmosomal cadherins (Descargues et al. 2005) and activation of PAR-2 (Briot et al. 2009). In rosacea, elevated KLK expression facilitates overaccumulation of cathelicidin peptides (Yamasaki et al. 2007); an established avenue to activation of the immune system via tissue-resident dendritic cells (Lande et al. 2007). Abnormal LEKTI function, coupled with dysfunctional protease activity, is also implicated in atopic dermatitis and eczema (Komatsu et al. 2007; Voegeli et al. 2009). Here, weakening of the epidermal barrier leaves the skin susceptible to infection, allergens and dehydration. Therefore, targeted inhibition of key KLKs within the skin is a potential strategy for alleviating these symptoms. However, there are currently no potent small molecule inhibitors for these enzymes. 132

A potent and selective KLK inhibitor has previously been produced for the related protease, KLK4, based on the naturally occurring sunflower trypsin inhibitor (SFTI). SFTI is a fourteen amino acid cyclic peptide consisting of two anti-parallel β-sheets stabilised by a bisecting disulfide bond and an extensive network of internal hydrogen bonds (Luckett et al. 1999). The strategy to engineer SFTI followed a two-phase approach. Firstly, selectivity was achieved by grafting an optimal substrate from a sparse matrix peptide library screen onto the contact β-sheet of the SFTI scaffold (Swedberg et al. 2009). Secondly, the potency of the engineered variant was improved by optimising the internal hydrogen bond network using amino acid substitutions guided by molecular dynamics simulations (Swedberg et al. 2011). This study utilises a similar approach to the rational design of KLK14 inhibitors. Screening KLK14 against a positional scanning synthetic combinatorial library of peptides, was used to outline approximate substrate preferences. Subsequently, the extended substrate specificity of KLK14 was fully defined using a non-combinatorial peptide library that revealed that subsite cooperativity occurred for KLK14 substrate recognition. Peptides that included these cooperativity features were cleaved with high efficiency. Substituting these sequences into the contact β-sheet of the SFTI produced a potent inhibitor that showed selectivity over the other serine proteases KLK5, trypsin and matriptase but not KLK4. Finally, molecular dynamics analysis was used to optimise the internal hydrogen bond network of SFTI variants and produced a second generation KLK14 inhibitor with a Ki of 1.46 ± 0.13 nM.

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Methods and Materials

Reagents Recombinant human KLK5, KLK7 and matriptase were obtained from R&D Systems, while bovine β-trypsin and human fibrinogen were obtained from Sigma-Aldrich. All synthesis reagents were obtained from Auspep Pty Ltd and all solvents from Merck Pty Ltd unless stated otherwise.

Production of recombinant KLK4 and KLK14 KLK4 and KLK14 were produced in stably transfected Sf9 insect cells according to Ramsay et al. (Ramsay et al. 2008) and Swedberg et al. (Swedberg et al. 2009) respectively. Pro-KLKs were purified from conditioned culture supernatant by Ni-NTA superflow agarose (Qiagen) according to the manufacturer’s instructions and stored at -80oC. Protease expression and purity were confirmed by Western blot analysis (against the poly-His epitope) and Coomassie stained SDS-PAGE respectively. For activation, pro-KLKs were incubated with thermolysin (R&D Systems) at 37oC, after which, thermolysin was inhibited with 25 mM EDTA. The concentration of mature KLKs was determined by active site titration with 4methylumbelliferyl-p-guanidinobenzoate hydrochloride (MUGB, Sigma-Aldrich).

Synthesis of peptide substrate libraries Peptide para-nitroanilide (pNA) substrates were synthesised on 2-chlorotrityl resin (0.13 mmol/g) derivatised with para-phenylenediamine (Sigma-Aldrich) as previously described (Abbenante et al. 2000). For individually synthesised substrates, peptide elongation was achieved with 4 eq. 9-fluorenylmethyl carbamate (Fmoc) protected amino acids dissolved in 0.25 M each of 1-hydroxybenzotriazole (HOBt), 2-(1H-benzotriazole-1-yl)-1,1,3,3tetramethyluronium hexafluorophosphate (HBTU) and N,N-diisopropylethylamine (DIPEA) 134

in N,N-dimethylformamide (DMF) for 1 hour. For the P1-P4 diverse combinatorial library, amino acid coupling for fixed positions occurred as above while degenerate positions were synthesised using a two-step limited loading approach given the widely varying reaction rates of individual amino acids (Boutin et al. 1997). Degenerate positions were firstly coupled using an equimolar concentration of mixed amino acids totalling the molar loading capacity of the resin followed by a second round of coupling with 4 eq. amino acids to ensure occupancy at all available sites. Fmoc deprotection was achieved using 50% piperidine and 5% 1,8-diazabicyclo [5.4.0]undec-7-ene (DBU) in DMF for 10 min. Fully protected peptides were cleaved from the solid support by successive changes of 1% trifluoroacetic acid (TFA) in dichloromethane (DCM) followed by ether precipitation and oxidation using 8 eq. Oxone® (Sigma-Aldrich) dissolved in 50% acetonitrile in H2O for 16 hours (Abbenante et al. 2000). This also resulted in oxidation of unprotected methionine side chains. Protecting groups were removed from the dry product by cleavage for 2 hours in 95% TFA, with scavengers; 1.25% triisopropylsilane (TIS, Sigma-Aldrich), 1.25% H2O and 2.5% thioanisole (Sigma-Aldrich). Peptides were precipitated in diethyl ether, lyophilised and stored at -80oC. Substrates for Michaelis-Menten kinetic analysis and inhibition assays were purified by reverse phase high-performance liquid chromatography (rp-HPLC) across a gradient of 10-100% isopropanol containing 0.1% TFA using a Jupiter 4µ Proteo 90A C-18 column (Phenomenex). This was followed by MALDI-TOF/MS validation for purity and correct mass.

Positional scanning-substrate combinatorial library (PS-SCL) analysis Substrate pools were solubilised in 50% isopropanol at 3.75 mM (by average pool molecular weight). Assays were carried out in 96 well transparent non-binding plates (Corning) using 250 µl KLK14 assay buffer (0.1 M Tris-HCl, 0.1 M NaCl, 25 mM EDTA, 0.005% Triton X-100) containing 150 µM substrate and 7.5 nM KLK14. Additionally, 10% isopropanol was 135

included in the assay buffer to aid substrate solubility. Activity was measured by the change in absorbance at 405 nM for 5 min using a Biorad Benchmark Plus multi-well spectrophotometer. Data represent the mean rate ± SEM from three independent assays carried out in triplicate.

Sparse matrix substrate screen Individually synthesised substrates were solubilised in 40% isopropanol and adjusted to apparent equal molarity by overnight cleavage of the pNA moiety (Swedberg et al. 2009). The sparse matrix substrate screen was carried out as for PS-SCL analysis with the exception that 250 µM substrate and 5 nM KLK14 were used, assay buffer did not contain isopropanol and assays proceeded for 7 min. Data represent the mean rate ± SEM from three independent assays carried out in triplicate. The four substrates cleaved at the highest rate and two substrates predicted from PS-SCL analysis were purified by rp-HPLC and subjected to Michaelis-Menten kinetic analysis. A constant concentration of KLK14 (0.7 nM) was assayed against serial dilutions of purified substrates (600 µM – 18.75 µM) over three independent assays (7 min) carried out in triplicate. Kinetic constants (Vmax and Km) were determined by non-linear regression in GraphPad Prism 5. These were subsequently used to calculate kcat and kcat/Km for each substrate.

Solid phase synthesis of SFTI-variants Inhibitors were synthesised as linear peptides on 2-chlorotrityl resin using a Discover SPS Microwave System (CEM Corporation). Resin was firstly derivatised with 2 eq. Fmoc-Ser (30 min, 75oC, 20 W). The following nine residues were coupled according to the manufacturer’s recommendations (7 min, 75oC, 20 W) using 5 eq. Fmoc-protected amino acids and 125 mM HBTU were dissolved in DMF containing 5% DIPEA. Cysteine residues 136

were coupled at 50oC to reduce racemisation. After each coupling, the Fmoc protecting group was removed by incubation in 50% piperidine in DMF (3 min, 75oC, 20 W). The final four residues were coupled for 10 min and deprotected for 4 min to circumvent aggregation. Assembled linear peptides were liberated from the resin by successive changes of 0.5% TFA in DCM at room temperature and collected in 10 volumes of diethyl ether. Microwave-assisted head-to-tail cyclisation occurred in solution using 125 mM each of 1hydroxy-7-aza-benzotriazole (HOAt) and benzotriazol-1-yl-oxytripyrrolidinophosphonium hexafluorophosphate (PyBOP) dissolved in DMF containing 5% DIPEA. Cyclisation proceeded for 30 min (20 W, 65oC). Extraction of peptides, cleavage of side chain protecting groups, purification from remaining synthetic by-products and formation of the internal disulfide bond were carried out as previously (Swedberg et al. 2011). Completed SFTI variants were purified by rp-HPLC (as above), lyophilised and stored at -80oC.

Inhibition assays Serial dilutions of SFTI variants were assayed against 1 nM KLK14 and 120 µM Ac-YANR-pNA in 250 µl assay buffer with activity of uninhibited enzyme measured by the change in absorbance at 405 nm over 7 min. IC50 and Morrison Ki values were determined using GraphPad Prism 5. Fibrinogen proteolysis assays were used to assess selectivity of initial SFTI variants. Digestions were carried out using 7 µM fibrinogen in 20 µl assay buffer at 37oC. Varying incubations were required given the differing efficiencies of each protease (KLK4: 90 min, 0.1 M Tris-HCl, pH 7.4, 0.1 M NaCl, 25 mM EDTA, 0.005% Triton X-100; KLK5: 4 hr, 0.1 M Tris-HCl pH 8.0, 0.1 M NaCl, 25 mM EDTA, 0.005% Triton X-100; KLK14, 1 hr, 0.1 M Tris-HCl pH 8.0, 0.1 M NaCl, 25 mM EDTA, 0.005% Triton X-100; trypsin, 30 min, 0.1 M Tris-HCl pH 8.0, 0.1 M NaCl, 10 mM CaCl2, 0.005% Triton X-100; matriptase, 3 hr, 0.1 M TrisHCl pH 8.5, 0.1 M NaCl, 0.005% Triton X-100). At the digestion end point, protease activity 137

was terminated by boiling in reducing SDS-PAGE loading buffer. Proteolysis fragments were resolved by SDS-PAGE on 10% acrylamide gels and visualised by Coomassie R-250 stain.

Molecular dynamics simulations of KLK14-inhibitor complexes Since the structure of KLK14 remains to be solved, a homology model was created with the SWISS-MODEL (Guex et al. 2009) using KLK5 as a template (PDB ID 2PSY). SFTI residue 12 variant/KLK14 complexes were generated by an overlay of the KLK14 model and the trypsin/SFTI-1 complex (PDB ID 1SFI) in SPDBV v4.01 (RSMD 0.96 Å) (Guex et al. 2009) before amino acid substitutions in YASARA Dynamics 9.12.13 (Krieger et al. 2002). Complexes were solvated, neutralised, equilibrated and simulated as described previously (Swedberg et al. 2011) with the exception that the three independent production runs of 1 ns were carried out in NAMD 2.6 (Phillips et al. 2005) using the same parameters. Coordinates were saved every 100 simulation steps producing 5000 frames per run. Hydrogen bond analysis was performed using VMD 1.8.7 (Humphrey et al. 1996) with hydrogen bond lengths and angles set to 3.3 Å and 40° respectively.

Results

Positional scanning analysis does not yield a definitive subsite profile for KLK14 Design of protease inhibitors requires a comprehensive understanding of how high affinity determinants are distributed within the active site. The peptide substrate specificity of KLK14 has previously been investigated using a positional scanning synthetic combinatorial library (PS-SCL) (Borgono et al. 2007). Applying this method to other KLKs (Matsumura et al. 2005; Debela et al. 2006; Borgono et al. 2007) has yielded conflicting results, suggesting that more than one PS-SCL screen is necessary to ensure identification of all preferred

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residues. Consequently, a P1-P4 diverse PS-SCL was synthesised with a para-nitroanilide (pNA) reporter group and included all naturally occurring amino acids. Screening KLK14 against the combinatorial library suggested a substrate preference that differed from previous findings for certain subsites. KLK14 displayed a dominant preference for P1 Arg, although cleavage of other residues was higher than previously reported (Figure 1). Furthermore, KLK14 showed a particular P2 site preference for Ser followed by Val, Cys and Asn, indicating both polar and hydrophobic residues were tolerated at this position. This deviated from previous results where Asn and Ala were predicted to be equally favoured with Ser. For the KLK14 S3 site, a noticeable partiality for hydrophobic residues such as Val and Leu was evident in contrast to Lys and Ala suggested by the earlier study. Finally, KLK14 displayed an equivalent preference at S4 for Tyr and Trp in this study rather than Tyr only as previously suggested. The lack of concordance between

Figure 1: Positional scanning screen of the extended substrate specificity of KLK14. Relative activity of KLK14 against combinatorial pools of peptides. The 80 peptides pools each included one of the 20 naturally occurring amino acids fixed at either of the P1-P4 positions while all other protein binding sites contained a mixture of all residues. The fixed residue is shown at the x-axis in one letter amino acid code, with M* being methionine sulfone. Data is shown as mean ± SEM from three independent experiments.

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the two PS-SCL screens may be a consequence of different synthesis methods resulting in varying representation of certain sequences (Boutin et al. 1997). This suggested that the substrate specificity of KLK14 was not yet fully described.

Non-combinatorial peptide screen defines KLK14 subsite cooperativity Combinatorial libraries are inherently unable to predict substrate subsite cooperativity (Schneider et al. 2009; Swedberg et al. 2009; Swedberg et al. 2010). Consequently, a noncombinatorial sparse matrix library (SML) of peptides was synthesised which combined preferred residues from both PS-SCL screens at each position. The data from assays of these substrates against KLK14 aligned with the PS-SCL specificities in this study regarding the P4 and P2 sites. Tyr and Trp appeared to be similarly preferred at P4 while substrates containing Ser and Val were favoured at P2 compared to Asn (Figure 2). In contrast, the previously reported PS-SCL better described the P3 site since sequences containing Ala at this position were hydrolysed at consistently higher rates. Additionally, several instances of subsite cooperativity were evident that could only be identified from screening a non-

Figure 2: Sparse matrix screen of the extended substrate specificity of KLK14. Activity as mOD/min at 405 nm of KLK14 for individually synthesised peptides selected from PS-SCL screens. The P1 residue was kept constant as Arg while varying the P2 (y-axis) and P4-P3 (x-axis) residues. M* represents methionine sulfone. Data is expressed as mean ± SEM from three independent experiments.

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combinatorial library. Val at the P3 site consistently resulted in a P4 preference for Trp. Similarly, when Ala occupied P3, substrates containing Tyr were always cleaved with the highest rate irrespective of the P2 residue. This is likely to explain why the four most rapidly hydrolysed sequences could not have been predicted by either combinatorial library alone. To validate these observations, kinetic constants were determined for preferred substrates from the SML and predicted optimal sequences from both PS-SCLs (Table 1). The substrates hydrolysed at the highest rate in the SML were found to have higher kcat values than substrates suggested to be highly preferred by either of the PS-SCL data sets (Ac-YANR-pNA and Ac-YVSR-pNA). Furthermore, the substrates with the highest kcat values reinforced the subsite cooperativity initially identified in the SML. Replacing Val with Ser at P2 produced an 87% increase in catalytic efficiency (kcat/KM) when substrates contained P4 Tyr (Ac-YAVRpNA to Ac-YASR-pNA) while the same substitution with P4 Trp had virtually no effect (AcWAVR-pNA to Ac-WASR-pNA). The substrate cleaved with the highest efficiency by KLK14 was Ac-YASR-pNA indicated by highest kcat/KM value. Table 1: KLK14 kinetic constants for peptide substrates Determined Mass 670.93

KM (µM)

Vmax (nM s-1)

kcat (s-1)

Ac-YAVR-pNA

Theoretical Mass 669.83

45.01 ± 4.95

65.33

93.33 ± 2.75

kcat/KM (M-1 s1 ) 2.074 x 106

Ac-WAVR-pNA

692.87

693.81

51.54 ± 3.10

68.12

97.31 ± 1.63

1.888 x 10

Ac-YASR-pNA

657.78

658.87

22.03 ± 2.88

58.70

83.85 ± 2.29

3.806 x 106

Ac-WASR-pNA

680.82

681.63

33.64 ± 2.07

44.27

63.24 ± 1.01

1.880 x 10

Ac-YANR-pNA

684.80

685.77

16.78 ± 1.96

37.13

53.04 ± 1.15

3.161 x 106

Ac-YVSR-pNA

685.83

686.88

25.23 ± 3.11

24.20

34.57 ± 0.96

1.370 x 10

Substrate

6

6

6

Rational design of SFTI-variants: engineering the contact β-sheet Previously, it has been shown that high affinity peptide substrates can be grafted onto the contact β-sheet of SFTI to produce inhibitor variants with improved selectivity for a target protease (Swedberg et al. 2009). However, analysis of kinetic constants from preferred KLK14 substrates did not narrow it down to one clear candidate. Therefore, the substrates with the highest kcat (WAVR and YAVR) and the highest kcat/KM (YASR and YANR) were 141

selected to guide inhibitor design. Additionally, Asp14 was replaced with Asn14 since a previous study found that this modification was favoured by KLK14 (Swedberg et al. 2011). The substrate with the highest kcat/Km (YASR) also produced the most potent KLK14 inhibitor, SFTI-YCSR N14 (P4: Arg to Tyr, P2: Thr to Ser, P1: Lys to Arg and Asp 14 to Asn 14: Figure 3) with an IC50 of 8.35 ± 0.82 nM (Table 2). However, there was no consistent relationship between kcat/Km and IC50 for the remaining substrates. Rather, it is more likely that the potency of SFTI-YCSR N14 related to an internal hydrogen bond formed by the hydroxyl group of P2 Ser, similar to that seen for P2 Thr in SFTI-1. Replacing Ser with Val or Asn resulted in a decrease in potency of 8.25 and 14.75 fold respectively, with SFTI-WCVR N14 being the least potent of the four inhibitors (IC50 = 142.9 ± 5.70 nM).

Figure 3: Schematic structure of SFTI-1. Amino acid sequence of the wild type SFTI shown in three letter code. Structurally important features such as the binding loop, side loop, bisecting disulfide bond, β-sheets, scissile bond and the protein binding sites (P4-P2’) are highlighted. Amino

acid

numbering

is

according to convention for SFTI (Luckett et al. 1999).

SFTI-WCVR N14 is the most selective KLK14 inhibitor The primary goal of engineering the contact β-sheet of SFTI is to improve selectivity. Therefore, SFTI-variants were assessed against a panel of related serine proteases including reported high affinity targets of SFTI-1 (trypsin and matriptase), relevant off-target skinexpressed proteases (KLK5 and matriptase) and close relatives of KLK14 (KLK4). Inhibitors were examined in fibrinogen proteolysis assays as inhibition does not necessarily correlate 142

Table 2: KLK14 Inhibition constants for SFTI variants Inhibitor

Determined Mass 1515.07

IC50 (nM)

[S] (µM)

Morrison Ki (nM)

SFTI-1

Theoretical Mass 1513.81

122.5 ± 6.07

120

16.82 ± 1.68

SFTI-WCVR N14

1568.89

1570.86

142.9 ± 5.70

120

19.05 ± 0.98

SFTI-YCNR N14

1560.83

1562.77

123.0 ± 5.50

120

16.56 ± 0.99

SFTI-YCSR N14

1533.80

1535.31

8.34 ± 0.82

120

1.41 ± 0.19

SFTI-YCVR N14

1545.86

1547.47

68.87 ± 4.00

120

9.60 ± 0.74

between peptide and protein substrates for both target and off-target proteases (Swedberg et al. 2009). To be able to evaluate the selectivity of inhibitors with varying affinity for KLK14, the concentration required to completely block KLK14 proteolysis was determined. Inhibitor concentrations for off-target enzymes were always used in the same ratio relative to KLK14. Analysis of protein digestion revealed that inhibitor concentration for complete blockage of KLK14 proteolysis generally followed the respective IC50 values (Figure 4). Additionally, the wild-type inhibitor (SFTI-1) displayed noticeable promiscuity, partially or completely inhibiting fibrinogen proteolysis for all enzymes. However, little effect was seen on matriptase despite a reported Ki of 0.92 nM using a peptide substrate (Long et al. 2001). Within the engineered variants, inhibitors containing P2 Val were the most selective. KLK5 or trypsin were not inhibited by SFTI-WCVR N14 and SFTI-YCVR N14 but were inhibited by both SFTI-YCSR N14 and SFTI-YCNR N14. Absolute selectivity over KLK4 was not attained for any inhibitor although SFTI-WCVR N14 permitted some fibrinogen digestion by this enzyme.

Optimising the SFTI-WCVR N14 internal hydrogen bond network improves inhibitor potency Once the contact β-sheet of SFTI has been suitably modified, the potency of the engineered inhibitor can be improved by optimising the internal hydrogen bond network using molecular dynamics simulations (Swedberg et al. 2011). Since no KLK14 structure is currently available, a homology model was created based on KLK5. Simulations of the

143

Figure 4: Inhibition of serine protease digestion of fibrinogen by SFTI variants. The ability to block KLK4, KLK5, KLK14, trypsin and matriptase digestion of fibrinogen was evaluated resolution of fragments on SDS-PAGE gels for (A) SFTI-1, (B) SFTI-WCVR N14 (C) SFTI-YCNR N14 (D) SFTI-YCSR N14 (E) SFTI-YCVR N14. Concentrations of inhibitor used are shown above digests while the fold change compared to KLK14 is indicated below. Digests are representative from three independent repeats.

KLK14/SFTI-WCVR N14 complex revealed an average 2.75 ± 0.82 internal hydrogen bonds. However, equivalent analyses of the trypsin/SFTI-1 complex produced 7.00 ± 0.07 mean hydrogen bonds (Swedberg et al. 2011), indicating that KLK14 favoured substitutions in the contact β-sheet caused a significant disruption to the internal hydrogen bond network. Examining the simulation trajectories of the KLK14/SFTI-WCVR N14 complex indicated that Phe 12 neither formed a favourable contact with the protease nor contributed to the internal hydrogen bond network. This demonstrated the suitability of Phe 12 as a target for substitution in optimisation of SFTI’s internal hydrogen bond 144

network. Consequently, SFTI-WCVR N14 residue 12 variants containing all naturally occurring amino acids (excluding cystine) were subjected to comparable simulations. Internal hydrogen bond analysis revealed that the SFTI-WCVR N14 starting structure (SFTIWCVR F12 N14) had the third lowest internal hydrogen bonding frequency (Figure 5A). The most extensive internal hydrogen bonding networks were seen for acidic residues, closely followed by small polar residues. Although hydrophobic residues at position 14 affected the number of internal hydrogen bonds in previous simulations (Swedberg et al. 2011), little effect was seen when they were present at position 12.

Figure 5: Average internal hydrogen bonds during molecular dynamics simulations for SFTI-WCVR N14 residue 12 variants. (A) The internal hydrogen bonds were analysed for SFTI-WCVR N14 variants in complex with a homology model of KLK14 during molecular dynamics. The average hydrogen bonds are displayed on the y-axis while residue 12 substitutions are labelled on the x-axis. Data is expressed as mean ± SEM for three independent simulation trajectories. (B) Relationship between IC50 and the number of internal hydrogen bonds: plot of the average number of hydrogen bonds of SFTI-WCVR N14 residue 12 variants (Asn, Thr, Gln and Phe) from Figure 4 versus IC50 values from (A).

In addition to the frequency of internal hydrogen bonds, high potency standard mechanism inhibitors require that they are optimally coordinated within the binding loop. Hydrogen bonds in the binding loop are most important since they contribute to a stabilised acylenzyme intermediate central to the mechanism of SFTI inhibition. Consequently, the 145

Table 3: KLK14 inhibition constants for of SFTI-WCVR N14 residue 12 variants

Inhibitor

Determined Mass 1570.86

IC50 (nM)

[S] (µM)

SFTI-WCVR F12 N14

Theoretical Mass 1568.89

Fold Change

120

Morrison Ki (nM) 19.05 ± 0.98

142.9 ± 5.70

SFTI-WCVR Q12 N14

1549.85

1551.92

64.42 ± 3.82

120

9.02 ± 0.66

2.11

SFTI-WCVR T12 N14

1522.82

1524.04

24.66 ± 1.58

120

3.46 ± 0.28

5.51

SFTI-WCVR N12 N14

1535.82

1537.02

10.28 ± 0.76

120

1.46 ± 0.13

13.05

-

hydrogen bond distribution for selected residues within SFTI was analysed. This revealed that although the Glu 12 variant contained most hydrogen bonds, these mainly occurred in the side loop (Table 3). In contrast, for smaller residues such as Asp and Asn the hydrogen bond network was more evenly distributed across the whole scaffold. In particular, there was an increased prevalence in hydrogen bonds of Ser 6 and Pro 8 which may result in a stable binding loop and therefore more potent inhibitors. To validate these findings, the SFTI-WCVR N14 variants Asn 12, Thr 12 and Gln 12 were produced and screened against KLK14 (Table 4). Increasing number and frequency of internal hydrogen bonds in silico correlated with a higher binding affinity in vitro (Figure 5B) as previously shown for SFTI variants and KLK4 (Swedberg et al. 2011). The most potent variant SFTI-WCVR N12 N14 inhibited KLK14 with a Ki of 1.46 ± 0.13 which is 13-fold more potent than for SFTI-WCVR F12 N14

Table 4: Average internal hydrogen bonds of SFTI-WCVR N14 residue 12 variants Side Loop 11 12 13 14 1 2 3 TOTAL 4 5 Cys Phe Pro Asp Gly Arg Cys Thr Lys WT 0.00 0.51 0.00 1.59 0.40 1.69 0.00 4.19 1.13 0.00 Cys X* Pro Asn Gly Trp Cys Val Arg Asp 0.00 1.14 0.00 0.48 0.18 0.48 0.00 2.28 0.59 0.00 Asn 0.00 1.25 0.00 0.13 0.40 0.74 0.00 2.52 0.55 0.01 Thr 0.00 1.15 0.00 0.04 0.31 0.81 0.00 2.31 0.50 0.00 Glu 0.00 2.00 0.00 0.63 0.47 0.90 0.00 3.99 0.60 0.00 Gln 0.00 1.03 0.00 0.17 0.43 0.45 0.00 2.08 0.44 0.00 Phe 0.00 0.74 0.01 0.04 0.30 0.48 0.00 1.57 0.57 0.00 *variable residue as in the leftmost column; WT =wild type SFTI/SFTI-1

146

6 Ser 0.61 Ser 0.56 0.34 0.24 0.15 0.20 0.11

Binding Loop 7 8 Ile Pro 0.00 0.23 Ile Pro 0.00 0.39 0.00 0.25 0.01 0.23 0.01 0.01 0.00 0.17 0.01 0.01

9 Pro 0.00 Pro 0.00 0.00 0.00 0.00 0.00 0.00

10 Ile 0.76 Ile 0.54 0.46 0.48 0.46 0.41 0.47

TOTAL 2.73 2.07 1.60 1.45 1.23 1.22 1.17

Discussion This study focused on KLK14 and characterised its extended substrate specificity by combinatorial and non-combinatorial peptide libraries. Resulting peptides relied heavily on subsite cooperativity to achieve the highest levels of catalytic efficiency. Substituting these sequences into SFTI produced a potent inhibitor of KLK14 (SFTI-WCVR N14) which showed selectivity over the other serine proteases KLK5, trypsin and Matriptase but not KLK4. Furthermore, substitution analysis of the most selective variant (SFTI-WCVR N14) in silico showed that residue 12 replacements promoting higher frequency of internal hydrogen bonds correlated with more potent KLK14 inhibitors in vitro and produced a compound with 13-fold increased binding affinity. Moreover, the inhibitors developed here may be used to help define the contribution of KLK14 in biological assays and presents a novel avenue for the treatment of certain skin pathologies. Peptide substrate libraries are valuable tools for examining protease substrate specificity and combinatorial approaches such as PS-SCLs have the advantage of allowing for high throughput screening. However, combinatorial methods are inherently unable to identify intramolecular and intermolecular cooperativity occurring during protease substrate recognition (Schneider et al. 2009). In this study, the combined substrate preference profile of KLK14 from two PS-SCL screens was refined by a non-combinatorial peptide library and revealed specific examples of subsite cooperativity. Further, a sequence that incorporated these cooperativity features was cleaved with a higher catalytic efficiency than those suggested by either combinatorial library. These findings align with those seen in a previous study of KLK4 where combinatorial methods failed to detect subsite cooperativity (Matsumura et al. 2005; Debela et al. 2006; Borgono et al. 2007). Later screening of KLK4 against a non-combinatorial peptide library identified subsite cooperativity and produced a single substrate sequence that was hydrolysed at a

147

substantially higher rate than those suggested by combinatorial methods (Swedberg et al. 2009). Cooperativity is also important for stabilising naturally occurring standard mechanism inhibitors including SFTI. For example, in the wild-type SFTI the side chain moieties of Arg2 and Asp14 form a salt-bridge that both stabilises the inhibitor backbone and allows for the broad-range activity of the inhibitor (Swedberg et al. 2011). The study presented here revealed that substitutions in the β-sheet of SFTI to target KLK14 (SFTIWCVR N14) resulted in a compromised internal hydrogen bond network compared to the wild-type SFTI. Further in silico analysis of SFTI-WCVR N14 residue 12 variants, indicated that substitutions promoting increased frequency of internal hydrogen bonds correlated with more potent KLK14 inhibitors in vitro. These findings are in agreement with a previous study where insertion of a preferred amino acid sequence of KLK4 into the β-sheet of SFTI (SFTI-FCQR) reduced the prevalence of internal hydrogen bonds (Swedberg et al. 2011). Additionally, increasing frequency of internal hydrogen of bonds of SFTI-FCQR residue 14 variants in silico correlated with lower KLK14 inhibitor constants in vitro as previously seen for KLK4. Internal hydrogen bonds may explain why there was no consistent relationship between kinetic constants of KLK14 substrate sequences and the inhibition constants of their corresponding SFTI variants. For example, SFTI-YCSR N14 was over 8-fold more potent than SFTI-YCVR N14 while the difference in kinetic constants was substantially lower at around 2-fold. Therefore it appears that some contribution to binding affinity of SFTI-YCSR N14 was made by internal hydrogen bonds formed by Ser at the P2 site in a similar way to Thr at this position in the wild-type SFTI. However, this interaction is internal to SFTI and devoid of any particular inhibitor-protease interaction and demonstrates a reduced selectivity as a result. This cooperative effect can be further highlighted by that fact Ser at P2 is one of the least preferred residues for KLK4 (Matsumura et al. 2005; Debela et al. 148

2006; Borgono et al. 2007) while SFTI-YCSR N14 more potently inhibited this protease than SFTI-YCVR N14. As a consequence, a hydrophobic residue at P2 was more successful in achieving selectivity while the inability of this residue to form hydrogen bonds also resulted in significantly lower potency for KLK14. Increasing selectivity could be achieved by screening the S2’ site of KLK14 in vitro to find the most preferred P2’ residue for this position and substitute into the corresponding P2 site of the more potent SFTI-YCSR N14 to achieve selectivity over KLK4 and KLK5. Residue 12 variants of the resulting inhibitor may then be screened in silico to further optimise the internal hydrogen bond network and the potency of inhibition. Comparing this study, which used molecular dynamics to analyse the effect of SFTI residue 12 variants with the previous one, which focused on residue 14; indicates marked differences regarding the effect on frequency and distribution of hydrogen bonds. All residue 14 SFTI substitutions reduced the internal hydrogen bonds of the side loop. Conversely, some substitutions at position 12 resulted in more internal hydrogen bonds occurring in either of the loops of SFTI. This was particularly noticeable for SFTI-WCVR Q12 N14 where a significant increase of hydrogen bonds occurred in the side loop. Inspection of the simulation trajectories revealed that these hydrogen bonds of SFTI-WCVR Q12 N14 caused such a constraint in the side loop that it distorted the binding loop conformation and reduced the ability of Ser 6 to form hydrogen bonds. Flanking the scissile bond of SFTI, Ser 6 plays an important role in the stabilisation of the acyl-enzyme intermediate central to the potency of standard mechanism inhibitors (Shaw et al. 1995; Radisky et al. 2002). Consequently, it is unlikely that this variant would have high potency even though it contained the most internal hydrogen bonds of all variants. In contrast, SFTI-WCVR D12 N14 appears to be a viable option to pursue further, since this inhibitor had the highest proportion of internal hydrogen bonds located in the binding loop. These observations regarding the importance of the internal hydrogen bond network of SFTI can be rationalised 149

in terms of maintenance of the molecule’s rigid structure. Previously, studies have linked the SFTI’s structure with the evolutionary pressure to reduce the entropic debt incurred upon inhibitor/protease complex formation (Korsinczky et al. 2001; Korsinczky et al. 2004; Korsinczky et al. 2005). However, this explanation is less than satisfactory given that the most significant entropic change will be incurred by desolvation of the protease active site and the SFTI contact β-sheet. A more likely explanation is provided by the importance of maintaining the binding loop stability after cleavage of the scissile bond to position the two SFTI termini for peptide bond reformation (Zakharova et al. 2009). The relative importance of hydrogen bonds distributed across the inhibitor versus those within a single loop or cluster of side chains is consistent with this hypothesis. In conclusion, two related while distinct serine proteases have to date been subjected to the combined substrate guided and computer aided approach to produce potent standard mechanism inhibitors. This involves a three stage procedure to sequentially target inhibitor selectivity and potency. Firstly, the protease is screened against a combinatorial PS-SCL of peptides to outline general trends in protease substrate preference. Secondly, a non-combinatorial sparse matrix library of individually synthesised peptides based upon PS-SCL data is used to reveal cooperativity and identify highly preferred cleavage sites. Identified sequences may then be grafted into the protease binding β-sheet of the inhibitor to achieve selectivity. Finally, in silico methods can be used to optimise internal hydrogen bonds of the canonical loop of the inhibitor to ensure rigidity and a confirmation that aligns with the starting structure. If sufficient selectivity is not achieved at this stage, particular features of the protease prime side may be engaged to enhance this property. Combined, the methods presented here are likely to produce potent and selective standard mechanism inhibitors for a wide variety of proteases.

150

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CHAPTER 6

Proteolysis of Sex Hormone-binding Globulin (SHBG) by Kallikreinrelated Peptidases Modulates Androgen Bioavailability In Vitro

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Proteolysis of Sex Hormone-binding Globulin (SHBG) by Kallikreinrelated Peptidases Modulates Androgen Bioavailability In Vitro

Washington Y. Sanchez, Simon J. de Veer, Joakim E. Swedberg, Eui-Ju Hong, Janet C. Reid, James P. Simmer, Terry P. Walsh, John D. Hooper, Geoffrey L. Hammond, Judith A. Clements and Jonathan M. Harris* Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland 4059, Australia

1

Institute of Health and Biomedical Innovation (W.Y.S, S.J.dV, J.E.S, T.P.W, J.A.C, J.M.H),

Queensland University of Technology, Brisbane, Queensland 4059, Australia; 2Child and Family Research Institute and Department of Obstetrics and Gynaecology (E-J.H, G.L.H), 3

University of British Columbia, Vancouver V5Z 4H4, Canada; 4Mater Medical Research

Institute (J.C.R, J.D.H), South Brisbane, Queensland 4101, Australia; 5Department of Biologic and Materials Sciences (J.P.S), School of Dentistry, University of Michigan, Ann Arbor, MI 48109-1078 *Corresponding author: [email protected]

Abstract Stimulation of the androgen receptor via bioavailable androgens including testosterone and testosterone metabolites is a key driver of prostate development and the early stages of prostate cancer. Androgens are particilarly hydrophobic and as such require carrier proteins including sex hormone-binding globulin (SHBG) to enable their systemic delivery. By doing so, SHBG regulates the concentration of free steroids in target tissues and thus influences the androgen signalling axis. This study found that SHBG binds strongly to the androgen regulated kallikrein-related peptidase KLK4 in GST interaction analyses. Furthermore, it was 159

demonstrated that human SHBG is cleaved by active KLK4 and the closely related KLK14. Edman degradation N-terminal sequencing of the cleavage products revealed that both enzymes cut between the two laminin G-like domains on SHBG. Characterisation of SHBG proteolysis products by 3H-labelled DHT binding assays showed unaltered steroid binding properties for the SHBG 1-209 fragment compared to full-length SHBG. Despite this, removal of the SHBG C-terminal (LG5) domain by KLK proteolysis resulted in reduced bioavailable androgen, measured by prostate-specific antigen (PSA) expression as an indicator of activity of the androgen receptor. Collectively, these data suggest that SHBG is a novel substrate for KLK proteases and indicate a new dimension in the regulation of the androgen signalling axis through proteolysis of SHBG.

Key words: SHBG; KLK4; KLK14; Androgen; Cancer

Introduction Prostate cancer is the most common newly diagnosed cancer in the United States and is the third leading cause of cancer-related death in men (Jemal et al. 2010). It is designated a hormone-dependent cancer due to the reliance of the prostate on sex steroids for growth and development in normal physiology, as well as during early stage prostate cancer (Feldman and Feldman 2001). Androgenic actions within the prostate are primarily carried out by two steroid species: testosterone, which is the principal androgen in circulating plasma, and its reduced metabolite, 5α-dihydrotestosterone (DHT), which predominates in the prostate. Classical androgen signalling proceeds through the androgen receptor (AR) which resides intracellularly (Lubahn et al. 1988) and requires androgens to be free to passively diffuse through plasma membranes (Giorgi and Stein 1981; Pardridge 1986). Following steroid binding, the androgen-AR complex rapidly homodimerises, before translocating to the nucleus and stimulating transcription of androgen-responsive genes 160

(Evans 1988). This in turn drives proliferation and differentiation of both the prostate stroma and epithelium. The androgen-dependence of the prostate is highlighted by the fact that androgen deprivation leads to the induction of apoptosis (Kyprianou and Isaacs 1988; Colombel et al. 1992). Accordingly, treatments for early stage (hormone sensitive) prostate cancer focus on androgen ablation. Delivery of androgens (and other sex steroids) to hormone-responsive tissues is primarily regulated by the plasma glycoprotein sex hormone-binding globulin (SHBG), the principal steroid hormone carrier protein in the blood (Westphal 1986). SHBG circulates as a homodimer with each subunit consisting of two laminin G-like domains termed the Nterminal (LG4) and C-terminal (LG5) globulins. Individual steroid-binding pockets are located within the LG4 domain of each monomer (Grishkovskaya et al. 2000; Avvakumov et al. 2001), which bind testosterone and estrogen with nanomolar affinities (Westphal 1986). In addition to steroid binding, the N-terminal globulin contributes the majority of the SHBG’s biological functions characterised to date, housing the motifs required for dimerization (Hammond and Bocchinfuso 1995; Avvakumov et al. 2001), divalent metal ion binding (Avvakumov et al. 2000), and interaction with the putative SHBG cell-surface receptor (RSHBG) (Khan et al. 1990). However, the significance of SHBG to androgen signalling extends beyond steroid transport. Classical androgen signalling requires steroids to be free in solution to access and activate the intracellular AR (Mendel 1989). Therefore, SHBG influences steroid bioavailability by sequestering androgens and estrogens (Pardridge 1986). In a similar manner, SHBG modulates steroid stability and rate of clearance from the bloodstream (Petra et al. 1985; Mendel et al. 1989; Plymate et al. 1990). Consequently, steroid interactions with SHBG are appreciably dynamic; while ligands have to bind with high affinity to be efficiently transported, they must also be progressively released once in the vicinity of target tissues. It has also been proposed that SHBG participates in non-genomic 161

steroid signalling via RSHBG as distinct from the classical androgen- and estrogen- pathways (Hryb et al. 1990; Nakhla and Rosner 1996), although the identity of this receptor remains a matter of debate (Rosner et al. 2010). Aside from complex formation with various steroids, SHBG reportedly interacts with a limited number of extracellular proteins. SHBG has been shown to interact with the matrix-associated proteins fibulin-1D and fibulin-2 within the uterine stroma (Ng et al. 2006). This interaction results in preferential sequestration of steroid-bound SHBG from circulation in a mechanism potentially aimed at enhancing delivery to target cells (Ng et al. 2006). In mice, megalin, a non-specific endocytotic membrane receptor for the vitamin A and D carrier protein, was demonstrated to bind and internalise the SHBG-steroid complex (Hammes et al. 2005). Although activation of a secondary signalling response by this process is yet to be shown, it is thought to contribute to steroid transport and hormone delivery. Previously, a yeast two-hybrid screen examining the interaction between prostatic proteins and human SHBG identified kallikrein-related peptidase 4 (KLK4) as a potential interacting partner (Pope and Lee 2005). KLK4 is a secreted trypsin-like serine protease belonging to the fifteen member tissue kallikrein-related peptidase family (Borgono and Diamandis 2004; Clements et al. 2004). KLK4 shares 40% amino acid sequence homology to classical kallikreins KLK2 and 3 (Stephenson et al. 1999; Harvey et al. 2000) and it is associated with the progression of prostate cancer (Day et al. 2002; Xi et al. 2004; Dong et al. 2005; Swedberg et al. 2010). Given that the expression of KLK4, as well as several other KLKs, is influenced by androgens (Lawrence et al. 2010), a SHBG/KLK interaction is likely to have relevance to androgen signalling within the prostate. Here, we examine the interaction between SHBG and four members of the KLK family (KLK3, 4, 7 and 14) to establish whether SHBG is a substrate for these proteases. For KLKs found to cleave SHBG, protease cut sites were identified by N-terminal sequencing of 162

proteolysis fragments. The effect of steroid binding on SHBG proteolysis was also investigated along with the implications of KLK-SHBG digestion on androgen bioavailability in cell culture. These data suggest a previously unrecognised mechanism for the proteolytic modulation of the androgen signalling axis revolving around SHBG.

Materials and methods

Reagents Lyophilised pregnancy serum-purified human SHBG (from phosphate buffered saline containing 1 mM CaCl2) was obtained from Fitzgerald Industries (Acton, MA). Recombinant KLK4 and KLK14 were produced as described previously (Ramsay et al. 2008; Swedberg et al. 2009) while recombinant KLK3 and 7 were sourced from R&D Systems (Minneapolis, MN). Thermolysin was obtained from Calbiochem (San Diego, CA) and 5αdihydrotestosterone (DHT), bovine serum albumin (BSA) and phosphoramidon were from Sigma-Aldrich (Castle Hill, Australia). Antibodies for western blotting were rabbit antihuman SHBG polyclonal antisera (Hammond et al. 1985), mouse anti-V5 primary (Invitrogen, Mount Waverly, Australia), Alexa Fluor 680-conjugated goat anti-rabbit secondary antibody (Invitrogen) and Alexa Fluor 488-conjugated goat anti-mouse secondary antibody (Invitrogen).

Glutathione S-Transferase (GST) pull-down interaction analyses Recombinant SHBG-GST fusion protein was produced as described previously (Hildebrand et al. 1995). Full length SHBG-GST (20 µg) and an equal quantity of GST were each immobilised on 100 µl glutathione sepharose resin for 1 hour at 4oC. Steroid-bound SHBGGST was prepared by pre-incubation with 100 nM DHT. SHBG-GST interaction analyses were carried out according to Ng et al. (2006) using 1.25 µg of pro-KLK4 or pro-KLK14. 163

Interacting protein was resolved by SDS-PAGE and pro-KLKs were detected by western blot against the V5 epitope on both pro-KLK4 and pro-KLK14. Activation of pro-KLKs Pro-KLK3, 4, 7 and 14 were activated with thermolysin (1:40 thermolysin: KLK) which was inhibited by 40 µM phosphoramidon immediately after activation. Mature KLK4 for cell culture assays was purified from thermolysin by ion exchange chromatography using a Pharmacia Resource Q anion exchange column (Amersham Biosciences, Piscataway, NJ).

Proteolysis of SHBG by KLKs Six concentrations of purified human SHBG (100-2000 nM) were digested with a constant concentration of either KLK4 (7 nM) or KLK14 (10 nM) in 10 µl proteolysis buffer (0.1M TrisHCl pH 7.5, 0.1M NaCl, 1.5 mM EDTA and 0.02% Tween-20). Digestions were carried out at 37oC over 2 hours (KLK14) or 4 hours (KLK4). Samples were taken at intervals of 15 min (KLK14) and 30 min (KLK4), diluted in reducing loading buffer and heated at 95oC to quench protease activity. For each SHBG concentration, samples were separated by SDS-PAGE and examined by western blot analysis for SHBG. Triplicate blots for each SHBG concentration were subjected to densitometric analysis using a Odyssey infrared imaging system (LI-COR Biosciences) for undigested SHBG (48 kDa). Data were compiled using GraphPad Prism 5.01 and initial velocities of SHBG digestion were calculated. These were used to determine semi-quantitative Vmax and Km values followed by kcat and kcat/Km.

N-terminal sequencing of SHBG proteolysis fragments SHBG (1 µg) was digested by KLK4 or KLK14 for 45 or 120 min at 37oC (as above). Samples for each KLK were pooled, lyophilised and resuspended in reducing loading buffer. Digest fragments were resolved by SDS-PAGE, transferred to nitrocellulose and detected by western blot as previously described or transferred to PVDF in CAPS buffer and stained with 164

Coomassie G-250. After blots were destained, proteolysis fragments were excised followed by Edman degradation N-terminal sequencing carried out at the Australian Proteomic Analysis Facility (APAF, Sydney, Australia). To confirm identified cut sites were high affinity substrates for KLK4 or KLK14, putative P4-P1 residues (FNLR and TSLR) were synthesised as peptide para-nitroanilides (peptide-pNAs) according to previously published methods (Abbenante et al. 2000; Swedberg et al. 2009). These substrates were assayed as per Sweberg et al. (2009) with kinetic constants (Km, kcat and kcat/Km) determined as above.

SHBG-DHT digests by KLK4 and KLK14 SHBG (200 nM) was digested with KLK4 or KLK14 for 2 hours at 37oC (as above). Digestions were also carried out in the presence of 1 µM DHT or an equivalent volume of ethanol (steroid vehicle control). Proteolysis fragments were analysed by western blot for SHBG (as above). To confirm any effect caused by SHBG-steroid interaction, control digests were carried out with mouse recombinant amelogenin (M179) produced in E. coli (Simmer et al. 1994). Amelogenin (4 µM) ± DHT or ethanol (as above) was digested with KLK4 and KLK14 for 1 hour at 37oC. Samples were separated by SDS-PAGE, stained with Coomassie G-250 and visualised using the LI-COR Odyssey infrared imaging system.

[3H]-DHT binding assays The steroid binding capacity of full-length and cleaved SHBG was determined using the saturation analysis method of Hammond et al. (1983) . KLK4 cleaved SHBG was prepared as above. [3H]-DHT (42Ci/mmol, PerkinElmer Life Sciences) was used as the labelled ligand. Scatchard analysis (Scatchard 1949) was used to compare the affinity constants for full length and KLK4 cleaved SHBG.

165

Cell culture LNCaP cells (obtained from the American Type Culture Collection) were maintained in RPMI-1640 media supplemented with 10% fetal calf serum (In vitro Technologies, Noble Park, Australia), 100 units/ml penicillin (Invitrogen) and 100 µg/ml streptomycin (Invitrogen). Cultures were propagated at 37oC in a humidified atmosphere containing 5% CO2.

Androgen bioavailability assays LNCaP monolayers were established in 24-well plates and deprived of androgens by culture in serum-free RPMI-1640 media for 72 hours. Prior to treatment, SHBG (final concentration 35 nM) was incubated with DHT (3 nM) for 60 min at 4oC. This ensured the concentration of DHT was below the SHBG-DHT Ka, and therefore bioavailable androgen would initially present. Cells were treated with fresh serum-free media containing either: DHT (3 nM), steroid-bound SHBG (see above), untreated SHBG (35 nM) or steroid vehicle control. Samples of media were taken at 0, 8, 16 and 24 hours to monitor free androgen by DHT ELISA (Alpha Diagnostic International, San Antonio, TX) according to the manufacturer’s instructions.

Modulation of androgen bioavailability by proteolysis of SHBG LNCaP cells were deprived of steroids by culture in serum-free media (as above). Prior to treatment, SHBG was bound with DHT (1:2) at 4oC for 60 min. Following this, cleaved DHTbound SHBG was prepared by digestion with purified KLK4 for 2 hours at 37oC. Cells were treated in fresh serum-free media containing either: DHT (final concentration 25 nM), untreated SHBG (12.5 nM), DHT-bound SHBG (12.5 nM), KLK4-digested DHT-bound SHBG (10 nM KLK4, 12.5 nM SHBG) along with controls for steroid vehicle and KLK4 (10 nM). Culture proceeded for 48 hours, after which media was recovered and concentrated 20-fold 166

using 96-well MultiScreen Filter Plates with 10 kDa cut-off Ultracel Membrane (Millipore, Billerica, MA) according to the manufacturer’s instructions.

PSA ELISA Concentrated culture media was bound to 96-well Nucleon protein-binding plates (Nunc) overnight at 4oC. Unoccupied binding sites were blocked for 3 hours at room temperature with 1% BSA in Tris buffered saline containing 0.005% Tween-20. PSA was detected with mouse anti-human PSA monoclonal IgG (clone PS6, Santa Cruz Biotechnology, Santa Cruz, CA), followed by goat anti-mouse polyclonal horse radish peroxidise-conjugated secondary (Pierce, Rockford, IL). Signal was developed using tetramethylbenzidine substrate (GE Healthcare Life Sciences, Buckinghamshire, UK) according to the manufacturer’s instructions using a Biorad Benchmark Plus multi-well spectrophotometer. Specificity of the PSA antibody was determined by western blot analysis on concentrated media samples against PSA (antibodies as for ELISA above). Additionally, SHBG western blots were carried out (as above) to confirm steroid-bound SHBG was digested by KLK4 in these assays.

Results

Pro-KLK4 and pro-KLK14 interact with SHBG-GST Previously, a yeast two-hybrid screen indicated SHBG may interact with the prostate cancer associated protease, KLK4 (Pope et al. 2005). To verify this interaction, SHBG-GST binding analyses were carried out with pro-KLK4 and the closely related pro-KLK14. Western blot analysis on pro-KLKs binding to immobilised SHBG-GST confirmed an interaction with proKLK4 (Figure 1A) and pro-KLK14 (Figure 1B). Further, the interaction with SHBG by pro-KLK4 but not pro-KLK14 was markedly increased by the presence of androgen, although binding persisted in the absence of steroid for both KLKs. No interaction was seen with immobilised 167

Figure 1: GST interaction analyses between SHBG and pro-KLKs. A. pro-KLK4 or B. proKLK14 interacting with GST and SHBG-GST fusion protein. Interacting protein was analysed by western blot analysis against the V5 epitope on recombinant pro-KLK4 and pro-KLK14 following overnight binding to immobilised GST or SHBG-GST. Additionally, interaction with SHBG-GST pre-loaded with DHT was examined to determine the effect of

steroid-binding

on

the

SHBG-KLK

interaction. GST alone controls confirmed that the binding interaction was specific for SHBG. Western blots are representative of three independent experiments

GST alone, confirming that the observed pro-KLK interactions occurred through SHBG and not the affinity tag.

SHBG is cleaved by KLK4 and KLK14 Having established that pro-KLK4 and pro-KLK14 bind to immobilised SHBG, it was investigated whether SHBG was also a substrate for these proteases. SHBG was cleaved by both KLKs with visible proteolysis fragments suggesting that each KLK had distinct cut site preferences. A single band at 25 kDa was the predominant product visible following KLK4 proteolysis (Figure 2A) while the major fragments from KLK14 digestion occurred at 30 kDa and 20 kDa (Figure 2B). No proteolysis was observed in control thermolysin digests. To examine whether SHBG may be a common substrate for prostate-expressed KLKs, digestions with KLK3 and KLK7 were also attempted. However, no detectable proteolysis of SHBG was seen (data not shown). Proteolysis of SHBG by KLK4 and KLK14 was measured by semi-quantitative kinetic analysis. Since the preferred cleavage sites for KLK4 and KLK14 differed, densitometry analysis was carried out on residual uncleaved SHBG (48 kDa). 168

Figure 2: SHBG is cleaved by KLK4 and KLK14. Purified human SHBG digested with active A. KLK4 or B. KLK14. Varying concentrations of SHBG were digested with

a

constant

concentration

of

protease to calculate semi-quantitative kinetic

constants

(2000

nM

SHBG

digestion is shown). Protease activity o was quenched by heating to 95 C in

reducing SDS-PAGE loading buffer, after which, SHBG digestion products were separated by SDS-PAGE and analysed by western blotting. Blots were visualised using the LI-COR Odyssey infrared imaging system and are representative of three independent experiments.

Kinetic constants indicated that proteolysis of SHBG was with kcat/Km values of 1.6 x 104 and 3.8 x 104 M-1 s-1 for KLK4 and KLK14 respectively and that KLK14 was a more efficient protease against SHBG than KLK4 (Table 1).

Table 1. Kinetic constants for SHBG and peptide-pNA KLK digests Protease/substrate Km kcat KLK4/SHBG (1.2 ± 0.7) x 10-6 M 0.02 ± 0.01 s-1 KLK14/SHBG (2.1 ± 0.6) x 10-6 M 0.08 ± 0.01 s-1 -4 KLK4/FNLR-pNA (1.1 ± 0.1) x 10 M 5.07 ± 0.09 s-1 -4 KLK14/TSLR-pNA (1.8 ± 0.2) x 10 M 18.80 ± 0.83 s-1

kcat/KM 1.6 x 104 M-1·s-1 3.8 x 104 M-1·s-1 4.6 x 104 M-1·s-1 1.0 x 105 M-1·s-1

Identification of KLK4 and KLK14 cut sites from SHBG proteolysis fragments Fragments liberated by KLK4 and KLK14 cleavage of SHBG were sequenced to determine the cut-sites for each protease. Higher concentrations of SHBG were digested to produce sufficient amounts of each fragment for sequencing. This also permitted detection of proteolysis fragments independent of antibody affinity. Consequently, while prior western blots may have suggested fragment 3 was processed further since it was less abundant

169

(Figure 3A), Coomassie-stained blots revealed it was more likely that fragment 3 did not contain a dominant epitope (Figure 3B). The identity of each fragment was determined by Edman degradation N-terminal sequencing (Table 2). Amino acid sequence data identified two predominant cut sites: one generated immediately after Arg-186 (fragment 1), and one commencing after Arg-209 (fragment 2). Fragment 3 corresponded to the N-terminus of full length SHBG (undefined C-terminus). Both cut sites were located on the region between the two laminin G-like domains of SHBG, illustrated in Figure 3C. To confirm identified cut sites were high affinity substrates for KLK4 or KLK14, the four non-prime residues (P4-P1) of each cut site were synthesised as peptide-pNA substrates. Kinetic constants were

Figure 3: N-terminal sequencing of SHBG proteolysis fragments to determine KLK4 and KLK14 cut sites. A. SHBG proteolysis fragments generated by KLK4 and KLK14 visualised by western blot analysis (as described previously). B. Coomassie G-250 stained electroblot of KLK4 and KLK14 digested SHBG. Digestion fragments were separated by SDS-PAGE, transferred to PVDF and stained with Coomassie G-250. Indicated fragments (*) were excised and subjected to Edman degradation Nterminal sequencing. N-terminal sequence data returned for fragment 1-3 is shown in Table 2. C. Schematic representation of human SHBG showing the N-terminal (LG4) and C-terminal (LG5) laminin G-like domains. Generated fragments are shown below. Sequence analysis indicated that the cleavage sites occurred between the two laminin G-like domains.

170

determined for cleavage of these substrates corresponding to the cut site preference of each protease (KLK4/FNLR-pNA and KLK14/TSLR-pNA). Calculated kcat/Km values (Table 1) verified efficient cleavage of these sequences.

Table 2.Cleavage sites for KLK4 and KLK14 proteolysis of SHBG revealed by N-terminal sequencing Fragment

N-terminal Sequence

Fragment 1

SCDVES

Fragment 2

DIPQPH

Fragment 3

LRPVLP

Cut Site Architecture (P4 – P4’) T F

S

L

N

186

S

C

D

V

209

D

I

P

Q

R

L

R

N-terminus of mature SHBG

DHT alters KLK4 and KLK14 proteolysis of SHBG Since endogenous SHBG is conceivably steroid-bound, proteolysis assays were carried out with SHBG pre-incubated with DHT. Steroid-bound SHBG showed noticeably reduced rates of proteolysis with KLK4 (Figure 4B) and KLK14 (Figure 4C), hence the binding of androgen to SHBG appears to make it less susceptible to proteolysis by these enzymes. Furthermore, SHBG that was ligand-bound was processed differently by KLK14, shifting the cut site preference to cleavage predominantly at Arg-209. Control digests with amelogenin, a substrate common to KLK4 and KLK14, in the presence and absence of DHT (Figure 4E-F)

Figure 4: DHT modulates KLK proteolysis of SHBG. A-C. Western blot analysis for buffer only, ethanol vehicle or DHT treated SHBG which was A. not digested, B. digested with KLK4 or C. digested with KLK14. D-F. Coomassie G-250 stained SDS-PAGE analysis for buffer only, ethanol vehicle or DHT treated recombinant mouse amelogenin which was D. not digested, E. digested with KLK4 or F. digested with KLK14. Gels were visualised using the LI-COR Odyssey infrared imaging

system.

representative experiments.

171

of

All three

Figures

are

independent

confirmed that altered proteolysis of SHBG was produced by steroid binding to SHBG and not a KLK-DHT interaction.

SHBG cleaved by KLK4 retains identical steroid binding capacity To assess the effect of SHBG cleavage on steroid binding we carried out comparative binding assays using intact SHBG and protein that had been cleaved by KLK4 as described above. Cleavage was confirmed by western blot analysis of proteolytic fragments which showed the characteristic proteolytically resistant peptide migrating with a molecular weight of 25 kDa (Figure 5A). Scatchard analysis showed that cleavage had no significant impact on DHT affinity despite the complete removal of the SHBG C-terminal domain.

SHBG prolongs androgen bioavailability over time in cell culture Retention of bioavailable DHT in cell culture media over time was measured to determine the ability of SHBG to bind and stabilise androgens in vitro (Figure 6). In free androgen treatments, while bioavailable DHT was abundant at 0 hour, it was rapidly depleted within 8 hours. In contrast, free DHT was lower at 0 hour when pre-incubated with SHBG since a proportion of steroid was bound to the carrier protein. However, it was more efficiently retained with detectable levels present at every time interval and a gradual decline by 24 hours. This indicated that binding androgen to SHBG greatly increased the stability of DHT in vitro, potentially by protecting it from steroid metabolism. No steroid was detected in untreated SHBG media, confirming a lack of contaminating androgen.

172

Figure 5: SHBG cleaved by KLK4 has identical steroid binding properties. A. Western blot analysis on intact and KLK4 cleaved SHBG under reducing (left) and native (right) conditions confirming proteolysis of SHBG produces two separate fragments. B. Saturation curve for binding of various 3

concentrations [ H] labelled DHT to fulllength (closed circles) and KLK4 cleaved SHBG (open circles).

C. Scatchard analysis was used to compare the affinity constants for full length and KLK4 cleaved SHBG.

Proteolysis of SHBG modulates androgen bioavailablity in cell culture The impact of KLK proteolysis on SHBG’s ability to influence androgen bioavailability was investigated using the androgen-responsive LNCaP cell-line. Utilising PSA expression as an indicator of the activity of the androgen receptor, and therefore bioavailable androgen, cells were stimulated in serum-free media and secreted PSA detected by ELISA (Figure 7A). Treatment with 25 nM DHT stimulated elevated PSA expression. Further, DHT-bound SHBG enhanced PSA expression compared to steroid only treatment, demonstrating that the previously identified improved DHT retention in culture media by SHBG resulted in enhanced AR signalling and gene expression. However, when cells were treated with DHT173

Figure

6:

SHBG

prolongs

androgen

bioavailability in cell culture. DHT ELISA for bioavailable androgen in cell culture media over 24 hours. Serum-starved LNCaP cells were

treated

with

serum-free

media

containing 3 nM DHT (open circles), 35 nM untreated SHBG (triangles) or 35 nM SHBG pre-loaded with 3 nM DHT (closed circles). Data was expressed as a fold-change over DHT measured at 0 hour in 3 nM free DHT treatments as mean ± S.E.M. from three independent experiments.

bound SHBG that had been digested with KLK4, a consistent and noticeable reduction in PSA expression was observed compared to undigested steroid-bound SHBG. The ‘free steroid’ theory requires stimuli to be free in solution to traverse the plasma membrane and activate the AR, hence this indicated that cleavage of SHBG by KLK4 may reduce delivery of androgen in vitro. Treating SHBG with dextran-coated charcoal prior to steroid loading did not alter PSA expression, both in terms of SHBG-DHT and KLK4 digested SHBG-DHT treatments (data not shown). To validate specificity of the PSA antibody, repeated western blots on conditioned media were carried out (Figure 7B). These identified a single band at the expected MW of PSA (34 kDa) with an intensity which concurred with ELISA data. Triplicate western blots also confirmed considerable ex situ cleavage by KLK4 (Figure 7C). This produced a fragment profile with digest products migrating at 25 kDa which corresponded to cleavage at Arg-209 as previously characterised (Figure 3).

174

FIGURE

7:

Proteolysis

of

SHBG

modulates androgen bioavailability in cell culture. A. DHT stimulated secretion of PSA measured by ELISA was used to assess steroid bioavailability. Serumstarved LNCaP cells were stimulated with 25 nM DHT, 12.5 nM SHBG (DHT-bound) or KLK4 digested 12.5 nM SHBG (DHTbound) along with controls for steroid vehicle (ethanol), KLK4 and untreated SHBG. Data were expressed as PSA levels relative to standard free androgen treatments (25 nM DHT) as mean ± S.E.M.

of

three

experiments.

B.

independent

Validation

of

PSA

antibody specificity by western blot analysis detected a single band the intensity of which concurred with ELISA data. Paired loadings for each condition are

from

separate

treatments.

C.

Confirmation of equivalent SHBG loading and substantial KLK4 proteolysis of DHTbound SHBG

by western blot on

concentrated conditioned media. Paired loadings for each condition are from separate treatments.

Discussion Prostate physiology is dominated by the androgen signalling axis which dictates prostatic development and is the prime point of therapeutic intervention in prostate cancer (Kirk 2004). Delivery of androgens to target tissues, enhancement of their stability in circulation and regulation of their bioavailability are primary functions of the steroid-binding protein, SHBG. Therefore, SHBG determines the ability of steroids to effect androgen-responsive

175

gene expression with potential significance to both homeostasis and tumourigenesis within the prostate. To date, knowledge of SHBG interacting proteins is fairly limited. Furthermore, interaction validation and characterisation is confined to a sparse subset of targets such as the uterine stroma matrix-associated proteins fibulin-1D and fibulin-2 (Ng et al. 2006) and the non-specific cell-surface receptor megalin (Hammes et al. 2005). However, proteolytic regulation of SHBG steroid carriage and delivery has yet to be thoroughly investigated. This study is the first to establish that SHBG, a critical plasma steroid binding protein, is a target for proteolysis by two prostate-expressed kallikrein proteases. Although KLK4 and KLK14 readily cleaved SHBG, the extent to which SHBG in complex with DHT was digested was noticeably reduced. This is in contrast to the higher affinity of pro-KLK4 for steroid-bound SHBG in GST interaction analyses. However, as previously noted for the ligand-dependent interaction of SHBG with cell-surface molecules (Grishkovskaya et al. 2002), a comprehensive explanation of this phenomenon is difficult to build without the structure of full length SHBG or the SHBG LG4 domain in an unliganded state. Despite this, some insight can be gained by examining the structure of the SHBG LG4 domain in complex with DHT (Grishkovskaya et al. 2000). The secondary structure of the LG4 domain is hallmarked by a twin seven-stranded β-sheet arrangement with the steroid binding groove extending deep between the adjacent sheets. Whilst this region is markedly hydrophobic, and therefore very unlikely to be solvated, it may permit some degree of flexibility across the protein when SHBG is in a ligand-free state. Occupying the steroid binding pocket with a relatively planar and rigid high affinity ligand such as DHT would provide an interface for tightly linking the adjacent sides of the binding pocket together and consequently may constrain any structural flexibility. In turn, this may limit access to the Arg-186 cut site which is also located on the N-terminal domain. Indeed, several conformational shifts have been noted for the SHBG 176

LG4 domain depending on the bound steroid (Grishkovskaya et al. 2002), including across a region with homology to a macromolecular interaction domain in structurally-related proteins (Rudenko et al. 2001). Such an effect accords with the distinct shift in KLK14 cut site preference observed upon steroid binding from predominantly Arg-186 to exclusively Arg-209. Several previously identified SHBG protein-protein interactions are also modulated in a ligand-dependent manner. Both estradiol and DHT significantly increased the interaction between SHBG and members of the fibulin family of extracellular matrixassociated proteins (Ng et al. 2006) while SHBG cannot bind to its putative cell-surface receptor when steroid bound (Hryb et al. 1990). Comparison of ligand-dependent modulation of KLK-SHBG proteolysis to the previously reported KLK4 cleavage of IGF-BPs is difficult, given that proteolysis of these proteins has not been examined when bound with IGF (Matsumura et al. 2005). Following characterisation of SHBG cleaved by KLK4 revealed that the N-terminal fragment (SHBG 1-209) retained identical steroid binding capacity compared to full length SHBG. This contrasts with a protease-mediated steroid release from corticosteroid binding globulin (CBG). Here, elastase cleavage of CBG induces a conformational change, reminiscent of serpin rearrangement following protease cleavage at the reactive loop (Loebermann et al. 1984; Huntington et al. 2000), resulting in liberation of corticosteroids from their carrier protein (Pemberton et al. 1988; Hammond et al. 1990). Nonetheless, this aligns with previous studies which have demonstrated that the SHBG LG4 domain alone is capable of the majority of SHBG’s biological functions, including steroid binding (Grishkovskaya et al. 2000; Avvakumov et al. 2001), dimerisation (Hammond et al. 1995; Avvakumov et al. 2001) and interaction with R SHBG (Khan et al. 1990). Despite indistinguishable steroid binding properties, proteolytic removal of the Cterminal LG5 domain altered SHBG’s influence on the androgen signalling axis in cell 177

culture. Androgen-responsive PSA expression was enhanced by delivering the DHT in complex with full-length SHBG, which we suggest offered the steroid greater protection from hydrolysis in the culture media. However, this effect was markedly reduced by cleaving the steroid-bound SHBG with KLK4, a prostate-expressed serine protease upregulated by AR activation. Two factors potentially complicate analysis of this phenomenon in biological assays. Firstly, the SHBG used in this study is purified from human pregnancy serum and so conceivably could carry significant levels of progesterone and other steroids. The significance of this lies with the fact that the LNCaP AR carries a substitution that renders it responsive to both estradiol and progesterone (Veldscholte et al. 1990). However, we found that SHBG subjected to steroid depletion using activated charcoal behaved identically to untreated carrier protein, which is consistent with other studies in the field (Hammond and Lahteenmaki 1983). Secondly, there have been numerous reports that SHBG itself can act as a signalling molecule at the cell surface when transitioning from ligand-free to ligand-bound states. This pathway is proposed to stimulate non-genomic AR activation coinciding with accumulation of cAMP (Nakhla et al. 1990). To reduce effects of SHBG-receptor signalling, SHBG was bound with DHT prior to addition to culture media in our studies, and so would be less likely to undergo a ligand-free to bound transition at the cell surface. Therefore, the reduction in detecTable PSA suggested that SHBG cleaved by KLK4 did not deliver bound steroid as efficiently as full-length SHBG. Considering the unaltered steroid binding for cleaved SHBG in comparison to intact SHBG, this potentially indicates a role for the C-terminal LG5 domain in mediating a physical interaction with the cell surface to enable active delivery or enhance passive steroid release. Given that expression of KLK4 is upregulated by androgens, proteolysis of SHBG may represent a potential feedback loop in androgen delivery and transcription of androgen responsive genes. Hence, KLK4, whose expression is androgen responsive 178

(Lawrence et al. 2010), cleaves SHBG to produce a proteolytic product with diminished ability to deliver androgen to cells. Consequently, KLK4 cleavage of SHBG will ultimately lead to lower levels of androgen-stimulated transcription by reducing bioavailable androgen, completing the feedback loop. Despite the fact that SHBG is traditionally associated with steroid transport in the blood, it has been established that SHBG is sequestered from circulation and accumulates within the stroma of sex-steroid responsive tissues such as the uterus (Ng et al. 2006). It is now well entrenched within proteolysis research that the contribution of proteases to cellular physiology encompasses great diversity, extending far beyond nonspecific protein degradation (Katsunuma 1997). In particular, defined cleavage drives several biological functions including stimulation of signalling events across the plasma membrane via protease-activated receptors (Soh et al. 2010) and regulation of protease activation cascades (Katsunuma 1997). Our data suggests a novel mechanism for regulating the critical androgen signalling axis by modulating the ability of SHBG to deliver bound steroids. To our knowledge, this would be the first example of an intrinsic regulatory mechanism focused on SHBG and the androgen signalling axis.

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183

CHAPTER 7

Substrate Guided Design of Potent Plasmin Peptide Aldehyde Inhibitors.

184

185

Substrate Guided Design of Potent Plasmin Peptide Aldehyde Inhibitors.

Joakim E. Swedberg and Jonathan M. Harris* Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland 4059, Australia *Corresponding author: [email protected]

Abstract Perioperative bleeding is a cause of major blood loss and is associated with increased rates of postoperative morbidity and mortality. Consequently, antifibrinolytic agents such as inhibitors of the serine protease plasmin are commonly used to reduce bleeding during surgery. The most effective and widely used of these is aprotinin, a broad range serine protease inhibitor of bovine origin. However, aprotinin has recently been withdrawn from general use after a large multicenter clinical trial found this drug associated with increased morbidity and mortality. In turn, this has led to a search for alternative treatments with comparable efficacy. This study used a non-combinatorial peptide library to define plasmin’s extended substrate specificity and guide the design of potent transition state analogue inhibitors. The various substrate binding sites of plasmin were found to exhibit a higher degree of cooperativity than had previously been appreciated. Peptide sequences capitalising on these features produced high affinity inhibitors of plasmin. The most potent of these, LysMet(sulfone)-Tyr-Arg-H (KM(O2)YR-H), inhibited plasmin with a Ki of 3.1 nM while maintaining 25-fold selectivity over plasma kallikrein. Furthermore, 125 nM (0.16 μg/ml) KM(O2)YR-H

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attenuated fibrinolysis with similar efficacy to 15 nM (0.20 μg/ml) aprotinin in an in vitro assay making it an attractive candidate for further therapeutic development.

Key words: Plasmin; Fibrinolysis; Inhibitor; Aprotinin; Positional scanning; Drug design

Introduction Perioperative bleeding is a significant cause of blood loss (Mannucci et al. 2007) and a large contributor to post operative complications (Koh and Hunt 2003). Major blood loss necessitates transfusion which is itself associated with risks of allergic reactions, mismatched transfusion and transmission of infections (Blajchman et al. 2006). Additionally, there is a global shortage of blood products (Goodnough and Shander 2007). Therefore, pharmacological intervention is commonly employed to reduce excessive bleeding and demand on blood transfusions during surgery, with antifibinolytic therapy being the most frequently employed method (Levy 2008). The serine protease plasmin is the primary enzyme responsible for dissolution of fibrin (Rijken and Lijnen 2009), the main structural component of blood clots. Commonly used antifibrinolytics are inhibitors of plasmin, either directly or through the prevention of activation of its zymogen plasminogen. While plasminogen is expressed in all tissues (Zhang et al. 2002), the principal source of circulating enzyme is the liver (Saito et al. 1980). Zymogen processing primarily occurs through two activators, urokinase-type plasminogen activator (uPA) (Robbins et al. 1967) and tissue-type plasminogen activator (tPA) (Hoylaerts et al. 1982), with tPA being considered to be most physiologically relevant in the intravascular compartment. Plasminogen activation by tPA can only occur at an appreciable rate when both the zymogen and activator are bound to fibrin through lysine binding sites on their kringle domains (Lerch et al. 1980) thereby restricting plasmin activity to the area of clotting. Further regulation occurs both at the level of plasminogen activation by plasminogen activator inhibitor-1 (Carmeliet et al. 1995) or 187

thrombin activatable fibrinolysis inhibitor (TAFI) (Bajzar et al. 1995) as well as at the level of plasmin, primarily by α-antiplasmin (Aoki et al. 1978). Until recently the plasmin inhibitor aprotinin (Trasylol®) was both the most effective and widely used antifibinolytic for reduction of perioperative bleeding (Mannucci et al. 2007). Aprotinin is a Kunitz-type serine protease inhibitor originally isolated from bovine lung tissue (Kunitz et al. 1936) that inhibits virtually all serine proteases (Ascenzi et al. 2003). However, use of aprotinin as an antifibrinolytic has been linked to increased incidence of myocardial infarction (Bukhari et al. 1995), vein graft hypercoagulation (Cosgrove et al. 1992) and renal failure (Karkouti et al. 2006; Mangano et al. 2006; Shaw et al. 2008). Accordingly, general use of aprotinin was discontinued in November 2007 after a large multicenter study from the Blood Conservation using Antifibrinolytics in a Randomised Trial (BART) found higher mortality rates associated with aprotinin compared to alternative treatments in the form of lysine analogues (Fergusson et al. 2008). ε-Aminocaprioic acid (EACA) (Okamoto et al. 1959) and tranexamic acid (TXA) (Okamoto et al. 1964) are lysine analogues which does not inhibit plasmin directly but rather bind to plasminogen’s lysine binding sites, preventing binding to fibrin and therefore efficient conversion to plasmin (Lucas et al. 1983). Although previously considered to have unproven efficacy in reducing bleeding during surgery (Royston 1998; Carless et al. 2005), recent investigations and meta-analyses of clinical trials have led to the conclusion that the lysine analogues reduce the need for blood products, while the reported level of effectiveness varies (Brown et al. 2007; Mannucci et al. 2007; Fergusson et al. 2008; Henry et al. 2009; Kagoma et al. 2009; Koster et al. 2010). However, both lysine analogues suffer from poor affinity and are non-specific lysine binding site inhibitors commonly given at high doses (EACA, 10-30g; TXA 310g), with loading doses at induction of anesthesia being equivalent to millimolar

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concentrations in the plasma (Royston 1998; Koster et al. 2010). Since these compounds inhibit any lysine domain binding interaction, high concentrations may result in clinical effects beyond plasmin inhibition and have been linked to nonischemic seizures (Koster et al. 2010). Consequently, there is a need for development of more potent and specific inhibitors of plasmin that can be administrated at lower concentrations with reduced risk for off-target effects. As with any protease target, design of potent and selective small molecule inhibitors against plasmin requires detailed knowledge of the active site architecture and resulting substrate preference. The extended peptide substrate specificity of plasmin has previously been investigated using positional-scanning synthetic combinatorial libraries (PS-SCL) (Backes et al. 2000; Harris et al. 2000; Gosalia et al. 2005). However, conflicting results were reported suggesting that plasmin’s peptide substrate preference has yet to be fully defined. PS-SCL consists of pools of substrates that poorly predict subsite cooperativity (Schneider et al. 2009; Swedberg et al. 2009; Swedberg et al. 2010). In addition, since the sub-libraries are produced with mixtures of amino acids with differential reaction rates, equal representation of all amino acids is unlikely (Boutin et al. 1997). Consequently, findings from PS-SCLs need to be further evaluated by rigorous screening against libraries of individually synthesised peptides. This study focuses on further defining plasmin’s extended peptide substrate preference by screening against a non-combinatorial peptide library using the para-nitroanilide (pNA) reporter group. Sequences of substrates cleaved with high efficiency were selected as candidates for plasmin peptide aldehyde transition state analogue inhibitors. The most potent of these Ac-KM(O2)YR-H inhibited plasmin (Ki = 3.08 ± 0.26) with 25-fold selectivity over plasma kallikrein (pKLK). Furthermore, 0.16 μg/ml Ac-KM(O2)YR-H prevented fibrinolysis with similar efficacy to 0.20 μg/ml aprotinin in an in vitro fibrinolysis assay.

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Methods and Materials

Peptide synthesis All peptide synthesis reagents and solvents were of analytical grade and obtained from Auspep Pty Ltd and Merck Pty Ltd, respectively, unless otherwise stated. Peptide para-nitroanilide (pNA) substrates were synthesised using para-phenylenediamine (Sigma-Aldrich) derivatised 2chlorotrityl resin (1.3 mmol/g) as previously described (Abbenante et al. 2000). Peptide elongation was performed with 4 eq. 9-fluorenylmethyl carbamate protected amino acids dissolved

in

0.25

M

each

of

2-(1H-benzotriazole-1-yl)-1,1,3,3-tetramethyluronium

hexafluorophosphate (HBTU), 1-hydroxybenzotriazole (HOBt) and N,N-di-isopropylethylamine (DIPEA;) in N,N-dimethylformamide (DMF) for 1 hour. Fmoc deprotection was achieved by treatment with 45% DMF, 50% piperidine and 5% 1,8-diazabicyclo [5.4.0]undec-7-ene (DBU; Sigma-Aldrich) over a period of 10 min. Fully protected peptides were liberated from the solid support by successive changes of 1% trifluoroacetic acid (TFA) in dichloromethane (DCM) followed by ether precipitation and overnight oxidation using 8 eq. Oxone® (Sigma-Aldrich) in acetonitrile: H2O (50:50). Protecting groups were removed from the dry product by cleavage for 2 hr hours 95% TFA, with scavengers; 1.25% triisopropylsilane (TIS; Sigma-Aldrich), 1.25% H2O and 2.5% thioanisole (Sigma-Aldrich). Peptides used for kinetic constants were purified by reverse phase HPLC (rp-HPLC) using a Jupiter 4µ Proteo 90A C-18 column (Phenomenex) developed with a gradient of 20-100% isopropanol-water containing 0.1% TFA before mass validation using MALDI-TOF mass spectrometry (ProteinChip System; Bio-Rad), lyophilisation and storage at -20 °C. Peptide aldehydes were synthesised on H-Arg(Boc)2-H NovaSyn® TG resin (0.21 mmol/g; Novabiochem) as described above. Protecting groups were removed by washing with 190

5 volumes of TFA for one hour before washing 3 times with 10 volumes each of DCM, DMF and acetonitrile to remove any residual TFA. Methionine was converted to methionine sulfone on resin by oxidation with oxone® (20 eq.) in water/acetonitrile (50:50) over 6 hours before cleavage with 1% TFA in water for 1 hour. Peptide aldehydes were purified and validated as above before storage under a nitrogen atmosphere at -80°C.

Kinetic enzyme assays Lyophilised crude SML substrates were solubilised in isopropanol and adjusted to equal molarity by total hydrolysis of the pNA moiety. Assays were performed with 6 nM human plasmin (Sigma-Aldrich) and 133.33 µM peptide substrates in 270 µl assay buffer (100 mM NaCl2, 0.005% Triton-X, 100 mM Tris-HCl , pH 8) and 10% isopropanol (from substrates), while measuring hydrolysis at 405 nM over 2 min. Kinetic constants for selected peptide substrates (18.75 - 600 μM) were determined for plasmin (1 nM) and pKLK (2 nM) in 300 µl assay buffer over 7 min and were calculated from three independent experiments by non-linear regression using Prism 5 (GraphPad Software Inc.).

Inhibitor assays Increasing concentrations of inhibitors were assayed against various proteases (human plasmin, 1 nM; human thrombin, 50 nM; human pKLK, 2 nM, bovine β-trypsin, bovine αchymotrypsin 25 nM; recombinant human KLK4, 2 nM; human factor IXa, 20 nM) as above in 300 μl assay buffer with 100 µM substrate over 7 min. The assay buffers for trypsin and factor IXa also included 10 mM CaCl2 with an additional 10% polyethylene glycol for factor IXa. Inhibition constants were determined from three independent experiments by non-linear regression using Prism 5. Protein proteolysis assays were performed as above with 7 μM 191

human fibrinogen over 30 min (trypsin) or 90 min (plasmin) before termination by boiling in SDS-PAGE sample buffer. Proteolysis fragments were separated on 10% polyacrylamide gels and were visualised by staining with Coomassie brilliant blue R-250 (Sigma-Aldrich). All proteins excluding KLK4 were obtained from Sigma Aldrich.

Protein expression and purification. Recombinant KLK4 was produced using a Sf9 insect cell expression construct as previously reported (Ramsay et al. 2008; Swedberg et al. 2009). These expression vectors generate the complete KLK4 amino acid sequence followed by a V5 epitope (GKPIPNPLLGLDST) and polyhistidine tags. Pro-KLK4 was purified from conditioned media using Ni2+-nitrilotriacetic acid agarose (Qiagen) according to the manufacturer’s instructions. The identity of the expressed protein was confirmed by western blot analysis before the zymogen was activated by incubation with thermolysin at a ratio of 1:40 for 60 min. Active KLK4 was purified in 50 mM Tris HCl, pH 7.5 using a 1 ml resource Q column (GE HealthCare) while eluting with 50 mM Tris HCl, pH 7.5 and 0.5 M NaCl in a linear gradient before storage at -80°C

Fibrinolysis assay Fibrinolysis assay was performed as previously described (Wolberg et al. 2002) with the following changes. Increasing concentration inhibitor was mixed with plasmin and thrombin in 150 µl fibrinolysis buffer (150 mM NaCl, 15 mM CaCl2 and 100 mM Tris-HCl, pH 7.4). The assay was initiated by addition of fibrinogen in 50 µl fibrinolysis buffer and fibrin formation and degradation was monitored by absorbance at 400 nm over 3 hours in a transparent 96 well plate. Final enzyme and substrate concentrations were: 1.5 nM plasmin, 30 nM thrombin and 4 mg/ml fibrinogen. 192

Results

Plasmin substrate binding sites express cooperativity Plasmin’s extended peptide substrate preference has previously been investigated using PS-SCL with conflicting results (Backes et al. 2000; Harris et al. 2000; Gosalia et al. 2005) indicating that the peptide substrate specificity of this protease is yet to be fully realised. Consequently, a noncombinatorial sparse matrix library (SML) of individually synthesised peptide substrates was designed to establish the most preferred plasmin peptide cleavage site. The SML incorporated amino acids that previous PS-SCL studies found to be preferred for the P1-P4 sites of plasmin and included basic P1 residues, aromatic P2 residues, polar P3 residues and basic/hydrophobic/polar P4 residues (Table 1). Although Met is oxidised during synthesis of peptide-pNAs with the method used here (Abbenante et al. 2000), the product Met sulfone (Met(O2)/M(O2)) appeared to fit plasmin’s polar preference at the P3 (rather than norleucine) and was consequently included. Screening of the peptide library against plasmin indicated that the preference for Lys over Arg in the P1 position was less than previously reported (Figure 1) (Backes et al. 2000; Harris et al. 2000). However, Lys at the P1 site did result in more promiscuous cleavage while a slight preference for Tyr compared with Phe or Trp at the P2 site was apparent. Contrary to previous studies (Backes et al. 2000; Harris et al. 2000), we did not see a clear preference for basic residues at P4 when Lys occupied the P1 site. Indeed, five of the seven sequences hydrolysed at the highest rate contained Phe or Val at this position. Placing Arg as the P1 Table 1: Design of Sparse Matrix Library of Peptides P1 P2 P3 K W>F>Y Q>A K F>Y>W T>n K/R F/Y/N M/Q K/R F/Y/W M(O2)/Q/T

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P4 K>R>Q>F>A K > n > V/F/I K/R/ M(O2)/V/F

Reference (Harris et al. 2000) (Backes et al. 2000) (Gosalia et al. 2005) SML

residue resulted in more restricted preferences at the other subsites, with reduced cleavage of sequences having Trp at the P2 site in particular. Additionally, Met(O2) and basic residues were relatively more favoured at the P3 and P4 sites respectively when combined with Arg at the P1 site. These findings confirm the occurrence of cooperativity between the subsites of plasmin as has previously been suggested by a study using two PS-SCLs with either Arg or Lys at the P1 site (Gosalia et al. 2005). As a consequence, substrates containing Lys at P1 were cleaved at a 43% higher rate on average although sequences cut at the highest rate included Arg at the P1 site.

Figure 1: Amidolytic activity of plasmin against a sparse matrix library of peptide-pNA substrates. The y axis represents the rate of plasmin substrate cleavage in mOD/min at 405 nm. Amino acid sequences are labelled as: P1 residues, y-axis; P2 residues, above graphs; P4 and P3 residues, x-axis. Data is represented as mean ± SEM from three independent experiments.

Plasmin most efficiently cleaves substrates with Arg at the P1 site Kinetic constants were determined for selected substrates to further guide design of plasmin inhibitors. Sequences were selected as to include both those hydrolysed at a high rate and a diverse range (Table 2). Substrates with Arg rather than Lys at the P1 site were generally

194

cleaved more efficiently as indicated by higher kcat/KM. Indeed, the P1 Lys peptide with the highest kat/KM (Ac-FM(O2)YKpNA) was only cleaved with half the catalytic efficiency to that of the P1 Arg peptide with highest kcat/KM (Ac-RM(O2)YRpNA). Contrary to previous findings (Backes et al. 2000), it appeared that the P3 residue made a substantial contribution to the catalytic efficiency of cleavage since the kcat/KM values were considerably higher for all five sequences that included Met(O2) at the P3 site. Overall, there was a high degree of correlation between the rates of hydrolysis from the SML screen and the Kcat values of the purified and mass determined substrates. The sequence with the highest kcat/KM value (Ac-RM(O2)YRpNA) was selected for use in all subsequent plasmin assays. Previous PS-SCL studies (Backes et al. 2000; Harris et al. 2000; Gosalia et al. 2005) and the MEROPS peptidase database specificity matrices (merops.sanger.ac.uk (Rawlings 2009)) suggest that factor IXa and pKLK are the plasma proteases with most similar substrate preference to plasmin. Consequently, these proteases were used to evaluate the selectivity of substrate cleavage. pKLK showed a strong preference for P4 Arg compared to Lys as indicated Table 2: Kinetic Constants of Peptide Substrates Enzyme Peptide Substrate Theoretical Mass P1 Arg Series Plasmin Ac-KM(O2)YRpNA 790.99 Plasmin Ac-RM(O2)YRpNA 819.00 Plasmin Ac-KM(O2)FRpNA 774.99 Plasmin Ac-VQYRpNA 726.94 Plasmin Ac-RQFRpNA 767.94 Plasmin Ac-RM(O2)WRpNA 842.04 pKLK Ac-KM(O2)YRpNA pKLK Ac-RM(O2)YRpNA pKLK Ac-KM(O2)FRpNA pKLK Ac-VQYRpNA pKLK Ac-RQFRpNA pKLK Ac-RM(O2)WRpNA P1 Lys Series Plasmin Ac-FM(O2)YKpNA 781.98 Plasmin Ac-RQWKpNA 778.96 Plasmin Ac-KTFKpNA 684.89 Plasmin Ac-VQYKpNA 698.87 Plasmin Ac-KQWKpNA 750.95

Determined Mass

KM (μM)

Kcat (s-1)

Kcat/KM (M-1 s-1)

791.78 819.72 776.07 728.01 769.07 843.07 -

61.3 ± 5.3 30.2 ± 1.2 42.6 ± 2.1 109.1 ± 4.0 64.3 ± 3.5 23.1 ± 1.8 361.2 ± 39.1 81.0 ± 4.3 267.0 ± 20.7 69.3 ± 4.1 87.1 ± 4.8 61.4 ± 5.6

41.1 ± 0.3 30.5 ± 1.0 34.6 ± 0.4 24.8 ± 0.3 24.8 ± 0.40 20.6 ± 0.4 19.0 ± 1.1 13.0 ± 0.2 21.5 ± 0.8 9.2 ± 0.2 18.9 ± 0.3 10.7 ± 0.3

67.0 x 10-4 -4 100.9 x 10 -4 81.3 x 10 -4 22.7 x 10 -4 38.5 x 10 -4 89.2 x 10 -4 5.3 x 10 -4 16.1 x 10 -4 8.0 x 10 -4 13.3 x 10 -4 21.7 x 10 -4 17.4 x 10

782.97 780.11 685.94 699.79 752.27

63.4 ± 3.8 99.1 ± 10.2 236.2 ± 20.2 136.2 ± 9.0 85.6 ± 5.2

30.07 ± 0.54 27.35 ± 0.96 26.07 ± 0.99 25.91 ± 0.64 24.68 ± 0.49

48.4 x 10-4 27.6 x 10-4 11.0 x 10-4 19.0 x 10-4 28.8 x 10-4

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by a kcat/KM ratio of 3.06 for Ac-RM(O2)YRpNA and Ac-KM(O2)YRpNA while not appearing to have a particular partiality for any of the aromatic P2 residues. The sequence Ac-KM(O2)YRpNA appeared most specific to plasmin compared to pKLK as indicated by the highest kcat/KM ratio while the substrate with the highest pKLK kcat/KM value Ac-RQFRpNA was used in subsequent assays for this enzyme. In contrast, neither of the peptide-pNAs assayed were cleaved by factor IXa (data not shown). These findings are contrary to a recent PS-SCL screen of factor IXa that indicated a substrate preference of P1 Arg, P2 Phe/Tyr and P3 Met/Glu (Gosalia et al. 2005) and further highlights the need to verify results from PS-SCL screens using individually synthesised peptides. However, the substrate NGRpNA has previously been used in factor IXa assays (Yang et al. 2006) and the similar sequence QGRpNA was readily hydrolysed and was used in subsequent factor IXa assays.

Peptide aldehydes based on substrate sequences are potent plasmin inhibitor The sequences cleaved with highest kcat/KM (Ac-KM(O2)YK, Ac-RM(O2)YR and Ac-KM(O2)FR) were selected as candidate plasmin peptide aldehyde inhibitors. Both Ac-KM(O2)YK-H and AcRM(O2)YR-H inhibited plasmin effectively with IC50 values of 8.8 nM (Ki = 3.08 nM) and 9.9 nM (Ki = 3.25 nM) respectively, while Ac-KM(O2)FR-H performed more poorly (Table 3). To determine the contribution from the various residues to binding affinity, the peptide aldehydes Ac-KMYK-H, Ac-RMYK-H, Ac-M(O2)YK-H and Ac-MYR-H were also screened against plasmin. Replacing the P3 methionine sulfone with methionine or removing the P4 basic residues reduced potency of inhibition with around 10- to 30-fold while both changes at once caused a 300-fold decrease in affinity. This suggested a similar degree of contribution from the P3 and P4 residues to binding affinity.

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Table 3: Kinetic Constants of Plasmin Inhibitors Enzyme Inhibitor Theoretical Determined Mass Mass Plasmin Ac-KMYR-H 622.77 624.00 Plasmin Ac-RMYR-H 650.78 651.98 Plasmin Ac-M(O2)YR-H 526.60 527.74 Plasmin Ac-MYR-H 494.60 495.32 Plasmin Ac-KM(O2)FR-H 638.77 639.62 Plasmin Ac-RM(O2)YR-H 682.78 683.96 Plasmin Ac-KM(O2)YR-H 654.77 656.04 Plasmin Aprotinin Trypsin Ac-KM(O2)YR-H Trypsin Aprotinin pKLK Ac-KM(O2)YR-H pKLK Aprotinin Thrombin Ac-KM(O2)YR-H Factor IXa Ac-KM(O2)YR-H KLK4 Ac-KM(O2)YR-H -

IC50 (nM) 102.6 ± 8.4 310.0 ± 8.8 186.6 ± 17.7 2681 ± 272 108.1 ± 5.6 9.9 ± 1.1 8.8 ± 0.6 95. 0 ± 2.7 366.1 ± 26.0 > 10,000 > 10,000 > 10,000

Substrate (100 μM) Ac-RM(O2)YRpNA Ac-RM(O2)YRpNA Ac-RM(O2)YRpNA Ac-RM(O2)YRpNA Ac-RM(O2)YRpNA Ac-RM(O2)YRpNA Ac-RM(O2)YRpNA Bz-FVRpNA Ac-RQFRpNA Bz-FVRpNA Ac-QGRpNA Bz-FVRpNA

Ki (nM) 3.08 ± 0.26 3.25 ± 0.25 a 0.18 ± 0.06 0.02 ± 0.003a 78.6 ± 7.3 13.4 ± 2.4a -

a

Data from reference (Delaria et al. 1997)

To assess the specificity of inhibition, the most potent inhibitor Ac-KM(O2)YK-H was screened against trypsin, pKLK, thrombin, factor IXa, kallikrein related peptidase 4 and αchymotrypsin. Trypsin and pKLK were inhibited with IC50 values of 95 nM and 366 nM, respectively, with no inhibition of the other proteases up to 10,000 nM. However, inhibition of cleavage of small colorimetric peptides does not always translate to inhibition of protein proteolysis (Swedberg et al. 2009). Consequently, the potency and selectivity of the inhibitors was evaluated against the protein substrate fibrinogen. Plasmin digestion of fibrinogen was completely blocked at 250 nM for both Ac-KM(O2)YK-H and Ac-RM(O2)YR-H (Figure 2A) while neither inhibitor substantially inhibited trypsin fibrinogen digestion up to 5,000 nM (Figure 2B).

Peptide aldehyde inhibitors block fibrinolysis In vitro During fibrinolysis plasmin degrades fibrin rather than its precursor fibrinogen. Therefore, an in vitro fibrin formation and dissolution assay was used to determine the ability of Ac-KM(O2)YK-H and Ac-RM(O2)YR-H to impede fibrinolysis. Since fibrin is insoluble, its formation and degradation can be monitored by the scattering of light as previously described (Wolberg et al. 197

Figure 2: Inhibition of serine protease proteolytic

activity

by

peptide

aldehydes. Examination of fibrinogen proteolysis by plasmin and trypsin using SDS-PAGE. Inhibition of (A) plasmin and (B) trypsin in the presence of increasing concentration

of

KM(O2)YR-H

and

RM(O2)YR-H. Bands were visualised with Coomassie blue staining after resolving on 10% polyacrylamide gels. Images are representative of three separate experiments.

2002). Similar methods have also been used to evaluate fibrinolysis and anti-fibinolytic compounds in human plasma (Kim et al. 2007; Sperzel et al. 2007). The standard fibrinolysis inhibitor aprotinin was used as a benchmark for inhibition efficacy. Complete attenuation of fibrinolysis was achieved using 250 nM of either aldehyde inhibitor which is equivalent to 0.164 μg/ml and 0.171 μg/ml for Ac-KM(O2)YK-H and Ac-RM(O2)YR-H respectively (Figure 3A and B). In the case of aprotinin, 31.25 nM inhibitor or 0.204 μg/ml was required to attain the same effect as for the peptide aldehydes (Figure 3C).

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Figure 3: Inhibition of in vitro fibrinolysis by peptide aldehyde inhibitors. Fibrin formation by thrombin and subsequent degradation by plasmin was monitored at 400 nm over 3 hours. The ability of peptide aldehyde inhibitors to prevent fibrinolysis was assessed using various inhibitor concentrations of (A) KM(O2)YR-H (0-250 nM), (B) RM(O2)YR-H (0-500 nM) and (C) aprotinin (031.25 nM). Data is represented as mean ± SEM from three independent experiments.

Discussion This study has fully defined plasmin’s extended peptide substrate specificity and has shown that cooperativity occurs between the various substrate binding sites of plasmin. Furthermore,

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highly preferred peptide cleavage sequences translated to potent aldehyde inhibitors of plasmin that attenuated fibrinolysis in vitro with an efficacy comparable to aprotinin, making them attractive candidates for further therapeutic development. Other studies investigating plasmin’s peptide substrate specificity have focused on screening combinatorial peptide libraries containing pools of mixed peptides without fully validating the results using individually synthesised peptides (Backes et al. 2000; Harris et al. 2000; Gosalia et al. 2005). It has previously been shown that although PS-SCL gives a general indication of enzyme subsite preferences, optimal peptide sequences may be overlooked using this method (Swedberg et al. 2009). This problem can be resolved by screening against a noncombinatorial SML of peptides more suited to reveal potential cooperativity between various substrate binding sites (Swedberg et al. 2009; Swedberg et al. 2010). This is of particular importance when designing peptide or peptide mimetic protease inhibitors since optimal contact across all substrate binding sites is more likely to produce potent and selective inhibitors. Currently, clinically available antifibrinolytics in thr form of lysine analogues are nonspecific and low affinity plasmin inhibitors. These are commonly administrated using 1–15 g loading doses at induction of anesthesia (Mannucci et al. 2007), which is equivalent to around 0.4-6 mg/ml or 0.3-46 mM in plasma for an individual with an average blood volume of 4.5 L (Tietz 1995) and a plasma content of 55%. In comparison, a recommended loading dose of aprotinin has been estimated to 280 mg or 0.11 mg/ml plasma with an optional pump priming dose of another 280 mg (Mannucci et al. 2007) or 0.11 mg/ml plasma, totalling a plasma concentration of 0.475 μM. This correlates well with in vitro plasma fibrinolysis assays for aprotinin where 0.3 μM completely blocks fibrinolysis (Sperzel et al. 2007). In contrast, 100 μM TXA is needed in the same assay to achieve equivalent inhibition which is 333 times higher

200

molar concentration than that required for aprotinin. The most potent inhibitors in this study prevented in vitro fibrinolysis at a comparable level to aprotinin when used at eight times higher molar concentration equating to a lower w/v concentration. However, relative efficacy does not always translate directly from an in vitro fibrinolysis assay to in vivo bleeding time reduction (Sperzel et al. 2007) and the use of plasmin peptide aldehyde inhibitors requires further in vivo testing to evaluate an effective dosing range. Since plasminogen circulates at a concentration of 2 μM (Collen and Lijnen 1991), even potent inhibitors need to be administered at a concentration considerably higher than the inhibition constant (Aprotinin Ki = 0.18 nM (Delaria et al. 1997)). This presents a particular challenge in terms of achieving specificity of inhibition over other serine proteases present in plasma. The most potent inhibitor from this study is also likely to inhibit pKLK if administrated at a dose required for appreciable in vivo reduction of blood loss. However, pKLK has a central role in initiation of the contact activation pathway (Colman and Schmaier 1997; Campbell 2001) and activation of the kallikrein-kinin system produces elevated brandykin release, resulting in complement and neutrophil activation (Wachtfogel et al. 1993; McEvoy et al. 2007). This is of particular importance during cardiopulmonary bypass (CPB) surgery where contact with the artificial surfaces of the heart-lung machine initiates the contact pathway and systemic inflammatory response, a major contributor to organ damage during CPB (Levy and Tanaka 2003; Rubens and Mesana 2004; McEvoy et al. 2007). Consequently, dual inhibition of plasmin and pKLK may be desirable for an antifibrinolytic agent (Dietrich et al. 2009). Non-specific inhibitors have an inherent disadvantage since interaction with many physiological components is more likely to produce further variability in response across a diverse population of individuals. Therefore, the availability of individual specific regulators of coagulation, complement activation and fibrinolysis would be ideal as it would allow for the

201

tailored treatment for individuals. One way of increasing the specificity of inhibitors described in this study involves engagement of the prime side substrate binding sites (S’) of plasmin. A recent study indicates that plasmin has a preference at the S2’ site for basic residues that is unique among the serine proteases within the circulatory system (Bajaj et al. 2010). Converting peptide aldehyde inhibitors to boronic acid inhibitors allows for engagement of the protease prime side and has been used to increase the potency of inhibition of kallikrein-related peptidase 3 (KLK3/PSA) over 100-fold with enhanced selectivity (LeBeau et al. 2008). Since peptide aldehydes have a known crossreactivity with other classes of proteases they have limited use as therapeutic agents (Meng et al. 1999; Kim and Crews 2004). Consequently, combining the high affinity plasmin P1-P4 sequences presented here with a P2’ basic residue and boronic acid as the transition state analogue may well produce a second generation of more potent and selective plasmin inhibitors with a greater therapeutic potential. In conclusion, this study has shown that although PS-SCL screening is an essential tool when defining proteases substrate specificity, subsequent deconvolution of the results using a SML is needed to harness the full potential of PS-SCL. Bringing these two methods together resulted in some of the most potent small molecule plasmin inhibitors ever produced, that also blocked fibrinolysis in vitro with an efficacy comparable to aprotinin.

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Cosgrove, D. M., 3rd, B. Heric, B. W. Lytle, P. C. Taylor, R. Novoa, L. A. Golding, R. W. Stewart, P. M. McCarthy and F. D. Loop (1992). "Aprotinin therapy for reoperative myocardial revascularization: a placebo-controlled study." Ann Thorac Surg 54(6): 1031-6. Delaria, K. A., D. K. Muller, C. W. Marlor, J. E. Brown, R. C. Das, S. O. Roczniak and P. P. Tamburini (1997). "Characterization of placental bikunin, a novel human serine protease inhibitor." J Biol Chem 272(18): 12209-14. Dietrich, W., S. Nicklisch, A. Koster, M. Spannagl, H. Giersiefen and A. van de Locht (2009). "CU2010 - a novel small molecule protease inhibitor with antifibrinolytic and anticoagulant properties." Anesthesiology 110(1): 123-30. Fergusson, D. A., P. C. Hebert, C. D. Mazer, S. Fremes, C. MacAdams, J. M. Murkin, K. Teoh, P. C. Duke, R. Arellano, M. A. Blajchman, J. S. Bussieres, D. Cote, J. Karski, R. Martineau, J. A. Robblee, M. Rodger, G. Wells, J. Clinch and R. Pretorius (2008). "A comparison of aprotinin and lysine analogues in high-risk cardiac surgery." N Engl J Med 358(22): 2319-31. Goodnough, L. T. and A. Shander (2007). "Blood management." Arch Pathol Lab Med 131(5): 695-701. Gosalia, D. N., C. M. Salisbury, J. A. Ellman and S. L. Diamond (2005). "High throughput substrate specificity profiling of serine and cysteine proteases using solution-phase fluorogenic peptide microarrays." Mol Cell Proteomics 4(5): 626-36. Gosalia, D. N., C. M. Salisbury, D. J. Maly, J. A. Ellman and S. L. Diamond (2005). "Profiling serine protease substrate specificity with solution phase fluorogenic peptide microarrays." Proteomics 5(5): 1292-8. Harris, J. L., B. J. Backes, F. Leonetti, S. Mahrus, J. A. Ellman and C. S. Craik (2000). "Rapid and general profiling of protease specificity by using combinatorial fluorogenic substrate libraries." Proc Natl Acad Sci U S A 97(14): 7754-9. Henry, D., P. Carless, D. Fergusson and A. Laupacis (2009). "The safety of aprotinin and lysinederived antifibrinolytic drugs in cardiac surgery: a meta-analysis." CMAJ 180(2): 183-93. Hoylaerts, M., D. C. Rijken, H. R. Lijnen and D. Collen (1982). "Kinetics of the activation of plasminogen by human tissue plasminogen activator. Role of fibrin." J Biol Chem 257(6): 2912-9. Kagoma, Y. K., M. A. Crowther, J. Douketis, M. Bhandari, J. Eikelboom and W. Lim (2009). "Use of antifibrinolytic therapy to reduce transfusion in patients undergoing orthopedic surgery: a systematic review of randomised trials." Thromb Res 123(5): 687-96. Karkouti, K., W. S. Beattie, K. M. Dattilo, S. A. McCluskey, M. Ghannam, A. Hamdy, D. N. Wijeysundera, L. Fedorko and T. M. Yau (2006). "A propensity score case-control comparison of aprotinin and tranexamic acid in high-transfusion-risk cardiac surgery." Transfusion 46(3): 327-38. 204

Kim, P. Y., R. J. Stewart, S. M. Lipson and M. E. Nesheim (2007). "The relative kinetics of clotting and lysis provide a biochemical rationale for the correlation between elevated fibrinogen and cardiovascular disease." J Thromb Haemost 5(6): 1250-6. Koh, M. B. and B. J. Hunt (2003). "The management of perioperative bleeding." Blood Rev 17(3): 179-85. Koster, A. and U. Schirmer (2010). "Re-evaluation of the role of antifibrinolytic therapy with lysine analogs during cardiac surgery in the post aprotinin era." Curr Opin Anaesthesiol 24(1): 92-97. Kunitz, M. and J. H. Northrop (1936). "Isolation from beef pancreas of crystalline trypsinogen, trypsin, a trypsin inhibitor, and an inhibitor-trypsin compound." J Gen Physiol 19(6): 991-1007. LeBeau, A. M., P. Singh, J. T. Isaacs and S. R. Denmeade (2008). "Potent and selective peptidyl boronic acid inhibitors of the serine protease prostate-specific antigen." Chem Biol 15(7): 665-74. Lerch, P. G., E. E. Rickli, W. Lergier and D. Gillessen (1980). "Localization of individual lysinebinding regions in human plasminogen and investigations on their complex-forming properties." Eur J Biochem 107(1): 7-13. Levy, J. H. (2008). "Pharmacologic methods to reduce perioperative bleeding." Transfusion 48(1 Suppl): 31S-38S. Levy, J. H. and K. A. Tanaka (2003). "Inflammatory response to cardiopulmonary bypass." Ann Thorac Surg 75(2): S715-20. Lucas, M. A., L. J. Fretto and P. A. McKee (1983). "The relationship of fibrinogen structure to plasminogen activation and plasmin activity during fibrinolysis." Ann N Y Acad Sci 408: 71-91. Mangano, D. T., I. C. Tudor and C. Dietzel (2006). "The risk associated with aprotinin in cardiac surgery." N Engl J Med 354(4): 353-65. Mannucci, P. M. and M. Levi (2007). "Prevention and treatment of major blood loss." N Engl J Med 356(22): 2301-11. McEvoy, M. D., S. T. Reeves, J. G. Reves and F. G. Spinale (2007). "Aprotinin in cardiac surgery: a review of conventional and novel mechanisms of action." Anesth Analg 105(4): 949-62. Meng, L., R. Mohan, B. H. B. Kwok, M. Elofsson, N. Sin and C. M. Crews (1999) Epoxomicin, a potent and selective proteasome inhibitor, exhibits in vivo antiinflammatory activity. PNAS 96(18): 10403-08.

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Okamoto, S., T. Nakajima, U. Okamoto, H. Watanabe, Y. Iguchi, T. Igawa, C. Chien and T. Hayashi (1959). "A suppressing effect of e-amino-n-caproic acid on the bleeding of dogs, produced with the activation of plasmin in the circulatory blood." Keio J Med 8: 247. Okamoto, S., S. Sato, Y. Tanaka and U. Okamoto (1964). "An active sterioisomer (trans-form) of amcha and its and its and its antifibinolytic (antiplasmic) action in vitro and in vivo." Keio J Med 13(4): 177-85. Ramsay, A. J., Y. Dong, M. L. Hunt, M. Linn, H. Samaratunga, J. A. Clements and J. D. Hooper (2008). "Kallikrein-related peptidase 4 (KLK4) initiates intracellular signaling via protease-activated receptors (PARs). KLK4 and PAR-2 are co-expressed during prostate cancer progression." J Biol Chem 283(18): 12293-304. Rawlings, N. D. (2009). "A large and accurate collection of peptidase cleavages in the MEROPS database." Database (Oxford) 2009: bap015. Rijken, D. C. and H. R. Lijnen (2009). "New insights into the molecular mechanisms of the fibrinolytic system." J Thromb Haemost 7(1): 4-13. Robbins, K. C., L. Summaria, B. Hsieh and R. J. Shah (1967). "The peptide chains of human plasmin. Mechanism of activation of human plasminogen to plasmin." J Biol Chem 242(10): 2333-42. Royston, D. (1998). "Aprotinin versus lysine analogues: the debate continues." Ann Thorac Surg 65(S4): 9-19. Rubens, F. D. and T. Mesana (2004). "The inflammatory response to cardiopulmonary bypass: a therapeutic overview." Perfusion 19(S1): 5-12. Saito, H., S. M. Hamilton, A. S. Tavill, L. Louis and O. D. Ratnoff (1980). "Production and release of plasminogen by isolated perfused rat liver." Proc Natl Acad Sci U S A 77(11): 683740. Schneider, E. L. and C. S. Craik (2009). "Positional scanning synthetic combinatorial libraries for substrate profiling." Methods Mol Biol 539: 59-78. Shaw, A. D., M. Stafford-Smith, W. D. White, B. Phillips-Bute, M. Swaminathan, C. Milano, I. J. Welsby, S. Aronson, J. P. Mathew, E. D. Peterson and M. F. Newman (2008). "The effect of aprotinin on outcome after coronary-artery bypass grafting." N Engl J Med 358(8): 784-93. Sperzel, M. and J. Huetter (2007). "Evaluation of aprotinin and tranexamic acid in different in vitro and in vivo models of fibrinolysis, coagulation and thrombus formation." J Thromb Haemost 5(10): 2113-8. Swedberg, J. E., S. J. de Veer and J. M. Harris (2010). "Natural and engineered kallikrein inhibitors: an emerging pharmacopoeia." Biol Chem 391(4): 357-74. 206

Swedberg, J. E., L. V. Nigon, J. C. Reid, S. J. de Veer, C. M. Walpole, C. R. Stephens, T. P. Walsh, T. K. Takayama, J. D. Hooper, J. A. Clements, A. M. Buckle and J. M. Harris (2009). "Substrate-guided design of a potent and selective kallikrein-related peptidase inhibitor for kallikrein 4." Chem Biol 16(6): 633-43. Tietz, N. W. (1995). Clinical guide to laboratory tests. Philadelphia, W.B. Saunders. Wachtfogel, Y. T., U. Kucich, C. E. Hack, P. Gluszko, S. Niewiarowski, R. W. Colman and L. H. Edmunds, Jr. (1993). "Aprotinin inhibits the contact, neutrophil, and platelet activation systems during simulated extracorporeal perfusion." J Thorac Cardiovasc Surg 106(1): 1-9; discussion 9-10. Wolberg, A. S., D. A. Gabriel and M. Hoffman (2002). "Analyzing fibrin clot structure using a microplate reader." Blood Coagul Fibrinolysis 13(6): 533-9. Yang, L., K. Gopalakrishna, C. Manithody and A. R. Rezaie (2006). "Expression, purification and characterization of factor IX derivatives using a novel vector system." Protein Expr Purif 50(2): 196-202. Zhang, L., D. Seiffert, B. J. Fowler, G. R. Jenkins, T. C. Thinnes, D. J. Loskutoff, R. J. Parmer and L. A. Miles (2002). "Plasminogen has a broad extrahepatic distribution." Thromb Haemost 87(3): 493-501.

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CHAPTER 8

Conclusions

208

8

Conclusions

The studies presented in this thesis demonstrate the power of coupling peptide library screening with molecular modelling to identify potent and selective inhibitors of serine proteases. It also highlights issues with the frequently employed PS-SCL technique and offers the SML strategy as a way of addressing the former’s shortcomings. Furthermore, the findings presented clarify the divide between serine protease selectivity and inhibition when acting on protein substrates as opposed to shorter peptides. This is highly significant given the widespread tendency in the field to regard sequences discovered by PS-SCL to be a guide to identify in vivo protein substrates and the fact that inhibition of peptide hydrolysis is directly equivalent to inhibition of protein substrates. The thesis findings do, however, support the common contention that efficient substrate sequences may be converted to efficient inhibitors. This concluding chapter will discuss the possibilities and limitations of the techniques developed during the research project in a broader context of current literature.

8.1

Intermolecular and intramolecular subsite cooperativity

Subsite cooperativity focuses on a protease’s active site and needs to be distinguished from allosteric cooperativity where binding of a molecule to a site of the protease distant from the active site changes the binding affinity for a substrate (Ng et al. 2009). Subsite cooperativity may be intermolecular where the contribution of binding affinity from one residue is directly dependent on its neighbours. Another form of subsite cooperativity is intramolecular where neighbouring residues of the substrate interact to primarily modulate the rate of scissile bond cleavage. Apart from these distinct cases, there are many instances where either intramolecular or intermolecular subsite cooperativity affects both binding affinity and the rate of substrate hydrolysis. For example, sequences that are highly preferred by proteases because 209

of intermolecular cooperativity have optimised subsite occupancy and higher binding affinity, resulting in a high rate of hydrolysis. In this case, binding affinity is causative of the higher rate of cleavage. For other substrate sequences, intramolecular cooperativity between amino acid side chains may directly affect the rate of cleavage of the scissile bond by modulating the stability of the acyl-enzyme intermediate (Chapter 4). A substrate with a more stable acylenzyme intermediate has a higher binding affinity as a result of a reduced rate of terminal cleavage. For the short peptides commonly used in peptide libraries which only probe either the primed or non-primed subsites of a protease, amino acids are not present on both sides of the scissile bond. Therefore the subsite cooperativity seen for peptide substrates in Chapter 3, Chapter 5 and Chapter 7 are primarily intermolecular. In the case of circular peptides or proteins, the distinction between intermolecular and intramolecular subsite cooperativity is less defined and difficult to determine experimentally. Nonetheless, the terminology is useful when discussing protease substrate and inhibitor design to indicate whether amino acid substitutions are made targeting binding to determinants of the protease or intrinsic properties of the substrate/inhibitor.

8.2

Limitations of the positional scanning synthetic combinatorial library method

The development of positional scanning synthetic combinatorial library (PS-SCL) screening has rapidly accelerated the search for antibody, receptor and enzyme ligands (Pinilla et al. 1992; Dooley et al. 1993; Dooley and Houghten 1993; Houghten and Dooley 1993) and has identified numerous high affinity proteases peptide substrates (Thornberry et al. 1997; Harris et al. 1998; Harris et al. 2000; Park et al. 2006) and inhibitors (Harris et al. 2001; Choe et al. 2006; Cuerrier et al. 2007; Fugere et al. 2007). However, there are commonly occurring misconceptions

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regarding the limitations of the PS-SCL method that may result in suboptimal data interpretation in addition to preventing this technique from being realised to its full potential. There is a wide appreciation that various amino acids react with differential rates during solid phase synthesis (Bayer and Hagenmaier 1968; Ragnarsson et al. 1971; Ragnarsson et al. 1974). Consequently, methods of compensation have been developed by adjusting the relative molar concentrations of amino acids to produce equimolar coupling efficiency. These ‘isokinetic’ mixtures of amino acids were determined by analysing the reaction rates for synthesis of various dipeptides based on total amino acid content post syntheses (Pinilla et al. 1992; Dooley et al. 1993; Dooley et al. 1993; Houghten et al. 1993; Kramer et al. 1993; Ostresh et al. 1994; Ivanetich and Santi 1996) and are commonly used. However, more recently it has been demonstrated by quantification of purified dipeptides that the previously published isokinetic mixtures could not have produced near equimolar representation of all amino acid sequences (variation ± 36.5%) (Boutin et al. 1997). Consequently, isokinetic mixtures may result in all amino acids being present in similar amounts without complete sequence representation. Additionally, the isokinetic synthesis strategy relies on an assumption that reaction rates when coupling amino acids to single solid-phase bound residues are equivalent to those involving longer peptide sequences, even though it is well known that that some sequences are particularly difficult to synthesise (Hyde et al. 1994; Dettin et al. 1997; Henkel and Bayer 1998; Larsen and Holm 1998; McNamara et al. 2000; Bacsa et al. 2008). This issue was highlighted by one study which used liquid chromatography/mass spectrometry to quantify the members of a tetra peptide combinatorial library (Arg, Gln, Gly and Phe; that is 256 theoretical compounds) which demonstrated representational variation of -50% and +300% from the target equal molarity (Boutin et al. 1997). Moreover, more than 25% of all theoretical sequences were

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absent in the combinatorial library while equimolar mixtures of the same peptides synthesised individually were accurately quantified. Further evidence against complete and equal amino acid sequence representation occurring in PS-SCLs is provided by the lack of reproducibility associated with the technique. A number of studies that employed similar synthesis methods including isokinetic mixtures and a fixed P1 residue have produced widely varying results. In the case of plasmin, the optimal cleavage site has been suggested as KQWK (Harris et al. 2000), KTFK (Backes et al. 2000) and MYK (Gosalia et al. 2005) while for KLK4 preferred sequences were found to be IQQR (Matsumura et al. 2005), IVQR (Debela et al.) and ISQR (Borgono et al. 2007). Furthermore, two PS-SCL screens of KLK5 disagreed regarding all of the P2-P4 sites and predicted the divergent optimal sequences: YRFR (Borgono et al. 2007) and GYSR (Debela et al. 2006). This demonstrates that although isokinetic mixtures of amino acids are employed during synthesis, variation in representation of sequences is still prevalent and needs to be taken into account when interpreting the data produced by combinatorial libraries. Despite variation in reaction rates between different residues, synthesis of PS-SCLs relying on isokinetic mixtures of amino acids is still commonplace (Backes et al. 2000; Harris et al. 2000; Harris et al. 2001; Mathieu et al. 2002; Leiting et al. 2003; Cotrin et al. 2004; Mahrus et al. 2004; Li et al. 2005; Matsumura et al. 2005; Schneider et al. 2009) while being described as producing libraries containing equimolar mixtures of amino acids that include all possible theoretical sequences (Backes et al. 2000; Pinilla et al. 2003; Matsumura et al. 2005; Debela et al. 2006; Diamond 2007; Schneider et al. 2009). A representative example is provided by one PS-SCL user describing the library content as “Each sublibrary consisted of 361 substrates/well for a total of 130321 individual substrates” (Borgono et al. 2007) which highlights the degree of misconception regarding the contents of these libraries. Consequently, greater awareness of

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the limitations associated with production of SC-SCL is needed together with more accurate post-screening data verification and analysis. Optimal interpretation of PS-SCL data is further hindered by an assumption that the biological contributions of substrate and protein binding sites are independent of each other; in reality, extensive subsite cooperativity takes place between the various sites (Ng et al. 2009). During the early work investigating KLK4s substrate preference (Chapter 3), it was found that the sequence IQQR predicted by PS-SCL to be the optimal cleavage site (Matsumura et al. 2005) was not cleaved at an appreciable rate. Similarly, a study of membrane-type serine protease 1 found that the sequence KRSK was suggested by PS-SCL to be an optimal cleavage site. However, dibasic sequences were completely absent in a subsequent phage display analysis (Takeuchi et al. 2000). These results indicated that the P3 and P4 basic residues bound to the same determinant of the protease erased the distinction between the substrate binding sites while producing false positives. Simmilarly, a PS-SCL screening of KLK6 suggested a basic residue preference for both of the P1 and P2 sites (Debela et al. 2006) while phage display methods failed to find a single sequence containing a basic P2 amino acid, with a strong selection for aromatic residues at this site (Li et al. 2008). Intramolecular substrate residue interactions may also occur in a way that either prevents detection of certain sequences or produces false positives. For example Arg or Lys in one position and Glu or Asp in another can only occur at the same time in 10% of sequences considering two sites in a PS-SCL library including variable 20 amino acids. Therefore, a great majority of sequences allow for interaction between the basic and acidic side chain moieties with the protease. However, when combined in an individually synthesised peptide they may well form an internal salt bridge and thus mask the side chain functionalities from the substrate binding sites. This type of interaction occurs in the wild-type SFTI to both stabilise the

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β-sheet for enhanced potency while avoiding presenting any P4 residue allowing for its broad range activity (Chapter 4). Consequently, other methods are needed following PS-SCL screening to reveal bias due to intermolecular subsite cooperativity in addition to unequal sequence representation and thereby prevent false positives or omission of highly preferred peptide substrate sequences.

8.3

The sparse matrix library screening method for deconvoluting PS-SCL data

Despite being limited by variations in sequence representation and an inability to recapitulate subsite cooperativity, PS-SCL does provide a starting point for optimising subsite occupancy. Therefore, while the PS-SCL screens may find high affinity substrates, this method most often fails to detect the sequence with the highest affinity possible. Previously, other researchers have tried to overcome this issue by screening against a few selected individually synthesised substrates (Backes et al. 2000; Harris et al. 2000; Harris et al. 2001; Mathieu et al. 2002; Leiting et al. 2003; Cotrin et al. 2004; Mahrus et al. 2004; Li et al. 2005; Matsumura et al. 2005; Debela et al. 2006; Borgono et al. 2007; Schneider et al. 2009). The data presented here suggest that a systematic investigation using individually synthesised sequences involving a number of preferred residues for each subsite is a better approach. Combining these amino acids in all possible ways in a sparse matrix library (SML) enables a second screen that may reveal both intermolecular subsite cooperativity and bias created by variations in concentrations between sequences inherent in the PS-SCL scheme. A prominent example of this involves PS-SCL screens of KLK4 where the sequence that was hydrolysed at the highest rate out of all studies still had kcat and kcat/KM values seven and two times lower respectively than the optimal sequence determined by the SML (Chapter 3). The most likely reasons for these different findings are variations in concentrations of 214

sequences in the PS-SCL in conjunction with intermolecular subsite cooperativity. For example, during this study it was found that synthesis of the most preferred sequence FVQR produced some of the lowest yields among the sequences in the KLK4 SML. Indeed, FVQR was among the sequences ( 10000 237.9 ± 5.9 1271 ± 38 > 10,000 > 10,000 > 10,000 177.7 ± 7.9 > 10,000

Substrate (100 μM) Ac-RM(O2)YRpNA Ac-RM(O2)YRpNA Ac-RM(O2)YRpNA Bz-FVRpNA Ac-RQFRpNA Bz-FVRpNA Ac-QGRpNA Bz-FVRpNA Bz-WpNA

Ki (nM) 55.5 ± 1.8 -

APPENDIX IV

Refereed publication: Plasmin Substrate Binding Site Cooperativity Guides the Design of Potent Peptide Aldehyde Inhibitors.

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Article pubs.acs.org/biochemistry

Plasmin Substrate Binding Site Cooperativity Guides the Design of Potent Peptide Aldehyde Inhibitors Joakim E. Swedberg and Jonathan M. Harris* Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland 4059, Australia

Due to copyright restrictions, this article is not available here. Please consult the hardcopy thesis available from QUT Library or view the published version online at: http://dx.doi.org/10.1021/bi201203y

© XXXX American Chemical Society

A

dx.doi.org/10.1021/bi201203y | Biochemistry XXXX, XXX, XXX−XXX

Abbreviations

253

Amino acid abbreviations Ala (A) – Alanine Arg (R) - Arginine Asn (N) - Asparagine Asp (D) - Aspartic Acid Cys (C) - Cyteine Glu (E) - Glutamic Acid Gln (Q) - Glutamine Gly (G) - Glycine His (H) - Histidine Ile (I) - Isoleucine Leu (L) - Leucine Lys (K) - Lysine Met (M) - Methionine Met (O2) (M(O2) - Methionine Sulfone Nor (n) - Norleucine Phe (F) - Phenylalanine Pro (P) - Proline Ser (S) - Serine Thr (T) - Threonine Trp (W) - Tryptophan Tyr (T) - Tyrosine Val (V) - Valine

254

Other abbreviations Å

Ångstrom, 10-10 m

α-AP

α-antiplasmin

Ac

Acetyl group

ACN

acetonitrile

AcOH

acetic acid

AR

androgen receptor

Boc

tert-butyloxycarbonyl

cAMP

cyclic adenosine monophosphate

CPB

cardiopulmonary bypass

DBU

1,8-Diazabicyclo [5.4.0]undec-7-ene

DCM

dichloromethane

DHT

dihydrotestosterone

DIC

N,N’-diisopropyl carbodiimide

DIPEA

N,N’-diisopropylethylamine

DMF

N,N’-dimethylformamide

DMSO

dimethylsulfoxide

DMEM

Dulbecco´s Modified Eagle’s Medium

EACA

ε-amino caproic acid

ECM

extracellular matix

EDTA

ethylenediaminetetraacetic acid

ELISA

enzyme linked immuno sorbent assay

eq

equivalent 255

EtOH

ethanol

FITC

fluorescein isothiocyanate

Fmoc

N-(9-fluorenyl)methoxycarbonyl

HATU

O-(7-Azabenzotriazol-1-yl)-N,N,N’,N’,-tetramethyluroniumhexafluorophosphat

HBTU

2-(1H-benzotriazol-1-yl)-1,1,3,3-tetramethyluroniumhexafluoro-phosphate

HEPES

N-(2-hydroxyethyl) piperazine-N´-(2-ethanesulfonic acid)

HOAt

1-hydroxy-7-azabenzotriazole

HOBt

1-hydroxybenzotriazol

HPLC

high-performance liquid chromatography

IC50

Inhibitior concentration giving 50% inhibition

kcat

Catalytic turnover constant

kDa

kilodaltons

Ki

Inhibition constant

KLK

kallikrein related peptidase

KM

Michaelis-Menten constant

LEKTI

lympho-epithelial kazal type inhibitor

LG

laminin G-like

λ

wave length

M

molar

MALDI

matrix-assisted laser desorption ionization

MeOH

methanol

mg

milligrams

MHC

major histocompatibility complex

min

minute 256

mM

millimolar

mmol

millimol

MMP

matrix metalloproteinase

MS

mass spectrometry

Mtt

4-methyltrityl

m/z

mass/charge ration

nm

nanometer

nM

nanomolar

nmol

nanomol

PAGE

polyacrylamide gel electrophoresis

P

protease binding site (non-primed side)

P'

protease binding site (primed side)

PAI

plasminogen activator inhibitor

PAR

protease activated receptor

PAS

Plasminogen Activation System

Pbf

2,2,5,7,8-pentamethyl-dihydrobenzofuran-5-sulfonyl

PBS

phosphate-buffered saline

PEG

polyethylene glycol

pKLK

plasma kallikrein

pNA

para-Nitroanilide

PS-SCL

positional scanning synthetic combinatorial library

PyBOP

(benzotriazol-1-yloxy)tripyrrolidinophosphonium hexafluorophosphate

RP

reversed phase

RSHBG

putative sex-hormone binding globuline cell surface receptor 257

RT

room temperature

s

seconds

S

substrate binding site (non-primed side)

S'

substrate binding site (primed side)

SBTI

soya bean trypsin inhibitor

sc

single chain

SDS

sodium dodecyl sulfate

SFTI-1

sunflower trypsin inhibitor

SHBG

sex-hormone binding globuline

SML

sparse matrix library

SPINK

Serine protease inhibitor kazal-type

SPPS

solid-phase peptide synthesis

t

time

TAFI

Thrombin activaTable fibrinolysis inhibitor

tBu

tert-butyl

tBuOH

tert-butyl alcohol

tc

two chain

TFA

trifluoroacetic acid

TFPI

tissue factor pathway inhibitor

TIS

triisopropylsilane

tPA

tissue plasminogen activator

Tris

Tris(hydroxymethyl)aminomethane

Trt

trityl

TXA

tranexamic Acid 258

UV

ultraviolet

uPA

urokinase plasminogen activator

uPAR

urokinase plasminogen activator receptor

µmol

micromol

µM

micromolar

V

volume

Vmax

maximum enzyme velocity

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