High throughput methodologies for systematic enzyme profiling

HIGH-THROUGHPUT METHODOLOGIES FOR SYSTEMATIC ENZYME PROFILING UTTAMCHANDANI MAHESH (B.Sc (Hons.), NUS) A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF BIOLOGICAL SCIENCES NATIONAL UNIVERSITY OF SINGAPORE 2007 Acknowledgements The skills I have learnt over the course of my scientific training have been inspired through the endearing guidance, patience and confidence of my supervisor, A/P Yao Shao Qin He has honed my scientific acumen, and ignited in me an inexorable passion for science and discovery - a blaze I hope to continuously fire throughout my life It is for his trust in me that I will be forever grateful - for letting me experience firsthand the rocky road of science, a path challenged with idealism and imagination, where reality and fiction blends into one My deepest appreciation is for Prof Yao - my teacher and mentor Having worked with so many individuals over the past few years, it will be impossible for me to adequately thank them all within the limited space of this section Lay Pheng, Souvik, Grace, Eunice, Rina, Marie, Dawn, Raja, Hu Yi, Huang Xuan, Zhu Qing, Wang Gang, Junqi, Wang Jun, Wei Lin, Hongyan, Elaine, Su Ling, Farhana, Candy, Liu Kai, Kitty, Mingyu, Peng Yu, Wu Hao, Haibin, Kalesh, in short, all of Yao Lab past and present! – I have known all of you for quite some time now (ranging from months to years), and I would like to take this opportunity to thank each of you for being such wonderful people to work and research with Thank you for the discussions, advice, understanding and support, but most of all, for the happy memories and lasting friendships The commitment of time in an undertaking as significant as a Ph.D takes precious moments away from those who are the closest Here no depth of gratitude can begin to acknowledge the support and understanding of my father, mother and sister I dedicate this thesis to them I would also like to thank the Defence Science and Technology Agency, DSTA and DSO National Laboratories for granting me sabbatical to pursue my Ph.D I also acknowledge kind support from NUS, through the NUS Research Scholarship and the President’s Graduate Fellowship i Table of Contents Page Chapter Introduction 1.1 Summary 1.2 The Nature of Enzymes – An Overview 1.2.1 1.2.1.1 Matrix Metalloproteases 1.2.2 Metalloproteases as Therapeutic Targets Anthrax Lethal Factor 1.3 Microplate Technology – The Advent of HTS 1.3.1 Assay Formats 1.3.2 Recent Advances and Developments 1.4 Microarray Technology 1.4.1 10 1.4.1.1 Array fabrication strategies 11 1.4.1.2 Applications 16 1.4.1.3 Recent Developments 21 Small Molecule Microarray 22 1.4.2.1 Library design for array-based screening 23 1.4.2.2 Array fabrication strategies 26 1.4.2.3 Applications 30 1.4.2.4 Recent developments 1.4.2 Protein Microarray 35 1.5 Project Objectives 37 Chapter Inhibitor Fingerprinting of Matrix Metalloproteases Using a Combinatorial Peptide Hydroxamate Library 38 ii 2.1 Summary 38 2.2 Introduction 39 2.3 Results 41 2.3.1 Library Synthesis 41 2.3.2 Inhibitor Fingerprints of MMPs across P1’ 42 2.3.3 Inhibitor Fingerprints of MMPs across P2’ and P3’ 47 2.3.4 Averaged Inhibitor Fingerprints 47 2.3.5 Cluster Analysis of MMPs 48 2.3.6 Top 100 Analysis 50 2.3.7 IC50 Measurements of Selected Inhibitors 52 2.3.8 Docked Positions of Selected Inhibitors 54 2.4 Discussion 57 2.5 Conclusion 59 Chapter Nanodroplet Profiling of Enzymatic Activities in a Microarray 61 3.1 Summary 61 3.2 Introduction 61 3.3 Results and Discussion 65 3.4 Conclusion 71 Chapter Nanodroplet Profiling of Metalloprotease Inhibitors on Microarrays 72 4.1 Summary 72 4.2 Introduction 73 4.3 Results and Discussion 76 4.4 Conclusion 82 Chapter Activity-Based Fingerprinting of Metalloproteases using a Panel of Hydroxamate-based Probes 83 iii 5.1 Summary 83 5.2 Introduction 83 5.3 Results and Discussion 85 5.3.1 Probe Synthesis 5.3.2 85 Application of Probes for Gel-Based Protein Fingerprinting 5.3.3 86 UV Dependent Labelling 90 5.3.4 Concentration Dependent Labelling 91 5.3.4.1 Protein concentration dependent labelling 5.3.4.2 Probe concentration dependent labeling 5.3.5 91 92 Labelling Protein Spiked in Cell Extract 93 5.3.6 Labelling on Protein Microarrays 5.4 Conclusion 94 95 Chapter Rapid Assembly of Metalloprotease Inhibitors Using “Click Chemistry” 97 6.1 Summary 97 6.2 Introduction 97 6.3 Results and Discussion 101 6.4 Conclusion 107 Chapter Quantitative Inhibitor Fingerprinting of Metalloproteases Using Small Molecule Microarrays 108 7.1 Summary 108 7.2 Introduction 109 7.3 Results 113 iv 7.3.1 Inhibitor Fingerprinting with Thermolysin on SMM 113 7.3.2 Inhibitor Fingerprinting with Enzyme Panel on SMM 115 7.3.3 Averaged Inhibitor Fingerprints 118 7.3.4 Top 100 Analysis 119 7.3.5 Cluster Analysis 120 7.3.6 KD Measurements with Thermolysin on SMM 120 7.3.7 KD Measurements with Anthrax LF on SMM 122 7.3.8 Docked Position of Selected Inhibitor 125 7.4 Discussion 126 7.5 Conclusion 128 Chapter Experimental Procedures 130 8.1 General Procedures 130 8.1.1 Materials 130 8.1.2 130 Instrumentation 8.2 Synthesis of the 1,400-member Hydroxamate Peptide Library 131 8.3 Microplate-Based Enzyme Profiling Procedures 132 8.3.1 High-Throughput Inhibitor Screening on Microplates 132 8.3.1.1 MMPs with inhibitor libraries 132 8.3.1.2 Thermolysin with 400-member P1’ Leu hydroxamate inhibitors 132 8.3.1.3 Thermolysin and collagenase with the 96-member “click” inhibitor library 8.3.2 IC50 Measurements 134 134 v 8.3.2.1 MMPs 134 8.3.2.2 Thermolysin and Collagenase 135 8.3.2.3 Anthrax LF 135 8.3.3 Ki Measurements 136 8.3.3.1 MMP-7 136 8.2.3.2 Thermolysin 136 8.4 Microarray-Based Enzyme Profiling Procedures 8.4.1 137 Screening Enzymes Using Nanodroplet Microarrays 137 8.4.1.1 Slide preparation 137 8.4.1.2 Protein application 137 8.4.2 Inhibitor Screening Using Nanodroplet Microarrays 138 8.4.3 Labelling Metalloproteases on Protein Microarrays 138 8.4.4 Inhibitor Fingerprinting of Metalloproteases on SMM 139 8.4.4.1 Surface preparation 139 8.4.4.2 Microarray printing 139 8.4.4.3 Protein application 140 8.5 Gel-Based Enzyme Profiling Procedures 141 8.5.1 General Labelling Procedures 141 8.5.2 Labelling in the Presence of Complex Cellular Lysates 141 8.6 In Silico Molecular Modeling Procedures 142 8.7 KD Determination Using SPR 143 8.8 Data Processing and Analysis 143 8.8.1 Microplate Data 143 8.8.1.1 High-throughput inhibitor screening 143 8.8.1.2 IC50 analysis 144 vi 8.8.1.3 Ki determination Microarray Data 145 8.8.2.1 Nanodroplet microarray 8.8.2 145 145 8.8.2.2 High-throughput protein fingerprinting on SMM 145 8.8.2.3 Quantitative KD analysis on SMM 8.8.3 146 Gel-Based Labelling Data 147 Chapter Concluding Remarks 148 Chapter 10 References 149 Chapter 11 Appendix 164 11.1 Supplemental Tables 164 11.2 Supplemental Figures 173 vii Summary Recent evidence suggests that 18-29% of eukaryotic genomes encode enzymes However, only a limited proportion of these enzymes have thus far been characterized, and little is understood about the physiological roles, substrate specificity and downstream targets of the vast majority of these important proteins While advances in sequencing and molecular biology have made it feasible to quickly amass a great wealth of genetic information, sparking the genomic revolution, similar capabilities are severely lacking in the relatively nascent proteomics arena A key step towards the biological characterization of enzymes, as well as in their adoption as drug targets, is the development of global solutions that bridge the gap in understanding proteins and their interactions This thesis examines and addresses these challenges by introducing a series of technologies that span various analytical modes, effectively expanding current capabilities in protein profiling by leveraging on throughput These include microplate (Chapter and 6) and microarray (Chapters 3-5 & 7) platforms, for which I demonstrate with examples, novel methodologies to garner implicit functional understanding of enzymes through systematic in vitro and in silico experimentation Cohesively, the methodologies are applied (but not limited) to investigations of metalloproteases – an important cluster of enzymes, whose expansive biological roles not only present pharmaceutical importance in combating diseases like cancer, arthritis and anthrax, but also provide functional insight into complex enzyme dynamics that orchestrate the remarkable enigma of life viii List of Publications (2005 – 2007) Uttamchandani, M., Walsh, D P., Yao, S Q., Chang, Y T “Small Molecule Microarrays – Recent Advances and Applications” Curr Opin Chem Biol 2005, 9, 4-13 Uttamchandani, M., Huang, X., Chen, G Y J., Yao, S Q “Nanodroplet Profiling of Enzymatic Activity on Microarrays” Bioorg Med Chem Lett 2005, 15, 2135-2139 Wang, J., Uttamchandani, M., Sun, L.P., Yao, S.Q “Activity-Based HighThroughput Profiling of Metalloprotease Inhibitors Using Small Molecule Microarrays” Chem Comm 2005, 7, 717-719 Uttamchandani, M., Wang, J., Yao, S.Q “Protein and Small Molecule Microarrays: Powerful Tools for High-Throughput Proteomics” Mol BioSyst.2006, 2, 58-68 Srinivasen, R., Uttamchandani, M., Yao, S Q “Rapid Assembly and In Situ Screening of Bidentate Inhibitors of Protein Tyrosine Phosphatases (PTPs), Org Lett 2006, 8, 713-716 Hu, Y., Uttamchandani, M., Yao, S Q “Microarray: A Versatile Platform for High-Throughput Functional Proteomics”, Comb Chem High Throughput Screening 2006, 9, 203-212 Wang, J., Uttamchandani, M., Hong, Y., Yao, S Q “Applications of Microarrays with Special Tagged Libraries” QSAR Comb Sc 2006, 11, 10091019 ix MMP-8 CpWA IC50 = 33.8nM 100 90 80 70 60 50 40 30 20 10 % Control % Control MMP-8 GM6001 IC50 = 1.37nM 120 110 100 90 80 70 60 50 40 30 20 10 0 MMP-8 CpYL IC50 = 209nM 100 90 80 70 60 50 40 30 20 10 % Control % Control MMP-8 LIG IC50 = 8.84nM 110 100 90 80 70 60 50 40 30 20 10 0 MMP-8 MMP-8 LVM IC50 = 275nM LVL IC50 = 451nM 110 100 90 80 70 60 50 40 30 20 10 % Control % Control Log(Concentration/nM) Log(Concentration/nM) Log(Concentration/nM) Log(Concentration/nM) Log(Concentration/nM) 120 110 100 90 80 70 60 50 40 30 20 10 0 Log(Concentration/nM) 181 MMP-8 CpAF IC50 = 1.1uM 110 100 90 80 70 60 50 40 30 20 10 % Control % Control MMP-8 CpAL IC50 = 963nM 120 110 100 90 80 70 60 50 40 30 20 10 0 Log(Concentration/nM) Log(Concentration/nM) MMP-8 % Control CpAY IC50 = 1.6uM 110 100 90 80 70 60 50 40 30 20 10 0 Log(Concentration/nM) 182 MMP-9 CpWA IC50 = 10.6nM 100 90 80 70 60 50 40 30 20 10 % Control % Control MMP-9 GM6001 IC50 = 4.12nM 110 100 90 80 70 60 50 40 30 20 10 MMP-9 CpYL IC50 = 39.0nM 110 100 90 80 70 60 50 40 30 20 10 % Control % Control MMP-9 LIG IC50 = 10.6nM 110 100 90 80 70 60 50 40 30 20 10 Log[Concentration/nM] MMP-9 MMP-9 CpAF IC50 = 330nM 110 100 90 80 70 60 50 40 30 20 10 % Control % Control Log[Concentration/nM] LVM IC50 = 223nM Log[Concentration/nM] Log(Concentration/nM) Log[Concentration/nM] 110 100 90 80 70 60 50 40 30 20 10 0 Log(Concentration/nM) 183 MMP-9 CpAL IC50 = 393nM 110 100 90 80 70 60 50 40 30 20 10 % Control % Control MMP-9 CpAY IC50 = 379nM Log(Concentration/nM) 110 100 90 80 70 60 50 40 30 20 10 0 Log(Concentration/nM) MMP-9 % Control LVL IC50 = 574nM 110 100 90 80 70 60 50 40 30 20 10 0 Log[Concentration/nM] 184 MMP-13 LIG IC50 = 7.22nM 100 90 80 70 60 50 40 30 20 10 % Control % Control MMP-13 GM6001 IC50 = 3.19nM 100 90 80 70 60 50 40 30 20 10 Log(Concentration/nM) MMP-13 CpWA IC50 = 33.7nM 100 90 80 70 60 50 40 30 20 10 % Control % Control MMP-13 CpYL IC50 = 12.4nM 130 120 110 100 90 80 70 60 50 40 30 20 10 Log(Concentration/nM) MMP-13 MMP-13 % Control % Control FEA IC50 = 164nM 120 110 100 90 80 70 60 50 40 30 20 10 Log(Concentration/nM) Log(Concentration/nM) LVL IC50 = 61.7nM Log(Concentration/nM) 100 90 80 70 60 50 40 30 20 10 0 Log(Concentration/nM) 185 MMP-13 CpAL IC50 = 687nM 110 100 90 80 70 60 50 40 30 20 10 % Control % Control MMP-13 LVM IC50 = 463nM 120 110 100 90 80 70 60 50 40 30 20 10 MMP-13 CpAF IC50 = 996nM 110 100 90 80 70 60 50 40 30 20 10 % Control % Control MMP-13 CpAY IC50 = 1.0uM Log(Concentration/nM) Log(Concentration/nM) Log(Concentration/nM) 120 110 100 90 80 70 60 50 40 30 20 10 0 Log(Concentration/nM) 186 MMP-14 LIG IC50 = 80.7nM 110 100 90 80 70 60 50 40 30 20 10 % Control % Control MMP-14 GM6001 IC50 = 33.2nM 110 100 90 80 70 60 50 40 30 20 10 Log(Concentration/nM) MMP-14 CpWA IC50 = 199nM 110 100 90 80 70 60 50 40 30 20 10 % Control % Control MMP-14 LVM IC50 = 133nM 110 100 90 80 70 60 50 40 30 20 10 Log(Concentration/nM) MMP-14 MMP-14 LVL IC50 = 281nM 110 100 90 80 70 60 50 40 30 20 10 % Control % Control Log(Concentration/nM) CpYL IC50 = 223nM Log(Concentration/nM) Log(Concentration/nM) 110 100 90 80 70 60 50 40 30 20 10 0 Log(Concentration/nM) Figure 11.3 IC50 determination for selected inhibitors with MMP panel A panel of inhibitors was selected for more detailed evaluation with each MMP 187 Leu-Phe IC50 = 144.5nM Ser-Ser IC50 = 176.7nM 100 % Control % Control 75 50 25 0.0 0.5 1.0 1.5 2.0 2.5 110 100 90 80 70 60 50 40 30 20 10 3.0 Log[Concentration] % Control % Control 1.5 2.0 2.5 % Control Tyr-Lys IC50 = 9.9nM % Control 1.0 Log[Concentration] Tyr-Asn IC50 = 33.1nM 0.5 110 100 90 80 70 60 50 40 30 20 10 Log[Concentration] 110 100 90 80 70 60 50 40 30 20 10 0.0 Tyr-Gln IC50 = 38.5nM Ser-Tyr IC50 = 107.3nM 120 110 100 90 80 70 60 50 40 30 20 10 0 Log[Concentration] 3.0 3.5 110 100 90 80 70 60 50 40 30 20 10 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Log[Concentration] Log[Concentration] % Control GM6001 IC50 = 23.9nM 110 100 90 80 70 60 50 40 30 20 10 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Log[Concentration] Figure 11.4 Graphs for determining IC50 values of selected inhibitors against thermolysin 188 GM6001 (Ki 25.2 nM) 1/V (s/units) 250 200 150 0.3ug Bod Casein 0.5ug Bod Casein 100 1ug Bod Casein 50 -50 -50 50 [inhibitor]/nM 100 Ser-Ser (Ki 104nM) 1/V (s/units) 200 150 0.3ug Bod Casein 100 0.5ug Bod Casein 1ug Bod Casein 50 -100 -50 -50 50 100 [inhibitor]/nM 1/V (s/units) Tyr-Lys (Ki 2.4nM) 1200 1000 800 600 0.3ug Bod Casein 0.5ug Bod Casein 400 200 1ug Bod Casein -10 10 30 [inhibitor]/ nM 50 Figure 11.5 Graphs for determining Ki values of representative inhibitors and GM6001 against thermolysin 189 Tyr-Asn IC50=45.9nM 110 100 90 80 70 60 50 40 30 20 10 %Control % Control Ser-Tyr IC50=124.8nM Log[Concentration] 110 100 90 80 70 60 50 40 30 20 10 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Log[Concentration] % Control Tyr-Lys IC50=65.6nM 110 100 90 80 70 60 50 40 30 20 10 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Log[Concentration] Figure 11.6 Graphs for determining IC50 values of selected samples for collagenase inhibitors 190 I Thermolysin III Carboxypeptidase II Collagenase IV Anthrax LF Figure 11.7 The data combined from both reciprocal experiments were presented in a 3D cube plot for enzymes in the panel Each sphere co-ordinate in the plot corresponds to the P1’, P2’ and P3’ identities of the inhibitors allowing binding intensities of all 1,400 cognate members to be visualized simultaneously Relative potency is indicated by both the color spectrum (blue - least potent, red - most potent) as well as by size of the sphere (small - least potent, big - most potent) Only data that was highly discordant between the reciprocal experiments were excluded Nevertheless a significant proportion of the data, 70% of the data in the case of collagenase, 75% for Anthrax LF, 90% for carboxypeptidase and 95% for thermolysin were consistently reproduced across the reciprocal channels Statistical correlation between the duplicated experiments was strong (r > 0.8) with thermolysin providing the highest correlation measure of r = 0.92 191 Figure 11.8 Averaged inhibition contributions permuted across P1’, P2’ and P3’ positions Each bar represents averaged inhibition across inhibitors in the library presenting the relevant residue The error bar denotes the standard deviation across each group of inhibitors Though information was lost by averaging because of consolidation of individual inhibitor sequences into general categories, this analysis provided for a broader analysis of the data and a snapshot view of the results, depicting each residues overall bearing to potency 192 14 15 234567890123456789012345A ## # MA(E) Thermolysin Collagenase Anthrax LF 16 17 678901234567890123456 # PLSGGIDVVAHELTHAVTDYTAGLSTYTLEELFRHEYTHYLQGRYAVPG ELRNDSEGFIHEFGHAVDDYAGYLL IYQNESGAINEAISDIFGTLV YDNDRLTWYEEGGAELFA LTSYGRTNEAEFFAEAFRLMH 23 123456789012345678901 # MA(E) Thermolysin Collagenase Anthrax LF YTGTQDNGGVHINSGIINKAA 18 19 20 901234567890123456789012 # # MC Carboxypeptidase RPAIWIDTGIHSREWVTQASGVWF AFTHSTNRMWRKTRSHTAGSL 30 31 678901234567890123456 # MC Carboxypeptidase 23 24 789012345678901234567 # 36 37 38 012345678901234567890 # HGNIKAFISIHSYSQLLMYPY SQGIKYSFTFELRDTGRYGFL Figure 11.9 Protein sequence alignment of the selected metalloproteases 193 IC50 Curves KD Curves ALF ALF LF-F-L KD = 0.81 uM 300 110 100 90 80 70 60 50 40 30 20 10 Fluorescence % Control lF-F-L IC50 = 2.0uM 200 100 0 250 500 750 1000 1250 ALF F-W-L KD = 0.71 uM 120 110 100 90 80 70 60 50 40 30 20 10 300 Fluorescence % Control ALF F-W-L IC50 = 2.2 uM 200 100 0 250 Log[Concentration/nM] 750 1000 1250 1500 1250 1500 1250 1500 ALF ALF I-Y-L KD = 0.74 uM 300 120 110 100 90 80 70 60 50 40 30 20 10 Fluorescence % Control 500 Concentration (nM) I-Y-L IC50 = 5.5 uM 200 100 0 250 500 750 1000 Concentration (nM) Log[Concentration/nM] ALF ALF F-W-S KD = 0.86 uM F-W-S IC50 = 7.9 uM 400 110 100 90 80 70 60 50 40 30 20 10 Fluorescence % Control 1500 Concentration (nM) Log[Concentration/nM] 300 200 100 0 Log[Concentration/nM] 250 500 750 1000 Concentration (nM) 194 ALF I-A-A KD = 2.6 uM 120 110 100 90 80 70 60 50 40 30 20 10 175 150 Fluorescence % Control ALF I-A-A IC50 = 14.0 uM 125 100 75 50 25 0 250 500 ALF 1000 1250 1500 ALF L-P-A IC50 = 16.3 uM L-P-A KD = 8.43 uM 125 100 90 80 70 60 50 40 30 20 10 Fluorescence % Control 750 Concentration (nM) Log[Concentration/nM] 100 75 50 25 Log[Concentration/nM] 250 500 750 1000 1250 1500 Concentration (nM) ALF ALF L-D-C KD = 2.0 uM 110 100 90 80 70 60 50 40 30 20 10 100 Fluorescence % Control L-D-C IC50 = 29.6 uM 75 50 25 Log[Concentration/nM] 0 250 500 750 1000 1250 1500 Concentration (nM) Figure 11.10 IC50 and KD curves for selected inhibitors with Anthrax LF A panel of inhibitors for Anthrax LF was selected and evaluated for quantitative binding parameters 195 ... Hu, Y., Uttamchandani, M., Yao, S Q “Microarray: A Versatile Platform for High- Throughput Functional Proteomics”, Comb Chem High Throughput Screening 2006, 9, 203-212 Wang, J., Uttamchandani, M.,... proteomics with the aid of the aforementioned highthroughput screening platforms Of specific interest to the context of this thesis are applications that facilitate rapid enzyme profiling and characterization... in protein profiling by leveraging on throughput These include microplate (Chapter and 6) and microarray (Chapters 3-5 & 7) platforms, for which I demonstrate with examples, novel methodologies