Lead Generation, 2 Volume Set
Methods and Strategies
By: Jörg Holenz (Editor), Raimund Mannhold (Editor), Hugo Kubinyi (Editor), Gerd Folkers (Editor)
Hardcover | 4 May 2016 | Edition Number 1
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Beginning with a general discussion of the underlying principles and strategies, individual lead generation approaches are described in detail, highlighting their strengths and weaknesses, along with all relevant bordering disciplines like e.g. target identification and validation, predictive methods, molecular recognition or lead quality matrices. Novel lead generation approaches for challenging targets like DNA-encoded library screening or chemical biology approaches are treated here side by side with established methods as high throughput and affinity screening, knowledge- or fragment-based lead generation, and collaborative approaches. Within the entire book, a very strong focus is given to highlight the application of the presented methods, so that the reader will be able to learn from real life examples. The final part of the book presents several lead generation case studies taken from different therapeutic fields, including diabetes, cardiovascular and respiratory diseases, neuroscience, infection and tropical diseases.
The result is a prime knowledge resource for medicinal chemists and for every scientist involved in lead generation.
Industry Reviews
drug discovery, which combined with very thorough up-to-date literature references and emphasis on emerging technologies, makes it a book we would readily suggest taking a look at" (Dr. Robert Webster, Dr. Nuria Ortega Hernandez Bayer Pharma AG, ChemMedChem, July 2017)
Dedication V
List of Contributors XXI
Preface XXVII
A Personal Foreword XXXI
Volume 68a
Part I Introduction to Lead Generation 1
1 Introduction: Learnings from the Past â" Characteristics of Successful Leads 3
Mike Hann
Acknowledgments 10
References 10
2 Modern Lead Generation Strategies 13
J¶rg Holenz and Dean G. Brown
2.1 Lead Generation Greatly Influences Clinical Candidate Quality 14
2.2 Screening of Compound Libraries has Undergone a Major Paradigm Change 15
2.3 New Chemical Modalities are Available to Tackle Difficult Targets 15
2.4 As Demands have Increased, New Lead Generation Methods Emerged 16
2.5 How do Lead Generation Chemists Meet These Challenges and Subsequently Provide Their Lead Optimization Colleagues with High-Quality Lead Series? 17
2.5.1 Learnings can be Drawn from LG Project Failures 17
2.5.2 How Many Compounds to Screen to Generate High-Quality Leads? 18
2.5.3 Which Compounds to Screen to Generate High-Quality Leads? 19
2.5.4 Developing Project-Customized, Concerted, and Comprehensive Lead Generation Strategies will Increase LG Success Rates: the CREATION of Leads 20
2.5.5 Selecting the Target Defines LG Success Rates 21
2.5.6 Lead Generation should be Complemented by Auxiliary Technologies to Characterize Hits 21
2.5.7 Phenotypic Screens are Often Complemented by a Chemical Biology Arm 22
2.5.8 The Lead Generation Strategy is Defined by the Budget Allocated 22
2.5.9 Cost-Efficient but Information-Rich Lead Generation Strategies 23
2.5.10 The Revival of Potency as the Most Important Lead Criterion? 24
2.5.11 When has a LG Campaign Delivered Successfully? 27
References 31
Part II The Importance of Target Identification for Generating Successful Leads 35
3 âLigandabilityâ of Drug Targets: Assessment of Chemical Tractability via Experimental and In Silico Approaches 37
Udo Bauer and Alexander L. Breeze
3.1 Introduction 37
3.2 The Concept of Ligandability 39
3.2.1 General Characteristics of Ligandable Targets 39
3.3 The Intersection of Ligandability and Human Disease Target Space 40
3.3.1 Experimental Techniques for Assessing Target Ligandability 42
3.3.1.1 High-Throughput Screening and Subset/âValidation Setâ Screening 43
3.3.1.2 Fragment Screening 44
3.4 Practical Examples of the Use of Fragment Screening for Ligandability Assessment 50
3.4.1 Chemical Tractability Assessment by in silico Approaches 54
3.4.1.1 Pocket-Finding Algorithms 54
3.4.1.2 Discrimination Functions and Validation Sets 55
3.4.1.3 Simulation-Based Methods for Identifying Interaction Potentials 56
3.5 Conclusions and Outlook 56
References 58
4 Chemistry-Driven Target Identification 63
Iv¡n Cornella-Taracido, Ryan Hicks, Ola Engkvist, Adam Hendricks, Ronald Tomlinson, and M. Paola Castaldi
4.1 Introduction 63
4.2 Chemistry-Driven Target Discovery: Enabling Biology 65
4.2.1 Biological Samples 65
4.2.2 Cells Cultured in 2D 66
4.2.3 Cells Cultured in 3D, Organoids, and Tissues 67
4.2.4 Nonhuman Cells and Whole-Organism Screening 68
4.2.5 Functional Assays and Readouts 68
4.3 Chemistry for Target Discovery 71
4.3.1 Screening Deck Selection 71
4.3.2 Triaging and Prioritization of Chemical Matter 72
4.3.3 SAR Expansion and Probe Synthesis for Target Deconvolution 73
4.4 Small-Molecule Target Identification Techniques 75
4.4.1 In Silico Target Deconvolution 75
4.4.2 Biochemical Profiling 77
4.4.3 Target Deconvolution Correlational Tools 78
4.4.4 Subcellular Localization 79
4.4.5 Chemical Genetics 79
4.4.6 Affinity Chemical Proteomics 81
4.4.7 Target Corroboration 84
4.5 Conclusions 86
References 89
Part III Hit Generation Methods 93
5 Lead Generation Based on Compound Collection Screening 95
Dirk Weigelt and Ismet Dorange
5.1 Introduction 95
5.2 Screening of Existing Collections: the General Workflow 96
5.2.1 High-Throughput Screening 96
5.2.2 Medium-Throughput Screening: Selection Methods 98
5.3 Generation of New Screening Compounds 99
5.3.1 Collection Enhancement Programs 102
5.3.2 Library Design and Compound Selection 102
5.3.2.1 Number of Dimensions 103
5.3.2.2 Enumeration and Filtering 104
5.3.2.3 Layout 106
5.3.3 Focus on Synthetic Feasibility 107
5.3.3.1 Multicomponent Reactions 107
5.3.3.2 Click Chemistry 108
5.3.3.3 Diversity-oriented Synthesis 108
5.3.4 Structure-driven Approaches 109
5.3.4.1 Privileged Structures 110
5.3.4.2 Structure-driven Approaches Toward Unchartered Territory 112
5.3.5 Target Focus 114
5.3.5.1 Kinases 114
5.3.5.2 G-Protein-Coupled Receptors 115
5.3.5.3 Ion Channels 116
5.3.5.4 Proteinâ"Protein Interactions 117
5.4 Other Concepts 117
5.4.1 Natural Products 118
5.4.2 DNA-Encoded Libraries 119
5.4.3 Spatially Addressed Libraries 120
5.4.4 On-bead Screening 120
5.4.5 Dynamic Combinatorial Chemistry 121
5.4.6 Cocktails and Mixtures 121
5.5 Summary and Outlook 122
References 123
6 Fragment-Based Lead Generation 133
Ivan V. Efremov and Daniel A. Erlanson
6.1 Introduction 133
6.2 Screening Methods 135
6.3 Hit Validation 137
6.4 Ligand Efficiency and Other Metrics 138
6.5 Hit Optimization 139
6.6 Fragment Growing 140
6.7 Fragment Linking 144
6.8 Proteinâ"Protein Interactions 147
6.9 GPCRs 151
6.10 Computational Approaches 152
6.11 Conclusions 153
References 154
7 Rational Hit Generation 159
Bernd Wellenzohn and Alexander Weber
7.1 Introduction 159
7.2 Lead Generation: Transition State and Substrate Analogs 161
7.3 Hit Generation by Rational Library Design 165
7.4 Hit Generation by Virtual Screening 167
7.4.1 Structure-based VS in Enumerated Molecules 170
7.4.2 Ligand-based VS in Nonenumerated Virtual Chemical Spaces 171
7.5 Hit Generation by Scaffold Replacement Technologies 173
7.6 Hit Generation by Chemogenomics Approaches 174
7.7 Summary 178
References 178
8 Competitive Intelligenceâ"based Lead Generation and Fast Follower Approaches 183
Yu Jiang, Ziping Liu, J¶rg Holenz, and Hua Yang
8.1 Introduction 183
8.2 Competitive Intelligence-based Approach 185
8.2.1 Example A: A Case Study for the Hybrid Strategy 190
8.2.2 Example C: A Case Study for the Fused Strategy 192
8.2.3 Example C: A Case Study for the Fused Strategy 193
8.2.4 Example D: A Case Study for the Fused Strategy 196
8.2.5 Example E: A Case Study for the Chimera Strategy 197
8.3 Fast Follower Approach 201
8.3.1 Salfanilamide-based Fast Follower Approaches 202
8.3.2 Omeprazole-based Fast Follower Approaches 203
8.3.3 Rimonabant-based Fast Follower Approach 210
References 214
9 Selective Optimization of Side Activities: An Alternative and Promising Strategy for Lead Generation 221
Norbert Handler, Andrea Wolkerstorfer, and Helmut Buschmann
9.1 Introduction 221
9.1.1 Drug Selectivity and Unwanted or Desired Side Effects 222
9.2 Definition, Rational, and Concept of the SOSA Approach 223
9.2.1 Multiple Ligands and Polypharmacology 224
9.2.2 Safety and Bioavailability 225
9.3 Drugs in Other Drugs: Drug as Fragments 225
9.4 Drug Repositioning and Drug Repurposing 226
9.4.1 Old Drugs 226
9.5 The SOSA Approach and Analog Design 227
9.6 Patentability and Interference Risk of the SOSA Approach 230
9.6.1 Analogization, Optimization, and Isosterism 230
9.7 Case Studies and Examples 231
9.7.1 Sulfonamides 231
9.7.2 Morphine Analogs 232
9.7.3 Warfarin 232
9.7.4 Sildenafil (Viagra) 232
9.7.5 Thalidomide Analogs 233
9.7.6 Bupropion 234
9.7.7 Chlorpromazine 235
9.7.8 Chlorothiazide 235
9.7.9 Propranolol 235
9.7.10 Minaprine Analogs 236
9.7.11 Viloxazine Analogs 237
9.7.12 Methylation in the SOSA Strategy of Drug Design 237
9.7.13 Discovery of New Antiplasmodial Compounds 239
9.7.14 Drugs Acting on Central Nervous System Targets as Leads for Non-CNS Targets 241
9.7.15 Mexiletine Derivatives as Orally Bioavailable Inhibitors of Urokinase-Type Plasminogen Activator 242
9.7.16 Amiloride Analogs as Inhibitors of the Urokinase-type Plasminogen Activator 245
9.7.17 Flavonoids with an Oligopolysulfated Moiety: A New Class of Anticoagulant Agents 246
9.7.18 Clioquinol 249
9.8 Conclusions 251
References 252
10 Lead Generation for Challenging Targets 259
Jinqiao Wan, Dengfeng Dou, Hongmei Song, Xian-Hui Wu, Xuemin Cheng, and Jin Li
10.1 Introduction 259
10.2 DNA-Encoded Library Technology in Lead Generation 260
10.2.1 Background 260
10.2.2 DNA-Recorded Synthesis-Assisted Libraries 262
10.2.3 DNA-Templated Synthesis-Assisted Libraries 264
10.2.4 Encoded Self-Assembling Chemical Libraries 266
10.2.5 Summary and Perspective 267
10.3 Stapled Peptide 276
10.3.1 Background 276
10.3.2 Structure, Design, and Synthesis of Stapled Peptide 278
10.3.2.1 Stapled Peptide Structure 278
10.3.2.2 Stapled Peptide Design 280
10.3.2.3 Stapled Peptide Synthesis 282
10.3.3 Stapled Peptide Solution α-Helix Conversion Measurement 283
10.3.4 Stapled Peptide Affinity Evaluation and α-Helix Content Correlation 284
10.3.4.1 Surface Plasmon Resonance Binding Assays 284
10.3.4.2 Fluorescence Polarization Assay 284
10.3.4.3 Stapled Peptide Affinity and α-Helix Content Correlation 285
10.3.5 Stapled Peptide Permeability 286
10.3.6 Peptide Stability Assay 288
10.3.7 Outlook 288
10.4 Phenotypic Screening 289
10.4.1 Introduction 289
10.4.2 Basics for Establishing a Phenotypic Screen 291
10.4.2.1 Identify a âDruggableâ Phenotype and the Type of Readout 291
10.4.2.2 Assay Design 291
10.4.2.3 Hit Selection and Secondary Assay 291
10.4.3 Typical Phenotypic Assays 292
10.4.3.1 Cell-Viability Assay 292
10.4.3.2 Fluorescent Imaging Plate Reader Technology 293
10.4.3.3 High-Content Screening 293
10.4.4 In Vitro Phenotypic Screening 293
10.4.4.1 Classic Phenotypic Screening 293
10.4.4.2 Patient-Derived Stem Cell in Drug Discovery 294
10.4.4.3 Phenotypic Screening on iPSC-Derived Disease Models 295
10.4.4.4 High-Content Cytotoxicity Screening by iPSC-Derived Hepatocytes 296
10.5 Summary 297
References 298
11 Collaborative Approaches to Lead Generation 307
Fabrizio Giordanetto, Anna Karawajczyk, and Graham Showell
11.1 Introduction 307
11.2 Creativity 308
11.3 Speed 308
11.4 Risk Sharing 308
11.5 Intellectual Property 309
11.6 Costs 309
11.7 Management 310
11.8 Lillyâs Open Innovation Drug Discovery 310
11.9 Molecular Library Program 312
11.10 EU Openscreen 314
11.11 European Lead Factory 315
11.12 Medicines for Malaria Venture 317
11.13 Open Source Malaria Project 320
11.14 Drugs for Neglected Diseases Initiative 320
11.15 Open Lab Foundation 321
11.16 Scientists Against Malaria 322
11.17 Open Source Drug Discovery 323
11.18 TB Alliance 323
11.19 Summary 324
References 325
Volume 68b
Dedication V
List of Contributors XXI
Part IV Converting Hits to Successful Leads 329
12 A Medicinal Chemistry Perspective on the Hit-to-Lead Phase in the Current Era of Drug Discovery 331
Dean G. Brown
12.1 Introduction 331
12.2 Active to Hit Processes 333
12.3 Target Potency: Energetics of Binding 336
12.4 Addressing Vast Chemical Space: HtL Strategies 345
12.5 Matched Pair Analysis 348
12.6 The Role of Hydrophobicity and HtL 351
12.7 Probing H-Bond Donors and Acceptors 353
12.8 Structure Based DD in HtL 356
12.9 Statistical Molecular Design 358
12.10 Hit to Lead is not Lead Optimization 359
12.11 Summary 362
References 363
13 Molecular Recognition and Its Importance for Fragment-Based Lead Generation and Hit-to-Lead 367
Thorsten Nowak
13.1 Introduction 367
13.2 Brief Summary of the Main Factors that Govern Molecular Interactions 368
13.3 Thermodynamics of Molecular Interactions and Impact on Hit Finding and Optimization 369
13.4 Enthalpy as a Key Decision Tool in Medicinal Chemistry 371
13.5 Importance of Enthalpic Interactions: Drivers of Selectivity and Specificity? 373
13.6 Fragment Screening Hit Optimization: Fragment Linking 374
13.7 Interstitial Waters and Their Usefulness: Case Studies on HSP-90 381
13.8 Fragments to Find Hot Spots in Binding Pockets 385
13.9 Nonclassical Hydrogen Bonds â" Interactions of Halogen Atoms with Î -Systems and Carbonyl Groups: Factor Xa and Cathepsin L 386
13.10 Binding Mode Dependency of the Experimental Conditions and Chemical Framework of Ligand 390
13.11 Cooperativity in Binding: DAO or DAAO D-Amino Acid Oxidase 391
References 394
14 Affinity-Based Screening Methodologies and Their Application in the Hit-to-Lead Phase 401
Stefan Geschwindner
14.1 Introduction 401
14.2 Nuclear Magnetic Resonance Spectroscopy 402
14.3 Optical Biosensors: Surface Plasmon Resonance and Optical Waveguide Grating 404
14.4 Isothermal Titration Calorimetry 407
14.5 Thermal Shift Assay 411
14.6 Mass Spectrometry Approaches 412
14.7 Encoded Library Technologies 414
14.8 Emerging Technologies: Microscale Thermophoresis and Backscattering Interferometry 417
References 418
15 Predictive Methods in Lead Generation 425
Matthew D. Segall and Peter Hunt
15.1 Introduction 425
15.2 Compound Property Prediction 427
15.3 Multiparameter Optimization: Identifying High-Quality Compounds 430
15.3.1 Drug-like Properties 430
15.3.2 Filters 431
15.3.3 Desirability Functions and Probabilistic Scoring 432
15.3.4 Pareto Optimization 435
15.3.5 Example 436
15.4 De Novo Design: Guiding the Exploration of Novel Chemistry 439
15.4.1 Example Application 442
15.5 Selection: Balancing Quality with Diversity 443
15.6 Conclusions 445
References 447
16 Lead Quality 451
J. Willem M. Nissink, Sebastien Degorce, and Ken Page
16.1 Introduction 451
16.2 Properties in Drug Design 452
16.2.1 Primary Activity Assays 453
16.2.2 Physicochemical Properties 453
16.2.3 DMPK 454
16.2.4 Safety 454
16.2.5 Overall Profiles 456
16.3 Optimizing Properties: Useful Rules, Guides, and Simple Metrics for Early-Stage Projects 457
16.3.1 Rules for Potency: Ligand Efficiency Measures 457
16.3.2 Rules for Safety 462
16.3.3 Rules for DMPK and Mode of Administration: Early-Stage Structure-Based Profiling 464
16.3.3.1 Simple Design Rules for Good DMPK 464
16.3.3.2 Other DMPK Design Rules 465
16.3.4 Multiobjective Optimization 466
16.4 Predicted Dose to Man as a Measure of Early- and Late-Stage Lead Quality 467
16.4.1 Introduction 467
16.4.2 Description of Models and Data 469
16.4.3 Data Supporting Technique 471
16.4.3.1 Matching eD2M Doses with Normalized Observed Clinical Doses 472
16.4.3.2 Matching Cmax Values from eD2M and Clinical Studies 472
16.4.4 Flagging Potential Candidate Drugs Using eD2M 473
16.4.5 Determining Properties that Drive eD2M Predictions for a Series 474
16.5 Summary 480
References 481
Part V Hypothesis-driven Lead Optimization 487
17 The Strategies and Politics of Successful Design, Make, Test, and Analyze (DMTA) Cycles in Lead Generation 489
Steven S. Wesolowski and Dean G. Brown
17.1 DMTA Cycles: Perspectives from History 490
17.2 Test: What Assays, in What Order, and Why? 494
17.3 Additional Advice for âTestâ Component of DMTA 496
17.4 Design: What to Make and Why? 496
17.5 Additional Advice for âDesignâ Component of DMTA 500
17.6 Make: Challenges and Strategies for Synthesis 501
17.7 Additional Advice for the âMakeâ Component of DMTA 502
17.8 Analyze: Making Sense of Whatâs Been Done and Formulating Sensible Plans for the Next Designs 502
17.9 Additional Advice for âAnalyzeâ Component of DMTA 508
17.10 Results: Do Lead Optimization Teams Get What They Need? 508
References 509
Part VI Recent Lead Generation Success Stories 513
18 Lead Generation Paved the Way for the Discovery of a Novel H3 Inverse Agonist Clinical Candidate 515
Christophe Genicot and Laurent Provins
18.1 Introduction 515
18.2 Hit Identification 517
18.3 Lead Generation 521
18.3.1 Exploration of Oxazoline Substitution 523
18.3.2 Rigidification of Propoxy Linker 531
18.3.3 Oxazoline/Oxazole Surrogates: Lactams 533
18.3.4 Conclusions 536
18.4 Lead Optimization and Candidate Selection 537
18.5 Conclusions 543
Acknowledgments 544
References 544
19 Vorapaxar: From Lead Identification to FDA Approval 547
Samuel Chackalamannil and Mariappan Chelliah
19.1 Introduction 547
19.2 Background Information on Antiplatelet Agents 549
19.3 Thrombin Receptor (Protease-activated Receptor-1) Antagonists as a Novel Class of Antiplatelet Agents 550
19.4 Mechanism of Thrombin Receptor Activation 550
19.5 Preclinical Data Supporting the Antiplatelet Effect of Thrombin Receptor Antagonists 551
19.6 Himbacine-derived Thrombin Receptor Antagonists 552
19.6.1 Lead Identification 552
19.6.2 Lead Generation of Himbacine-derived Thrombin Receptor Antagonist Hit 553
19.6.2.1 Structureâ"Activity Relationship Studies 555
19.6.2.2 First-Generation Thrombin Receptor Antagonists 556
19.6.2.3 In vivo Metabolism of Himbacine Derivatives 558
19.6.2.4 Generation of Aryl Himbacine Leads 561
19.6.2.5 Second-Generation Leads that Incorporate Heteroatoms in the C-ring 562
19.6.2.6 Identification of nor-seco Himbacine Lead 564
19.6.3 Discovery of Vorapaxar (SCH 530348) 565
19.6.3.1 Clinical Studies of Vorapaxar 567
19.7 Conclusions 569
Abbreviations 570
Acknowledgments 570
References 571
20 Lead Generation Approaches Delivering Inhaled β2-Adrenoreceptor Agonist Drug Candidates 575
Michael Stocks and Lilian Alcaraz
20.1 Introduction 575
20.2 Lead Generation Exercises to Discover β2AR Agonist Clinical Candidates 577
20.3 AstraZeneca Lead Generation Exercises to Discover β2AR Agonist Clinical Candidates 587
20.4 Summary 593
References 593
21 GPR81 HTS Case Study 597
Eric Wellner and Ola Fjellstr¶m
21.1 General Remarks 597
21.2 The Target 598
21.3 Screening Cascade 599
21.4 Compound Selection (10 K Validation Set) 602
21.5 HTS 606
21.5.1 CSE 608
21.5.2 Single-Concentration Counterscreen 614
21.5.3 Clustering 615
21.5.4 Cluster Expansion and Nearest Neighbours 618
21.6 Hit Evaluation 618
21.6.1 Potency, Efficacy, and Curves 618
21.6.2 Binding Kinetics 621
21.6.3 Concentrationâ"Response Counterscreen 622
21.6.4 Hit Assessment 622
21.6.4.1 Size and Lipophilicity Efficiency Assessment 622
21.6.4.2 Secondary Pharmacology Assessment 626
21.6.5 Secondary Screening Cascade and Hit Expansion 630
21.6.6 Biological Effect Assay 634
21.7 Alternative Lead Generation Strategies 638
21.7.1 Pepducins and Other Modified Peptides 641
21.8 Conclusions 645
References 646
22 Development of Influenza Virus Sialidase Inhibitors 651
Mauro Pascolutti, Robin J. Thomson, and Mark von Itzstein
22.1 Introduction 651
22.2 Targets for Anti-influenza Drug Development: Receptor Binding and Receptor Cleavage 652
22.2.1 Targeting Receptor Binding by Haemagglutinin 654
22.2.2 Targeting Receptor Destruction by Sialidase 655
22.2.3 Influenza Virus Sialidase: Structure and Mechanism 656
22.3 Development of Influenza Virus Sialidase Inhibitors 658
22.3.1 The Development of Zanamivir: Proof of Concept and First-in-Class Sialidase Inhibitor Drug 659
22.3.1.1 Template Selection 659
22.3.1.2 Structure-based Inhibitor Design 662
22.3.1.3 X-Ray Crystallographic Confirmation of Inhibitor Binding Mode 665
22.3.1.4 Selectivity for Influenza Virus Sialidase over Human Sialidases 666
22.3.1.5 Efficacy against Virus Replication 667
22.3.1.6 Mode of Administration of the Highly Polar Drug 667
22.3.1.7 Modifying the Presentation of Zanamivir: Prodrugs and Multivalency 668
22.3.2 Sialidase Inhibitor Development on Noncarbohydrate Scaffolds 671
22.3.2.1 A Sialidase Inhibitor Based on a Cyclohexene Scaffold: The Development of Oseltamivir 671
22.3.2.2 A Sialidase Inhibitor Based on a Cyclopentane Scaffold: The Development of Peramivir 673
22.3.3 Monitoring Resistance to Influenza Virus Sialidase Inhibitors 675
22.4 Summary and Future Directions 676
References 676
23 The Discovery of Cathepsin A Inhibitors: A Project-Adapted Fragment Approach Based on HTS Results 687
Sven Ruf, Christian Buning, Herman Schreuder, Wolfgang Linz, Dominik Linz, Hartmut R¼tten, Georg Horstick, Markus Kohlmann, Katja Kroll, Klaus Wirth, and Thorsten Sadowski
23.1 General Background 687
23.2 Cathepsin A enzyme 687
23.2.1 Structural Biology and Catalytic Mechanism 687
23.2.2 Structural and Catalytic Functions of CatA 689
23.2.3 Tissue Distribution and Substrates 689
23.2.4 Natural Products and Synthetic Peptides as Inhibitors of CatA 690
23.3 CatA and the Link to Cardiovascular Disease 691
23.4 Lead Discovery 692
23.4.1 High-Throughput Screening and Data Analysis 692
23.4.2 Evaluation of Hit Series 693
23.4.2.1 Covalent Inhibitor Series 693
23.4.2.2 Malonamide Series 697
23.4.2.3 Pyrazolone Hit Series 698
23.4.3 Explorative Chemistry Delivers a Novel Lead Structure 699
23.4.3.1 Crystal Structure of 9b Bound to CatA 705
23.5 Lead Optimization 705
23.6 Toward an in vivo Proof of Concept 711
23.7 Summary and Conclusions 713
References 714
24 Lead Structure Discovery for Neglected Diseases: Product Development Partnerships Driving Drug Discovery 717
Jeremy N. Burrows and Takushi Kaneko
24.1 Introduction 717
24.2 Malaria and Medicines for Malaria Venture 719
24.3 Malaria Lead Generation Strategy 719
24.4 Hit Identification Strategies 722
24.5 Optimization of a Marketed Antimalarial Chemotype 723
24.6 Target-Based Approaches 723
24.7 Asexual Blood-Stage Phenotypic Screening 724
24.8 Whole-Cell Screening: Results 725
24.9 Repositioning of Clinical Candidates Developed for Other Indications 726
24.10 Case Studies 727
24.10.1 Dihydroorotate Dehydrogenase (DHODH) 727
24.10.2 Whole-Cell Screening 728
24.11 Screening for Malaria Eradication 729
24.12 Tuberculosis and the Global Alliance for Tuberculosis Drug Development (TB Alliance) 729
24.13 Target Product Profiles 730
24.14 TB Allianceâs Mission 730
24.15 Hit Generation Strategies for TB 732
24.16 Examples of Phenotypic Screens 733
24.17 Conclusions 741
References 741
25 A Fragmentation Enumeration Approach to Generating Novel Drug Leads 747
Pravin S. Iyer and Manoranjan Panda
25.1 Introduction 747
25.2 Principle 748
25.3 Research Methodology 748
25.3.1 Fragmentation 749
25.3.1.1 Origin of Parent Molecules 749
25.3.1.2 Cores and Daughters 749
25.3.1.3 Nonflat Cores 751
25.3.2 Intelligent Recombination and Enumeration 754
25.4 Evaluation 754
25.4.1 Preliminary Experimental Evaluation 755
25.4.2 In Silico Evaluation 755
25.4.3 Virtual Screening Using Enzymeâ"Ligand Docking 756
25.5 Summary 758
References 759
Index 761
ISBN: 9783527333295
ISBN-10: 3527333290
Series: Methods & Principles in Medicinal Chemistry
Published: 4th May 2016
Format: Hardcover
Language: English
Number of Pages: 824
Audience: Professional and Scholarly
Publisher: Wiley
Country of Publication: DE
Edition Number: 1
Dimensions (cm): 24.64 x 17.78 x 5.08
Weight (kg): 2.05
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