Lead-Seeking Approaches (eBook)

Matthew M. Hayward (Herausgeber)

eBook Download: PDF
2010 | 2010
XIII, 217 Seiten
Springer Berlin (Verlag)
978-3-642-01075-0 (ISBN)

Lese- und Medienproben

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High quality leads provide the foundation for the discovery of successful clinical development candidates, and therefore the identi?cation of leads is an essential part of drug discovery. The process for the identi?cation of leads generally starts with the screening of a compound collection, either an HTS of a relatively large compound collection (hundreds of thousands to one million plus compounds) or a more focused screen of a smaller set of compounds that have been preselected for the target of interest. Virtual screening methods such as structure-based or pharmacophore-based searches can complement or replace one of the above approaches. Once hits are identi?ed from one or more of these screening methods, they need to be thoroughly characterized in order to con?rm activity and identify areas in need of optimization. Finally, once fully characterized hits are identi?ed, preliminary optimization through synthetic modi?cation is carried out to generate leads. Parallel optimization of all properties, including biological, physicochemical, and ADME is the most ef?cient approach to the identi?cation of leads. Hit characterization is described in the previous chapter. The focus of this chapter is on hit optimization and the identi?- tion of leads. After a general overview of these processes, examples taken from the literature since 2001 will be used to illustrate speci?c points. There are also a number of excellent reviews covering the lead identi?cation process [1-6].

Volume Editors 5
Editorial Board 5
Topics in Medicinal Chemistry Also Availabe Electronically 6
Preface to the Series 7
Preface to Volume 5 8
Contents 9
Overview of Hit to Lead: The Medicinal Chemist's Role from HTS Retest to Lead Optimization Hand Off 10
1 Introduction: What is a Medicinal Chemist? 12
1.1 The Medicinal Chemist's Role 13
2 Drug Discovery, Druggability and Developability 14
2.1 High Throughput Screening 15
2.2 Phenotypic Screening 15
2.3 Fragment Screening 17
2.4 Structure-Based Drug Design 18
2.5 Homology Modeling 18
2.6 Chemoinformatics 19
3 High-Order Pattern Recognition 19
3.1 HTS and the Defined Mechanism Screen 20
3.2 HTS, Library Design and the Medicinal Chemist 20
3.3 HTS True Positive Hit Rates 21
3.4 False Positives in HTS 21
3.5 Stochastic False Positives: Mostly in Biology 22
3.6 Nonstochastic False Positives: Mostly in Chemistry 22
3.7 False Negatives 23
4 Screening: What is the Goal? 24
4.1 Chemical Biology/Chemical Genetics Screening 24
4.2 Drug Discovery Screening 25
4.3 Compound Quality Filters Aka Functional Groups to Avoid 26
4.4 Structure Verification on the Original Sample 27
4.5 Activity Verification in a Resynthesized Sample 27
4.6 Hit to Lead also Known as Closed Loop 28
4.7 Multiple vs Single Chemical Series in ``Hit to Lead´´ 29
4.8 Profiling is Critical in ``Hit to Lead´´ 29
4.9 How Many Problems Can Be Handled in Chemistry? 30
4.10 Preformulation: Pharmaceutical Sciences in Early Discovery 30
4.11 Activity SAR Patterns 31
5 Hit to Lead, Exit Criteria to Lead Optimization 31
6 Conclusion 32
References 33
High Throughput Screening in the Twenty-First Century 34
1 Introduction 35
2 Useful Definitions 36
3 Conducting an HTS 36
3.1 Automation 36
3.1.1 Structural Organization 37
3.1.2 Platforms 38
3.1.3 Art of the Possible 39
3.2 HTS Process 40
3.2.1 Phases of HTS 40
3.2.1.1 Transfer of an Assay from Therapeutically Focused Area to HTS 41
3.2.1.2 HTS Assay Development and Validation 42
3.2.1.3 Robotic Assay Adaptation and Validation 43
3.2.1.4 HTS Campaign 44
3.2.1.5 Hit Confirmation 44
3.2.1.6 Logistics 45
3.3 Assay Development 46
3.3.1 Assay Formats 47
3.3.1.1 Fluorescence Polarization 47
3.3.1.2 Homogeneous Time Resolved Fluorescence 48
3.3.1.3 Bead-Based Assays 48
3.3.1.4 Scintillation Proximity Assays 50
3.3.2 Assay Formats by Target Class 50
3.3.2.1 Kinases 50
3.3.2.2 Proteases 51
3.3.2.3 Nuclear Receptors 52
3.3.2.4 G Protein Coupled Receptors 53
3.3.2.5 Ion Channels 56
3.3.2.6 Protein-Protein Interactions 57
3.3.2.7 Phenotypic Assays 57
3.4 Screening Sample Management 58
3.4.1 Solvent 58
3.4.2 Storage Conditions 59
3.4.3 Plate Format 60
3.4.4 Logistic Strategy 61
3.4.5 Automation Systems 62
4 Deliverables 63
4.1 Output 63
4.2 Statistics 64
4.2.1 The Zhang Factor 64
4.2.2 Statistics and Hit Identification 66
4.2.3 Hit Selection by Other Means 67
5 Has HTS Been Successful? 68
5.1 A Pessimistic View 68
5.2 An Optimistic View 69
6 Impact, Challenges, and Future Directions 70
6.1 Data Management 70
6.1.1 User Requirements 71
6.1.2 Data Management Options 72
6.2 Staff Development 73
6.3 New Technologies 75
6.3.1 Miniaturization and Fluidics 75
6.3.2 Label-Free Screening 76
6.3.3 High Content Screening and Short Interfering RNA 77
6.3.4 Primary Cells 78
6.4 Smarter Approaches to Screening 78
6.4.1 Focused Libraries 78
6.4.2 Fragment Based Screening 79
6.4.3 Virtual Screening 80
6.5 HTS in Academics 80
7 Summary 81
Appendix 81
Accuracy 81
Active 81
Activity 82
Activity distribution 82
Artifact 82
Assay 82
Assay control, negative 82
Assay control, positive 83
Assay format 83
Assay validation 83
Automation 83
Background 83
Batch 83
Compound collection/library 84
Concentration response 84
Counter-screen 84
Effective concentration 50 (EC50) 84
Efficacy 84
False negative 85
False positive 85
High content screening (HCS) assay 85
High throughput 85
Hit 85
Hit rate 86
Hit threshold 86
HTS 86
Inactive 86
Lead 86
Library 87
Liquid handler or liquid handling machine 87
Microplate 87
Microplate standards 87
Module 87
Noise 87
Plate format 88
Plate map 88
Precision 88
Primary screen 88
Quality control 88
Reproducibility 89
Robustness 89
Sample 89
Screen 89
Screen validation 89
Secondary screen 90
Selectivity assay 90
Target 90
Targeted library 90
References 90
Lead Discovery Using Virtual Screening 94
1 Introduction 95
1.1 Benchmarking Virtual Screening Methods 98
1.2 Database Creation 100
1.3 Database Filtering 101
2 Ligand-Based Methods 102
2.1 Introduction 102
2.2 Case Studies 104
3 Pharmacophore-Based Methods 107
3.1 Introduction to Methods 107
3.2 Case Studies 109
4 Receptor Structure-Based Methods (SBVS) 111
4.1 Introduction to Methods 111
4.2 Case Studies 117
5 Hybrid Workflows 118
5.1 Case Studies 120
6 Fragment-Based Virtual Screening 121
6.1 Case Study 122
7 Text-Mining as a Novel Virtual Screening Tool 122
7.1 Current Limitations 123
7.2 The Rewards of Storing Molecular Structures in NLP Searchable Form 123
7.3 Potential Long Term Solutions 124
7.4 Potential Short Term Solutions 124
8 Summary 124
8.1 Virtual Screening Strategy 125
References 127
NMR Spectroscopy in Fragment Based Drug Design 134
1 Introduction 134
2 Fragment-Based Ligand Design: Puzzling Approaches to Drug Discovery 135
3 Chemical Shift Perturbation and Related Methods 139
4 Transferred NMR Measurements to Detect Ligand Binding and Related Methods 141
5 Conclusions and Outlook 145
Acknowledgments 146
References 146
Hit Triage: Medicinal Chemistry Strategies to Improve the Odds of Success in Discovery 150
1 Introduction: Philosophy of ``Hit Triage´´ 151
1.1 Sources of Hits 151
1.2 The Balance Between Data, Knowledge, and Probability 152
2 Properties to Consider 152
2.1 Experimental Data: Potency 155
2.1.1 Biophysical Assays 156
2.1.2 Biological Assays 158
2.2 Ligand Efficiency and Fragment Screening 159
2.3 Lead-Like vs Drug-Like Hits 161
3 Experimental Data: Pharmacokinetics - Absorption, Distribution, Metabolism, Excretion 162
3.1 Clearance 164
3.2 Permeability/Absorption 168
3.3 Solubility 170
4 Experimental Data: Safety 171
4.1 hERG 172
4.2 Genetic Toxicity 174
4.3 Reactive Metabolite Formation, Mechanism-Based CYP Inhibition, and Relationship to Toxicity 176
4.4 Broad Ligand Profile Screening 177
4.5 Computational Models 178
5 Summary: Decision Making 179
References 180
Lead Identification 184
1 Introduction 187
2 Lead Definition 187
3 Establish Lead Profile 187
4 Characterization of Hits 188
4.1 Biophysical Characterization/Enzymology 188
4.2 Clustering, Series Formation or Identification of Singletons 188
4.3 Pharmacophore/Binding Model 189
4.4 Patentability Assessment 189
5 Supplementing Characterized Hits 190
5.1 Substructure and Similarity Searching 190
5.2 Preliminary Array Synthesis 190
6 Parallel Optimization 190
6.1 Biological Properties 193
6.1.1 Potency 193
6.1.2 Selectivity 193
6.1.3 Function 193
6.1.4 Cellular Activity 194
6.2 Physical Properties 194
6.2.1 Solubility 194
6.2.2 pKa 195
6.2.3 Stability (Chemical, Plasma) 195
6.2.4 Protein Binding 195
6.2.5 Calculated Properties 195
6.3 In Vitro ADME 196
6.3.1 Metabolite Identification 196
6.4 Toxicology 196
6.4.1 hERG Inhibition 197
7 Pharmacokinetics 197
8 Tools for Data Analysis 198
8.1 Multivariate Data Analysis 198
8.2 Non-Linear Mapping 198
9 Tools for the Design of Synthetic Targets 199
9.1 Structure-Based, Structure-Guided Array Synthesis 199
9.2 Pharmacophore Guided Array Synthesis 199
9.3 Design of Experiments Applied to Array Design 200
9.4 Scaffold Hopping 200
10 Establishing an Intellectual Property Position 200
11 Illustrations with Examples 201
11.1 Example 1: CCR4 Antagonists 201
11.2 Example 2: cPLA2a Inhibitors 201
11.3 Example 3: MCH1 Receptor Antagonists 203
11.4 Example 4: RARbeta2 Receptor Agonists 204
11.5 Example 5: HCV NS5B Polymerase Inhibitors 204
11.6 Example 6: CGRP Antagonists 205
11.7 Example 7: IKKbeta Inhibitors 206
11.8 Example 8: IKKbeta Inhibitors 206
11.9 Example 9: PKCtheta Inhibitors 207
11.10 Example 10: mu Opioid Receptor Modulators 208
11.11 Example 11: AcpS Inhibitors 209
11.12 Example 12: PDE5 Inhibitors 209
11.13 Example 13: CXCR2 Antagonists 211
11.14 Example 14: CXCR2 Antagonists 211
11.15 Example 15: CXCR2 Antagonists 212
11.16 Example 16: CCR5 Antagonists 213
11.17 Example 17: CDK2 Inhibitors 213
11.18 Example 18: P2X7 Inhibitors 214
11.19 Example 19: DPP-4 Inhibitors 215
11.20 Example 20: BACE-1 Inhibitors 215
11.21 Example 21: mGluR1 Inhibitors 216
11.22 Example 22: ITK Inhibitors 216
11.23 Example 23: CCR1 Antagonists 217
11.24 Example 24: CHK-1 Inhibitors 218
12 Summary 218
References 219
Index 222

Erscheint lt. Verlag 12.3.2010
Reihe/Serie Topics in Medicinal Chemistry
Zusatzinfo XIII, 217 p. 36 illus., 10 illus. in color.
Verlagsort Berlin
Sprache englisch
Themenwelt Medizin / Pharmazie Studium
Naturwissenschaften Chemie
Technik
Schlagworte Chemistry • medicinal chemistry • Nuclear Magnetic Resonance (NMR) • spectroscopy
ISBN-10 3-642-01075-X / 364201075X
ISBN-13 978-3-642-01075-0 / 9783642010750
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