Hayward Lead-Seeking Approaches

1. Auflage 2010
ISBN: 978-3-642-01075-0
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 5, 217 Seiten

Reihe: Topics in Medicinal Chemistry

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].

Autoren/Hrsg.

Hayward, Matthew M.

Inhaltsverzeichnis

1;Volume Editors;5
2;Editorial Board;5
3;Topics in Medicinal Chemistry Also Availabe Electronically;6
4;Preface to the Series;7
5;Preface to Volume 5;8
6;Contents;9
7;Overview of Hit to Lead: The Medicinal Chemist's Role from HTS Retest to Lead Optimization Hand Off;10
7.1;1 Introduction: What is a Medicinal Chemist?;12
7.1.1;1.1 The Medicinal Chemist's Role;13
7.2;2 Drug Discovery, Druggability and Developability;14
7.2.1;2.1 High Throughput Screening;15
7.2.2;2.2 Phenotypic Screening;15
7.2.3;2.3 Fragment Screening;17
7.2.4;2.4 Structure-Based Drug Design;18
7.2.5;2.5 Homology Modeling;18
7.2.6;2.6 Chemoinformatics;19
7.3;3 High-Order Pattern Recognition;19
7.3.1;3.1 HTS and the Defined Mechanism Screen;20
7.3.2;3.2 HTS, Library Design and the Medicinal Chemist;20
7.3.3;3.3 HTS True Positive Hit Rates;21
7.3.4;3.4 False Positives in HTS;21
7.3.5;3.5 Stochastic False Positives: Mostly in Biology;22
7.3.6;3.6 Nonstochastic False Positives: Mostly in Chemistry;22
7.3.7;3.7 False Negatives;23
7.4;4 Screening: What is the Goal?;24
7.4.1;4.1 Chemical Biology/Chemical Genetics Screening;24
7.4.2;4.2 Drug Discovery Screening;25
7.4.3;4.3 Compound Quality Filters Aka Functional Groups to Avoid;26
7.4.4;4.4 Structure Verification on the Original Sample;27
7.4.5;4.5 Activity Verification in a Resynthesized Sample;27
7.4.6;4.6 Hit to Lead also Known as Closed Loop;28
7.4.7;4.7 Multiple vs Single Chemical Series in ``Hit to Lead´´;29
7.4.8;4.8 Profiling is Critical in ``Hit to Lead´´;29
7.4.9;4.9 How Many Problems Can Be Handled in Chemistry?;30
7.4.10;4.10 Preformulation: Pharmaceutical Sciences in Early Discovery;30
7.4.11;4.11 Activity SAR Patterns;31
7.5;5 Hit to Lead, Exit Criteria to Lead Optimization;31
7.6;6 Conclusion;32
7.7;References;33
8;High Throughput Screening in the Twenty-First Century;34
8.1;1 Introduction;35
8.2;2 Useful Definitions;36
8.3;3 Conducting an HTS;36
8.3.1;3.1 Automation;36
8.3.1.1;3.1.1 Structural Organization;37
8.3.1.2;3.1.2 Platforms;38
8.3.1.3;3.1.3 Art of the Possible;39
8.3.2;3.2 HTS Process;40
8.3.2.1;3.2.1 Phases of HTS;40
8.3.2.1.1;3.2.1.1 Transfer of an Assay from Therapeutically Focused Area to HTS;41
8.3.2.1.2;3.2.1.2 HTS Assay Development and Validation;42
8.3.2.1.3;3.2.1.3 Robotic Assay Adaptation and Validation;43
8.3.2.1.4;3.2.1.4 HTS Campaign;44
8.3.2.1.5;3.2.1.5 Hit Confirmation;44
8.3.2.1.6;3.2.1.6 Logistics;45
8.3.3;3.3 Assay Development;46
8.3.3.1;3.3.1 Assay Formats;47
8.3.3.1.1;3.3.1.1 Fluorescence Polarization;47
8.3.3.1.2;3.3.1.2 Homogeneous Time Resolved Fluorescence;48
8.3.3.1.3;3.3.1.3 Bead-Based Assays;48
8.3.3.1.4;3.3.1.4 Scintillation Proximity Assays;50
8.3.3.2;3.3.2 Assay Formats by Target Class;50
8.3.3.2.1;3.3.2.1 Kinases;50
8.3.3.2.2;3.3.2.2 Proteases;51
8.3.3.2.3;3.3.2.3 Nuclear Receptors;52
8.3.3.2.4;3.3.2.4 G Protein Coupled Receptors;53
8.3.3.2.5;3.3.2.5 Ion Channels;56
8.3.3.2.6;3.3.2.6 Protein-Protein Interactions;57
8.3.3.2.7;3.3.2.7 Phenotypic Assays;57
8.3.4;3.4 Screening Sample Management;58
8.3.4.1;3.4.1 Solvent;58
8.3.4.2;3.4.2 Storage Conditions;59
8.3.4.3;3.4.3 Plate Format;60
8.3.4.4;3.4.4 Logistic Strategy;61
8.3.4.5;3.4.5 Automation Systems;62
8.4;4 Deliverables;63
8.4.1;4.1 Output;63
8.4.2;4.2 Statistics;64
8.4.2.1;4.2.1 The Zhang Factor;64
8.4.2.2;4.2.2 Statistics and Hit Identification;66
8.4.2.3;4.2.3 Hit Selection by Other Means;67
8.5;5 Has HTS Been Successful?;68
8.5.1;5.1 A Pessimistic View;68
8.5.2;5.2 An Optimistic View;69
8.6;6 Impact, Challenges, and Future Directions;70
8.6.1;6.1 Data Management;70
8.6.1.1;6.1.1 User Requirements;71
8.6.1.2;6.1.2 Data Management Options;72
8.6.2;6.2 Staff Development;73
8.6.3;6.3 New Technologies;75
8.6.3.1;6.3.1 Miniaturization and Fluidics;75
8.6.3.2;6.3.2 Label-Free Screening;76
8.6.3.3;6.3.3 High Content Screening and Short Interfering RNA;77
8.6.3.4;6.3.4 Primary Cells;78
8.6.4;6.4 Smarter Approaches to Screening;78
8.6.4.1;6.4.1 Focused Libraries;78
8.6.4.2;6.4.2 Fragment Based Screening;79
8.6.4.3;6.4.3 Virtual Screening;80
8.6.5;6.5 HTS in Academics;80
8.7;7 Summary;81
8.8;Appendix;81
8.8.1;Accuracy;81
8.8.2;Active;81
8.8.3;Activity;82
8.8.4;Activity distribution;82
8.8.5;Artifact;82
8.8.6;Assay;82
8.8.7;Assay control, negative;82
8.8.8;Assay control, positive;83
8.8.9;Assay format;83
8.8.10;Assay validation;83
8.8.11;Automation;83
8.8.12;Background;83
8.8.13;Batch;83
8.8.14;Compound collection/library;84
8.8.15;Concentration response;84
8.8.16;Counter-screen;84
8.8.17;Effective concentration 50 (EC50);84
8.8.18;Efficacy;84
8.8.19;False negative;85
8.8.20;False positive;85
8.8.21;High content screening (HCS) assay;85
8.8.22;High throughput;85
8.8.23;Hit;85
8.8.24;Hit rate;86
8.8.25;Hit threshold;86
8.8.26;HTS;86
8.8.27;Inactive;86
8.8.28;Lead;86
8.8.29;Library;87
8.8.30;Liquid handler or liquid handling machine;87
8.8.31;Microplate;87
8.8.32;Microplate standards;87
8.8.33;Module;87
8.8.34;Noise;87
8.8.35;Plate format;88
8.8.36;Plate map;88
8.8.37;Precision;88
8.8.38;Primary screen;88
8.8.39;Quality control;88
8.8.40;Reproducibility;89
8.8.41;Robustness;89
8.8.42;Sample;89
8.8.43;Screen;89
8.8.44;Screen validation;89
8.8.45;Secondary screen;90
8.8.46;Selectivity assay;90
8.8.47;Target;90
8.8.48;Targeted library;90
8.9;References;90
9;Lead Discovery Using Virtual Screening;94
9.1;1 Introduction;95
9.1.1;1.1 Benchmarking Virtual Screening Methods;98
9.1.2;1.2 Database Creation;100
9.1.3;1.3 Database Filtering;101
9.2;2 Ligand-Based Methods;102
9.2.1;2.1 Introduction;102
9.2.2;2.2 Case Studies;104
9.3;3 Pharmacophore-Based Methods;107
9.3.1;3.1 Introduction to Methods;107
9.3.2;3.2 Case Studies;109
9.4;4 Receptor Structure-Based Methods (SBVS);111
9.4.1;4.1 Introduction to Methods;111
9.4.2;4.2 Case Studies;117
9.5;5 Hybrid Workflows;118
9.5.1;5.1 Case Studies;120
9.6;6 Fragment-Based Virtual Screening;121
9.6.1;6.1 Case Study;122
9.7;7 Text-Mining as a Novel Virtual Screening Tool;122
9.7.1;7.1 Current Limitations;123
9.7.2;7.2 The Rewards of Storing Molecular Structures in NLP Searchable Form;123
9.7.3;7.3 Potential Long Term Solutions;124
9.7.4;7.4 Potential Short Term Solutions;124
9.8;8 Summary;124
9.8.1;8.1 Virtual Screening Strategy;125
9.9;References;127
10;NMR Spectroscopy in Fragment Based Drug Design;134
10.1;1 Introduction;134
10.2;2 Fragment-Based Ligand Design: Puzzling Approaches to Drug Discovery;135
10.3;3 Chemical Shift Perturbation and Related Methods;139
10.4;4 Transferred NMR Measurements to Detect Ligand Binding and Related Methods;141
10.5;5 Conclusions and Outlook;145
10.6;Acknowledgments;146
10.7;References;146
11;Hit Triage: Medicinal Chemistry Strategies to Improve the Odds of Success in Discovery;150
11.1;1 Introduction: Philosophy of ``Hit Triage´´;151
11.1.1;1.1 Sources of Hits;151
11.1.2;1.2 The Balance Between Data, Knowledge, and Probability;152
11.2;2 Properties to Consider;152
11.2.1;2.1 Experimental Data: Potency;155
11.2.1.1;2.1.1 Biophysical Assays;156
11.2.1.2;2.1.2 Biological Assays;158
11.2.2;2.2 Ligand Efficiency and Fragment Screening;159
11.2.3;2.3 Lead-Like vs Drug-Like Hits;161
11.3;3 Experimental Data: Pharmacokinetics - Absorption, Distribution, Metabolism, Excretion;162
11.3.1;3.1 Clearance;164
11.3.2;3.2 Permeability/Absorption;168
11.3.3;3.3 Solubility;170
11.4;4 Experimental Data: Safety;171
11.4.1;4.1 hERG;172
11.4.2;4.2 Genetic Toxicity;174
11.4.3;4.3 Reactive Metabolite Formation, Mechanism-Based CYP Inhibition, and Relationship to Toxicity;176
11.4.4;4.4 Broad Ligand Profile Screening;177
11.4.5;4.5 Computational Models;178
11.5;5 Summary: Decision Making;179
11.6;References;180
12;Lead Identification;184
12.1;1 Introduction;187
12.2;2 Lead Definition;187
12.3;3 Establish Lead Profile;187
12.4;4 Characterization of Hits;188
12.4.1;4.1 Biophysical Characterization/Enzymology;188
12.4.2;4.2 Clustering, Series Formation or Identification of Singletons;188
12.4.3;4.3 Pharmacophore/Binding Model;189
12.4.4;4.4 Patentability Assessment;189
12.5;5 Supplementing Characterized Hits;190
12.5.1;5.1 Substructure and Similarity Searching;190
12.5.2;5.2 Preliminary Array Synthesis;190
12.6;6 Parallel Optimization;190
12.6.1;6.1 Biological Properties;193
12.6.1.1;6.1.1 Potency;193
12.6.1.2;6.1.2 Selectivity;193
12.6.1.3;6.1.3 Function;193
12.6.1.4;6.1.4 Cellular Activity;194
12.6.2;6.2 Physical Properties;194
12.6.2.1;6.2.1 Solubility;194
12.6.2.2;6.2.2 pKa;195
12.6.2.3;6.2.3 Stability (Chemical, Plasma);195
12.6.2.4;6.2.4 Protein Binding;195
12.6.2.5;6.2.5 Calculated Properties;195
12.6.3;6.3 In Vitro ADME;196
12.6.3.1;6.3.1 Metabolite Identification;196
12.6.4;6.4 Toxicology;196
12.6.4.1;6.4.1 hERG Inhibition;197
12.7;7 Pharmacokinetics;197
12.8;8 Tools for Data Analysis;198
12.8.1;8.1 Multivariate Data Analysis;198
12.8.2;8.2 Non-Linear Mapping;198
12.9;9 Tools for the Design of Synthetic Targets;199
12.9.1;9.1 Structure-Based, Structure-Guided Array Synthesis;199
12.9.2;9.2 Pharmacophore Guided Array Synthesis;199
12.9.3;9.3 Design of Experiments Applied to Array Design;200
12.9.4;9.4 Scaffold Hopping;200
12.10;10 Establishing an Intellectual Property Position;200
12.11;11 Illustrations with Examples;201
12.11.1;11.1 Example 1: CCR4 Antagonists;201
12.11.2;11.2 Example 2: cPLA2a Inhibitors;201
12.11.3;11.3 Example 3: MCH1 Receptor Antagonists;203
12.11.4;11.4 Example 4: RARbeta2 Receptor Agonists;204
12.11.5;11.5 Example 5: HCV NS5B Polymerase Inhibitors;204
12.11.6;11.6 Example 6: CGRP Antagonists;205
12.11.7;11.7 Example 7: IKKbeta Inhibitors;206
12.11.8;11.8 Example 8: IKKbeta Inhibitors;206
12.11.9;11.9 Example 9: PKCtheta Inhibitors;207
12.11.10;11.10 Example 10: mu Opioid Receptor Modulators;208
12.11.11;11.11 Example 11: AcpS Inhibitors;209
12.11.12;11.12 Example 12: PDE5 Inhibitors;209
12.11.13;11.13 Example 13: CXCR2 Antagonists;211
12.11.14;11.14 Example 14: CXCR2 Antagonists;211
12.11.15;11.15 Example 15: CXCR2 Antagonists;212
12.11.16;11.16 Example 16: CCR5 Antagonists;213
12.11.17;11.17 Example 17: CDK2 Inhibitors;213
12.11.18;11.18 Example 18: P2X7 Inhibitors;214
12.11.19;11.19 Example 19: DPP-4 Inhibitors;215
12.11.20;11.20 Example 20: BACE-1 Inhibitors;215
12.11.21;11.21 Example 21: mGluR1 Inhibitors;216
12.11.22;11.22 Example 22: ITK Inhibitors;216
12.11.23;11.23 Example 23: CCR1 Antagonists;217
12.11.24;11.24 Example 24: CHK-1 Inhibitors;218
12.12;12 Summary;218
12.13;References;219
13;Index;222