Scaffold Hopping in Medicinal Chemistry

Overview

This first systematic treatment of the concept and practice of scaffold hopping shows the tricks of the trade and provides invaluable guidance for the reader's own projects.

The first section serves as an introduction to the topic by describing the concept of scaffolds, their discovery, diversity and representation, and their importance for finding new chemical entities. The following part describes the most common tools and methods for scaffold hopping, whether topological, ...

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Scaffold Hopping in Medicinal Chemistry, Volume 58

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Overview

This first systematic treatment of the concept and practice of scaffold hopping shows the tricks of the trade and provides invaluable guidance for the reader's own projects.

The first section serves as an introduction to the topic by describing the concept of scaffolds, their discovery, diversity and representation, and their importance for finding new chemical entities. The following part describes the most common tools and methods for scaffold hopping, whether topological, shape-based or structure-based. Methods such as CATS, Feature Trees, Feature Point Pharmacophores (FEPOPS), and SkelGen are discussed among many others. The final part contains three fully documented real-world examples of successful drug development projects by scaffold hopping that illustrate the benefits of the approach for medicinal chemistry.

While most of the case studies are taken from medicinal chemistry, chemical and structural biologists will also benefit greatly from the insights presented here.

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Product Details

Meet the Author

Nathan Brown is the Head of the In Silico Medicinal Chemistry group in the Cancer Therapeutics Unit at The Institute of Cancer Research in London (UK). At the ICR, Dr. Brown and his group support the entire drug discovery portfolio together with developing new computational methodologies to enhance the drug design work.

Nathan Brown conducted his doctoral research in Sheffield with Professor Peter Willett focusing on evolutionary algorithms and graph theory. After a two-year Marie Curie Fellowship in Amsterdam in collaboration with Professor Johann Gasteiger in Erlangen, he joined the Novartis Institutes for BioMedical Research in Basel for a three-year Presidential Fellowship in Basel working with Professors Peter Willett and Karl-Heinz Altmann.

His work has led to the pioneering work on multiobjective de novo design in addition to a variety of discoveries and method development in scaffold hopping, bioisosteric identifi cation and replacement, molecular descriptors and statistical modeling. Nathan continues to pursue his research in all aspects of in silico medicinal chemistry.

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Table of Contents

List of Contributors XIII

Preface XVII

A Personal Foreword XIX

Part One Scaffolds: Identification, Representation Diversity, and Navigation 1

1 Identifying and Representing Scaffolds 3
Nathan Brown

1.1 Introduction 3

1.2 History of Scaffold Representations 4

1.3 Functional versus Structural Molecular Scaffolds 7

1.4 Objective and Invariant Scaffold Representations 7

1.4.1 Molecular Frameworks 7

1.4.2 Scaffold Tree 8

1.5 Maximum Common Substructures 9

1.6 Privileged Scaffolds 11

1.7 Conclusions 11

References 12

2 Markush Structures and Chemical Patents 15
David Anthony Cosgrove

2.1 Introduction 15

2.2 Encoding Markush Structures 18

2.2.1 The r_group Record 19

2.2.1.1 Exact R Groups 19

2.2.1.2 Inexact R Groups 19

2.2.1.3 Fused R Groups 19

2.2.2 The Menguin Program 20

2.2.3 Correspondence between the MIL File and the Markush Structure 21

2.3 The Search Algorithm 22

2.3.1 Matching R Groups 25

2.3.1.1 Exact R Groups 25

2.3.1.2 Inexact R Groups 27

2.3.1.3 Fused R Groups 28

2.3.1.4 Hydrogen Atoms 29

2.3.1.5 Managing Multiple Fragment/R Group Matches 30

2.4 Using Periscope for Scaffold Hopping 31

2.4.1 Substructure Searching 32

2.4.2 Free–Wilson Analysis 33

2.4.3 Fast Followers 36

2.5 Conclusions 36

References 37

3 Scaffold Diversity in Medicinal Chemistry Space 39
Sarah R. Langdon, Julian Blagg, and Nathan Brown

3.1 Introduction 39

3.1.1 Scaffold Representation 39

3.1.2 What Do We Mean by Scaffold Diversity? 41

3.2 Scaffold Composition of Medicinal Chemistry Space 41

3.2.1 Natural Products as a Source of Novel Medicinal Chemistry Scaffolds 45

3.2.2 Enumerating Potential Medicinal Chemistry Scaffolds 46

3.2.3 Using Scaffold Composition to Interpret Bioactivity Data 48

3.3 Metrics for Quantifying the Scaffold Diversity of Medicinal Chemistry Space 48

3.4 Visualizing the Scaffold Diversity of Medicinal Chemistry Space 53

3.5 Conclusions 56

References 57

4 Scaffold Mining of Publicly Available Compound Data 61
Ye Hu and Jöurgen Bajorath

4.1 Introduction 61

4.2 Scaffold Definition 62

4.3 Selectivity of Scaffolds 63

4.3.1 Privileged Substructures 63

4.3.2 Target Community-Selective Scaffolds 64

4.3.3 Target-Selective Scaffolds 67

4.4 Target Promiscuity of Scaffolds 67

4.4.1 Promiscuous BM Scaffolds and CSKs 67

4.4.2 Scaffold–Target Family Profiles 70

4.4.3 Promiscuous Scaffolds in Drugs 70

4.5 Activity Cliff-Forming Scaffolds 71

4.5.1 Activity Cliff Concept 71

4.5.2 Multitarget Cliff-Forming Scaffolds 71

4.6 Scaffolds with Defined Activity Progression 73

4.6.1 Activity Profile Sequences 73

4.6.2 Conserved Scaffolds 75

4.7 Scaffold Diversity of Pharmaceutical Targets 76

4.7.1 Scaffold Hopping Potential 76

4.7.2 Structural Relationships between Scaffolds 76

4.7.3 Scaffold Hopping in Virtual Screening 78

4.8 Conclusions 79

References 80

5 Exploring Virtual Scaffold Spaces 83
William R. Pitt and Boris Kroeplien

5.1 Introduction 83

5.1.1 Virtual Chemistry 83

5.1.2 Chemical Space 83

5.1.3 Scaffold Definition 84

5.2 The Comprehensive Enumeration of Parts of Chemical Space 85

5.2.1 Fragments 85

5.2.2 Ring Systems 86

5.2.3 Reagents 87

5.3 The Iterative Generation of Virtual Compounds 88

5.3.1 Transformations 88

5.3.2 Manual Selection of Chemical Modifications 88

5.3.3 Analog Generators 89

5.3.4 Inverse QSAR 89

5.3.5 Multiple Objective Optimization 90

5.3.6 Structure-Based De Novo Design 90

5.4 Virtual Synthesis 92

5.4.1 Synthetic Tractability 92

5.4.2 Using Real-Life Reactions for in Silico Molecule Construction 93

5.4.3 Readily Synthesizable Compounds 94

5.4.3.1 Construction 94

5.4.3.2 Searching 95

5.4.3.3 Outside Big Pharma 96

5.4.4 Iterative Approaches 96

5.5 Visualizations of Scaffold Space 96

5.6 A Perspective on the Past and the Future 97

References 99

Part Two Scaffold-Hopping Methods 105

6 Similarity-Based Scaffold Hopping Using 2D Fingerprints 107
Peter Willett

6.1 Fingerprints 107

6.2 Retrospective Studies of Scaffold Hopping Using 2D Fingerprints 109

6.3 Predictive Studies of Scaffold Hopping Using 2D Fingerprints 112

6.4 Conclusions 114

References 115

7 CATS for Scaffold Hopping in Medicinal Chemistry 119
Christian P. Koch, Michael Reutlinger, Nickolay Todoroff, Petra Schneider, and Gisbert Schneider

7.1 Chemically Advanced Template Search 119

7.2 Retrospective Evaluation of Enrichment and Scaffold Hopping Potential 122

7.3 Prospective Scaffold-Hopping Applications 126

7.4 Conclusions 128

References 128

8 Reduced Graphs 131
Kristian Birchall

8.1 Introduction 131

8.2 Generating Reduced Graphs 133

8.2.1 Reduction Scheme 133

8.2.2 Node Labeling 134

8.2.3 Sheffield Implementations 135

8.2.4 Extended Reduced Graphs 136

8.3 Comparison and Usage of Reduced Graphs 137

8.3.1 Conventional Fingerprinting 138

8.3.2 RG-Specific Fingerprints 139

8.3.3 Augmenting Fingerprints with Edit Distance 140

8.3.4 Extended Reduced Graph Fingerprints 141

8.3.5 Graph Matching Approaches 143

8.3.6 Bioisostere Encoding 144

8.4 Summary 146

References 146

9 Feature Trees 149
Nathan Brown

9.1 Introduction 149

9.2 Feature Tree Generation 149

9.3 Feature Tree Comparison 150

9.4 Retrospective Validation 151

9.5 Implementations and Applications 152

9.5.1 MTree: Combinations of Query Molecules 152

9.5.2 Similarity Searching in Large Combinatorial Chemistry Spaces 152

9.6 Conclusions 153

References 154

10 Feature Point Pharmacophores (FEPOPS) 155
Jeremy L. Jenkins

10.1 Similarity Searching in Drug Discovery 155

10.2 FEPOPS: An Analogy to Image Compression 157

10.3 Computing FEPOPS 159

10.4 Scaling and Correlations 162

10.5 Defining Scaffold Hopping 163

10.6 FEPOPS in Similarity Searching and Scaffold Hopping 164

10.7 Alternative Alignment 168

10.8 In Silico Target Prediction 170

10.9 Chemical Space Uniqueness 171

10.10 Perspective on FEPOPS’ 10 Year Anniversary 172

References 173

11 Three-Dimensional Scaffold Replacement Methods 175
Nathan Brown

11.1 Introduction 175

11.2 Generic Three-Dimensional Scaffold Replacement Workflow 175

11.2.1 Molecule Databases 175

11.2.2 Fragment Generation and Filtering 177

11.2.3 Fragment Replacement Search and Scoring 178

11.3 SHOP: Scaffold HOPping by GRID-Based Similarity Searches 178

11.4 ReCore 179

11.5 BROOD 179

11.6 Conclusions 180

References 181

12 Spherical Harmonic Molecular Surfaces (ParaSurf and ParaFit) 183
David W. Ritchie and Violeta I. Perez-Nueno

12.1 Introduction 183

12.2 Spherical Harmonic Surfaces 183

12.3 Rotating Spherical Polar Fourier Expansions 185

12.4 Spherical Harmonic Surface Shape Similarity 186

12.5 Calculating Consensus Shapes and Center Molecules 187

12.6 The ParaSurf and ParaFit Programs 188

12.7 Using Consensus Shapes to Probe the CCR5 Extracellular Pocket 190

12.8 Conclusions 192

References 193

13 The XED Force Field and Spark 195
Martin Slater and Andy Vinter

13.1 Pharmacological Similarity – More than Just Chemical Structure 195

13.2 Improving the Generation of Valid Molecular Fields 199

13.3 The eXtended Electron Distribution (XED) Force Field 200

13.4 The XED Force Field Applied to Scaffold Hopping in Spark 202

13.5 How Spark Works 202

13.6 Application of Spark in Drug Discovery Scenarios 206

13.7 P38 Kinase Inhibitor Fragment Growing Using Spark 207

13.7.1 The Beauty of P38 207

13.8 Creating New Molecules 208

13.9 New Potential Inhibitors 210

13.10 The Far-Reaching Consequences of Using Molecular Fields as Measures of Similarity 212

References 213

14 Molecular Interaction Fingerprints 215
Didier Rognan and Jeremy Desaphy

14.1 Introduction 215

14.2 Target-Annotated Ligand Fingerprints 215

14.2.1 Interacting Atom/Fragment Fingerprints 216

14.2.2 Protein–Ligand Pharmacophores 217

14.3 Ligand-Annotated Target Fingerprints 217

14.4 True Target–Ligand Fingerprints 220

14.4.1 Association Fingerprints 220

14.4.2 Interaction Pattern Fingerprints 222

14.5 Conclusions 225

References 226

15 SkelGen 231
Nikolay P. Todorov

15.1 Introduction 231

15.2 Structure Generation and Optimization 232

15.2.1 Fragments and Fragment Sets 232

15.2.2 Structure Generation 234

15.2.3 Scoring and Optimization 234

15.2.4 Ligand-Based Design 234

15.3 Validation Studies 235

15.3.1 Retrospective Validation Study: CDK2, COX2, ER, MMP-3 235

15.3.2 Estrogen Receptor 235

15.3.3 Histamine H3 Inverse Agonists 236

15.4 Scaffold Hopping Using Fixed Fragments 237

15.5 Scaffold Hopping Using Site Points 238

15.6 Further Considerations for Scaffold Hopping 240

15.6.1 Receptor Flexibility 240

15.6.2 Water Molecules 241

15.6.3 Receptor Specificity 242

15.7 Conclusion 242

References 243

Part Three Case Studies 245

16 Case Study 1: Scaffold Hopping for T-Type Calcium Channel and Glycine Transporter Type 1 Inhibitors 247
Leah C. Konkol, Timothy J. Senter, and Craig W. Lindsley

16.1 Introduction 247

16.2 T-Type Calcium Channel Inhibitors 248

16.3 Scaffold Hopping to Access Novel Calcium T-Type Channel Inhibitors 250

16.4 Scaffold Hopping to Access Novel Glycine Transporter

Type 1 (GlyT1) Inhibitors 253

16.5 Conclusions 255

References 255

17 Case Study 2: Bioisosteric Replacements for the Neurokinin 1 Receptor (NK1R) 259
Francesca Perruccio

17.1 Introduction 259

17.2 Neurokinin 1 (NK1) Therapeutic Areas 259

17.3 The Neurokinin 1 Receptor (NK1R) and Its Mechanism 260

17.4 Neurokinin 1 Antagonists 261

17.5 NK1 Receptor: Target Active Site and Binding Mode 264

17.6 Bioisosteric Replacements in NK1 Receptor Antagonist 266

17.7 Bioisosteric Replacements in NK1 Receptor Antagonist: A Retrospective Study 270

17.8 Summary and Conclusions 274

References 274

18 Case Study 3: Fragment Hopping to Design Highly Potent and Selective Neuronal Nitric Oxide Synthase Inhibitors 279
Haitao Ji and Richard B. Silverman

18.1 Fragment-Based Drug Design 279

18.2 Minimal Pharmacophoric Elements and Fragment Hopping 281

18.3 Fragment Hopping to Design Novel Inhibitors for Neuronal Nitric Oxide Synthase 283

18.4 Fragment Hopping to Optimize Neuronal Nitric Oxide Synthase Inhibitors 288

18.5 Application of Neuronal Nitric Oxide Synthase Inhibitors to the Prevention of Cerebral Palsy 289

References 291

Index 297

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