Physico-chemical and computational approaches to drug discovery

Contents......Page 16
1.1 Physical Basis of Ligand–Protein Binding......Page 26
1.2 Prediction of Binding Affinities: Free Energy Calculations......Page 29
1.3 Quantum Mechanical-Guided Refinements in Interaction Energy Potentials......Page 32
1.4 Quantum Mechanical Methods in Ligand–Protein Interactions......Page 36
1.5 Summary and Outlook......Page 42
References......Page 43
2.1 Introduction......Page 48
2.2.2 Details of the Ligand–Receptor Binding Process; the Role of the Solvent......Page 49
2.2.3 Ligand Properties and Binding Thermodynamics......Page 53
2.3.1 Isothermal Titration Calorimetry......Page 60
2.3.2 Van’t Hoff Analysis......Page 62
2.4.1 Molecular Simulation-Based Computational Methods......Page 63
2.4.2 Other Computational Methods......Page 67
2.4.3 Summary of Binding Free Energy Calculations......Page 71
2.5.1 Property Shifts and Medicinal Chemistry Optimizations......Page 72
2.5.2 Optimization Strategies......Page 76
2.5.3 Thermodynamics-Guided Medicinal Chemistry Optimization......Page 77
2.6.1 Renin Inhibitors......Page 81
2.6.2 Carbonic Anhydrase Inhibitors......Page 83
2.6.3 Matrix Metalloproteinase (MMP12) Inhibitors......Page 85
2.6.4 Heat Shock Protein (HSP90) Inhibitors......Page 87
2.6.5 Adenosine A1 Receptor Ligands......Page 89
2.6.6 Trypsin Inhibitors......Page 91
2.6.7 Thrombin Inhibitors......Page 93
2.6.8 Adenosine A2A Antagonists......Page 95
2.7 Summary......Page 97
References......Page 98
3.1 Solvation Models in Binding Affinity Prediction and Scoring Functions......Page 105
3.2.1 Continuum Electrostatics......Page 108
3.2.2 Nonpolar Contribution......Page 111
3.3 Capturing Discrete Water in Continuum Solvation Models......Page 113
3.3.1 Semi-Explicit Assembly (SEA) Continuum Model......Page 115
3.3.2 First Shell of Hydration (FiSH) Continuum Model......Page 118
3.3.3 Analytical Generalized Born plus Nonpolar Implicit Solvent Model 2 (AGBNP2)......Page 120
3.3.4 Three-Dimensional Reference Interaction Site Model (3D-RISM)......Page 121
3.4 Concluding Remarks......Page 122
References......Page 123
4.1 Bioavailability......Page 129
4.2 Internal Dataset Used in This Chapter......Page 131
4.3 Permeability......Page 132
4.3.1 Permeability In Vitro Assays......Page 133
4.3.2 Permeability: Simple Rules......Page 136
4.4 Solubility......Page 140
4.4.1 Solubility In Vitro Assays......Page 141
4.4.2 Solubility: Simple Rules......Page 143
4.5 First-Pass Metabolism......Page 145
4.5.1 Intrinsic Clearance In Vitro Assays......Page 146
4.5.1 Intrinsic Clearance: Simple Rules......Page 147
4.6 The Whole Picture: Putting the Pieces Together......Page 148
References......Page 151
5.1 Introduction......Page 153
5.2 The History of QSAR......Page 155
5.3 The Evolving Dimensionality of QSAR Methods......Page 156
5.4.1 Electronic Descriptors......Page 158
5.4.2 Steric Descriptors......Page 159
5.4.3 Hydrophobic Descriptors......Page 160
5.6 Information Encoded in Empirical Hydrophobic Descriptors......Page 161
5.6.2 Hydrophobic Fields......Page 163
5.6.4 Absorption, Distribution, Metabolism and Excretion (ADME)......Page 164
5.7 Estimation of log P......Page 165
5.8 HINT: an Empirical log P-Based Paradigm for Drug Discovery......Page 166
5.9.1 The HINT 3D Maps......Page 168
References......Page 170
6.1 Introduction......Page 176
6.2.1 Feature Representation......Page 178
6.2.2 Alignment......Page 180
6.2.3 Scoring Functions......Page 182
6.2.5 Evaluation of Pharmacophore Methods......Page 183
6.3 Application of Pharmacophores in Virtual Screening......Page 184
6.4 Receptor-Based Pharmacophores......Page 186
6.5 Pharmacophores and 3D QSAR......Page 188
6.6.1 Ligand-Based Pharmacophores......Page 189
6.6.2 Receptor-Based Pharmacophores......Page 191
References......Page 192
7.1 Introduction......Page 196
7.2 Molecular Docking Methods......Page 197
7.2.1 Search Methods......Page 198
7.2.2 Target Validation and Preparation......Page 201
7.2.4 Ligand Selection and Preparation......Page 205
7.2.5 Evaluating Docking Results......Page 207
7.3 Virtual Screening......Page 209
7.4 Conclusion......Page 212
References......Page 213
8.1 Introduction......Page 220
8.2.1 Physico-Chemical Aspects of Protein–Ligand Binding......Page 222
8.2.2 Binding Free Energy Calculation......Page 223
8.3.1 General Considerations......Page 224
8.3.2 Scoring Functions 200......Page 225
8.3.3 Comparison of Scoring Functions......Page 228
8.3.4 Limitations of Scoring Functions: Can They Be Improved?......Page 229
8.4 Post-Docking Processing in High-Throughput Docking......Page 232
8.5 Conclusions......Page 239
References......Page 240
9.1 Introduction......Page 248
9.2 Thermodynamic Driving Forces of Binding and the Scoring Problem......Page 250
9.3 Molecular Motions of Proteins and Ligands......Page 252
9.4.2 Accounting Implicitly for Receptor Flexibility......Page 253
9.4.3 Ligand–Receptor Docking Using Molecular Dynamics Simulations......Page 254
9.5 Conformational Ensemble Methods......Page 256
9.5.1 Employing Structural Ensembles in Docking Calculations......Page 258
9.6 Use of Collective Modes to Describe Global Motions......Page 260
9.7 Conclusions and Outlook......Page 263
References......Page 264
10.1 Introduction......Page 269
10.2.1 A Historical Perspective......Page 271
10.2.2 The Statistics Behind COMBINE......Page 274
10.2.3 gCOMBINE: the Graphical User Interface to COMBINE......Page 278
10.3 3D-QSAR Models in Virtual Screening......Page 279
10.3.1 Retrospective Studies......Page 280
10.3.2 Prospective Studies......Page 281
10.3.3 3-D QSAR Pharmacophores......Page 282
10.4 3D-QSAR Modeling of Ligand Selectivity......Page 283
10.5 Current Trends in COMBINE Analysis as a 3D-QSARTechnique......Page 285
10.5.1 COMBINE Analysis as a Scoring Functionf or Virtual Screening......Page 286
10.5.2 COMBINE Analysis for Modeling Target Flexibility and/or Ligand Orientation......Page 287
10.5.3 COMBINE Analysis for Modeling Ligand Selectivity......Page 288
10.5.4 SemiEmpirical COMBINE (SE-COMBINE) Analysis......Page 290
10.6 Future Challenges for COMBINE Analysis......Page 291
10.7 Conclusions......Page 292
References......Page 293
11.1 Introduction......Page 298
11.2.1 Fixed Energy Systems (NVE)......Page 301
11.2.2 Fixed Temperature Systems (NVT)......Page 303
11.2.4 Microscopic Estimators of Thermodynamic Observables......Page 304
11.2.5 Numerical Integration of the Equations of Motion in Molecular Dynamics......Page 305
11.3.2 The Role of Free Energy and the Concept of Reaction Coordinate......Page 308
11.3.3 Volumetric Effect on the Unbound State......Page 310
11.4.1 The Importance of Sampling and the‘‘Importance Sampling ’’......Page 311
11.4.3 Enhanced Sampling Techniques......Page 312
11.5 Enhanced Sampling Applications to Protein–Ligand Binding......Page 316
11.5.1 Steered Molecular Dynamics......Page 317
11.5.2 Metadynamics......Page 319
11.6 Conclusions and Perspectives......Page 321
References......Page 323
12.1 Introduction......Page 327
12.2.1 Privileged Target Classes......Page 328
12.3 Properties of Drug Binding Sites......Page 330
12.4 Druggability: Term Definition and Controversy......Page 331
12.5.1 High-Throughput Screening......Page 332
12.5.3 Multiple Solvent Crystal Structures......Page 333
12.6.1 Data Sets......Page 334
12.6.2 Cavity Detection Algorithms......Page 335
12.6.3 Methods Based on Cavity Descriptors......Page 336
12.6.4 Methods Based on Interaction Potentials......Page 338
References......Page 340
13.1 Introduction......Page 344
13.2 What Makes Protein–Protein Interfaces Difficult to Target?......Page 345
13.3 Computational Hot Spot Detection......Page 349
13.4 Predicting Potential Binding Sites in Protein–Prote inInterfaces from Unbound Protein States......Page 353
13.5 Allosteric Binding Sites as Alternative Targets for Modulating Protein–Protein Interactions......Page 356
13.6.1 Improved Descriptions of Solvent Effects......Page 359
13.6.3 Data-Driven Docking Approaches......Page 362
13.7 Summary and Outlook......Page 371
References......Page 373
14.1 Introduction......Page 385
14.2.1 Metadynamics......Page 386
14.2.3 Path Collective Variables......Page 387
14.2.4 Optimal Collective Variables for Ligand Binding......Page 389
14.3.1 Binding Profiles for a Series of CDK2 Inhibitors......Page 390
14.3.2 Rationalizing the Different Residence Times of a Ligand in COX Isoforms......Page 392
14.4 Conclusions......Page 393
References......Page 394
15.1 Introduction......Page 397
15.2 Methods and Formats in Computer-Assisted Library Design......Page 399
15.3.1 Viral Diseases......Page 401
15.3.2 Parasitic Diseases......Page 413
15.3.3 Bacterial Diseases......Page 414
References......Page 419
Subject Index......Page 424