Physico-chemical and Computational Approaches to Drug Discovery

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ISBN: 9781849733533 | 1849733538
Cover: Hardcover
Copyright: 6/15/2012

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Molecular modeling and simulation play a central role in academic and industrial research focused on physico-chemical properties and processes. The efforts carried out in this field have crystallized in a variety of models, simulation methods, and computational techniques that are examining the relationship between the structure, dynamics and functional role of biomolecules and their interactions. In particular, there has been a huge advance in the understanding of the molecular determinants that mediate the interaction between small compounds acting as ligands and their macromolecular targets. This book provides an updated description of the advances experienced in recent years in the field of molecular modeling and simulation of biomolecular recognition, with particular emphasis towards the development of efficient strategies in structure-based drug design. The main aims of the book are:* To provide a detailed description of the physico-chemical principles that underlie the ligand-receptor interaction* To describe the methodological basis of computational tools to elucidate the molecular features that modulate the ligand-receptor interaction* To highlight the impact of the methodological innovations in drug designThe publication covers a wide range of topics relevant to the development of drugs and provides, in a single volume, a comprehensive description of the major methodological strategies available for drug discovery. There are two main features that make this book unique: firstly, the contents provide a physical basis of the methodological tools described in the book, which capture the essential physico-chemical properties inherent to the recognition between ligands and their receptors. This provides the reader with clear guidelines to calibrate the performance of the current methodologies used in drug design. Secondly, the combination of standard formalisms widely accepted in the pharmaceutical and medicinal chemistry arena are included, with an updated review of the latest advances experienced in the field. This current state-of-the-art publication covers the current challenges faced by computational tools to decipher the basis of ligand-receptor interaction and is aimed towards both academic and industrial researchers working in modeling of biomolecular systems and drug discovery.

Recognition of Ligands by Macromolecular Targets	p. 1
Physical Basis of Ligand-Protein Binding	p. 1
Prediction of Binding Affinities: Free Energy Calculations	p. 4
Quantum Mechanical-Guided Refinements in Interaction Energy Potentials	p. 7
Quantum Mechanical Methods in Ligand-Protein Interactions	p. 11
Summary and Outlook	p. 17
Acknowledgements	p. 18
References	p. 18
Thermodynamics of Ligand Binding	p. 23
Introduction	p. 23
Theoretical Background	p. 24
Basic Equations of Ligand-Protein Binding Thermodynamics	p. 24
Details of the Ligand-Receptor Binding Process; the Role of the Solvent	p. 24
Ligand Properties and Binding Thermodynamics	p. 28
Measuring Binding Thermodynamics	p. 35
Isothermal Titration Calorimetry	p. 35
Van't Hoff Analysis	p. 37
Further Notes on Experimental Approaches	p. 38
Calculation of the Binding Free Energy and Its Components	p. 38
Molecular Simulation-Based Computational Methods	p. 38
Other Computational Methods	p. 42
Summary of Binding Free Energy Calculations	p. 46
Impact of Thermodynamics on Medicinal Chemistry Optimizations	p. 47
Property Shifts and Medicinal Chemistry Optimizations	p. 47
Optimization Strategies	p. 51
Thermodynamics-Guided Medicinal Chemistry Optimization	p. 52
Case Studies	p. 56
Renin Inhibitors	p. 56
Carbonic Anhydrase Inhibitors	p. 58
Matrix Metalloproteinase (MMP12) Inhibitors	p. 60
Heat Shock Protein (HSP90) Inhibitors	p. 62
Adenosine A1 Receptor Ligands	p. 64
Trypsin Inhibitors	p. 66
Thrombin Inhibitors	p. 68
Adenosine A2A Antagonists	p. 70
Summary	p. 72
Acknowledgements	p. 73
References	p. 73
Continuum Solvation in Biomolecular Systems	p. 80
Solvation Models in Binding Affinity Prediction and Scoring Functions	p. 80
Continuum Solvation Models	p. 83
Continuum Electrostatics	p. 83
Nonpolar Contribution	p. 86
Capturing Discrete Water in Continuum Solvation Models	p. 88
Semi-Explicit Assembly (SEA) Continuum Model	p. 90
First Shell of Hydration (FiSH) Continuum Model	p. 93
Analytical Generalized Born plus Nonpolar Implicit Solvent Model 2 (AGBNP2)	p. 95
Three-Dimensional Reference Interaction Site Model (3D-RISM)	p. 96
Other Recent Models Capturing First-Shell Effects	p. 97
Concluding Remarks	p. 97
References	p. 98
Bioavailability Prediction at Early Drug Discovery Stages: In Vitro Assays and Simple Physico-Chemical Rules	p. 104
Bioavailability	p. 104
Internal Dataset Used in This Chapter	p. 106
Permeability	p. 107
Permeability In Vitro Assays	p. 108
Permeability: Simple Rules	p. 111
Solubility	p. 115
Solubility In Vitro Assays	p. 116
Solubility: Simple Rules	p. 118
First-Pass Metabolism	p. 120
Intrinsic Clearance In Vitro Assays	p. 121
Intrinsic Clearance: Simple Rules	p. 122
The Whole Picture: Putting the Pieces Together	p. 123
References	p. 126
Molecular Descriptors for Database Mining. Translating Empirical Chemistry into Mathematics: Tools for QSAR and In Silico Screening Based on the Hydrophobicity of Small Molecules	p. 128
Introduction	p. 128
The History of QSAR	p. 130
The Evolving Dimensionality of QSAR Methods	p. 131
Descriptors and Molecular Properties	p. 133
Electronic Descriptors	p. 133
Steric Descriptors	p. 134
Hydrophobic Descriptors	p. 135
Connectivity and Related Descriptors	p. 136
Information Encoded in Empirical Hydrophobic Descriptors	p. 136
Nano-Scale Icebergs and Entropy	p. 138
Hydrophobic Fields	p. 138
Additional Free Energy Information	p. 139
Absorption, Distribution, Metabolism and Excretion (ADME)	p. 139
Estimation of log P	p. 140
HINT: an Empirical log P-Based Paradigm for Drug Discovery	p. 141
Treating Hydrophobicity as a 3D Property	p. 143
The HINT 3D Maps	p. 143
Virtual Screening and Modeling with an Empirical Force Field	p. 145
References	p. 145
Pharmacophore Models in Drug Design	p. 151
Introduction	p. 151
Ligand-Based Pharmacophore Elucidation	p. 153
Feature Representation	p. 153
Alignment	p. 155
Scoring Functions	p. 157
Recent Methods	p. 158
Evaluation of Pharmacophore Methods	p. 158
Datasets for Ligand-Based Pharmacophore Elucidation	p. 159
Validation of Pharmacophore Hypotheses	p. 159
Application of Pharmacophores in Virtual Screening	p. 159
Receptor-Based Pharmacophores	p. 161
Pharmacophores and 3D QSAR	p. 163
Example Applications of Pharmacophores	p. 164
Ligand-Based Pharmacophores	p. 164
Receptor-Based Pharmacophores	p. 166
Conclusions	p. 167
References	p. 167
Docking and Virtual Screening	p. 171
Introduction	p. 171
Molecular Docking Methods	p. 172
Search Methods	p. 173
Target Validation and Preparation	p. 176
Target Flexibility	p. 180
Ligand Selection and Preparation	p. 180
Evaluating Docking Results	p. 182
Virtual Screening	p. 184
Conclusion	p. 187
Acknowledgements	p. 188
References	p. 188
Binding Free Energy Calculation and Scoring in Small-Molecule Docking	p. 195
Introduction	p. 195
Binding Free Energy	p. 197
Physico-Chemical Aspects of Protein-Ligand Binding	p. 197
Binding Free Energy Calculation	p. 198
Scoring Functions in High-Throughput Docking	p. 199
General Considerations	p. 199
Scoring Functions	p. 200
Comparison of Scoring Functions	p. 203
Limitations of Scoring Functions: Can They Be Improved?	p. 204
Post-Docking Processing in High-Throughput Docking	p. 207
Rescoring of Top-Ranking Hits Using Advanced Simulation Techniques	p. 208
Conclusions	p. 214
References	p. 215
Accounting for Target Flexibility During Ligand-Receptor Docking	p. 223
Introduction	p. 223
Thermodynamic Driving Forces of Binding and the Scoring Problem	p. 225
Molecular Motions of Proteins and Ligands	p. 227
Accounting for Conformational Flexibility During Docking	p. 228
Inclusion of Ligand Flexibility	p. 228
Accounting Implicitly for Receptor Flexibility	p. 228
Ligand-Receptor Docking Using Molecular Dynamics Simulations	p. 229
Treatment of Side-Chain Flexibility and Local Protein Backbone Changes	p. 231
Conformational Ensemble Methods	p. 232
Employing Structural Ensembles in Docking Calculations	p. 233
Use of Collective Modes to Describe Global Motions	p. 235
Conclusions and Outlook	p. 238
Acknowledgements	p. 239
References	p. 239
COMparative BINding Energy (COMBINE) Analysis as a Structure-Based 3D-QSAR Method	p. 244
Introduction	p. 244
COMparative BINding Energy (COMBINE) Analysis	p. 246
A Historical Perspective	p. 246
The Statistics Behind COMBINE	p. 249
gCOMBINE: the Graphical User Interface to COMBINE	p. 253
3D-QSAR Models in Virtual Screening	p. 254
Retrospective Studies	p. 255
Prospective Studies	p. 256
3-D QSAR Pharmacophores	p. 257
3D-QSAR Modeling of Ligand Selectivity	p. 258
Current Trends in COMBINE Analysis as a 3D-QSAR Technique	p. 260
COMBINE Analysis as a Scoring Function for Virtual Screening	p. 261
COMBINE Analysis for Modeling Target Flexibility and/or Ligand Orientation	p. 262
COMBINE Analysis for Modeling Ligand Selectivity	p. 263
SemiEmpirical COMBINE (SE-COMBINE) Analysis	p. 265
Future Challenges for COMBINE Analysis	p. 266
Conclusions	p. 267
Acknowledgements	p. 268
References	p. 268
Enhanced Sampling Methods in Drug Design	p. 273
Introduction	p. 273
Basics	p. 276
Fixed Energy Systems (NVE)	p. 276
Fixed Temperature Systems (NVT)	p. 278
Isothermal-Isobaric Systems (NPT)	p. 279
Microscopic Estimators of Thermodynamic Observables	p. 279
Numerical Integration of the Equations of Motion in Molecular Dynamics	p. 280
Description of the Binding Process	p. 283
Identification of Sub-States in a Given Thermodynamic Ensemble	p. 283
The Role of Free Energy and the Concept of Reaction Coordinate	p. 283
Volumetric Effect on the Unbound State	p. 285
Basics of Enhanced Sampling	p. 286
The Importance of Sampling and the "Importance Sampling"	p. 286
Collective Variables	p. 287
Enhanced Sampling Techniques	p. 287
Enhanced Sampling Applications to Protein-Ligand Binding	p. 291
Steered Molecular Dynamics	p. 292
Metadynamics	p. 294
Conclusions and Perspectives	p. 296
References	p. 298
Expanding the Target Space: Druggability Assessments	p. 302
Introduction	p. 302
The Target Space	p. 303
Privileged Target Classes	p. 303
Under-Exploited Molecular Mechanism of Action	p. 305
Properties of Drug Binding Sites	p. 305
Druggability: Term Definition and Controversy	p. 306
Experimental Determination of Druggability	p. 307
High-Throughout Screening	p. 307
Fragment Screening	p. 308
Multiple Solvent Crystal Structures	p. 308
Computational Assessment of Druggability	p. 309
Data Sets	p. 309
Cavity Detection Algorithms	p. 310
Methods Based on Cavity Descriptors	p. 311
Methods Based on Interaction Potentials	p. 313
Summary and Outlook	p. 315
Acknowledgements	p. 315
References	p. 315
Computational Strategies and Challenges for Targeting Protein-Protein Interactions with Small Molecules	p. 319
Introduction	p. 319
What Makes Protein-Protein Interfaces Difficult to Target?	p. 320
Computational Hot Spot Detection	p. 324
Predicting Potential Binding Sites in Protein-Protein Interfaces from Unbound Protein States	p. 328
Allosteric Binding Sites as Alternative Targets for Modulating Protein-Protein Interactions	p. 331
Docking for Targeting Protein-Protein Interfaces	p. 334
Improved Descriptions of Solvent Effects	p. 334
Protein Flexibility in Protein-Ligand Docking	p. 337
Data-Driven Docking Approaches	p. 342
Summary and Outlook	p. 346
Acknowledgements	p. 348
References	p. 348
Using Molecular Simulations and Metadynamics to Predict Binding Free Energies and Kinetics: the Case of Cox and Cdk2	p. 360
Introduction	p. 360
Methods	p. 361
Metadynamics	p. 361
The Choice of the CVs	p. 362
Path Collective Variables	p. 362
Optimal Collective Variables for Ligand Binding	p. 364
Results and Discussion	p. 365
Binding Profiles for a Series of CDK2 Inhibitors	p. 365
Rationalizing the Different Residence Times of a Ligand in COX Isoforms	p. 367
Conclusions	p. 368
References	p. 369
Computer-Assisted Design of Drug-Like Synthetic Libraries	p. 372
Introduction	p. 372
Methods and Formats in Computer-Assisted Library Design	p. 374
Examples of Computer-Assisted Library Design	p. 376
Viral Diseases	p. 376
Parasitic Diseases	p. 388
Bacterial Diseases	p. 389
Conclusions	p. 394
Acknowledgements	p. 394
References	p. 394
Subject Index	p. 399
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Physico-chemical and Computational Approaches to Drug Discovery

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