Note: Protein-Ligand Interactions -- Contents -- List of Contributors -- Preface -- A Personal Foreword -- Part I: Binding Thermodynamics -- 1 Statistical Thermodynamics of Binding and Molecular Recognition Models -- 1.1 Introductory Remarks -- 1.2 The Binding Constant and Free Energy -- 1.3 A Statistical Mechanical Treatment of Binding -- 1.3.1 Binding in a Square Well Potential -- 1.3.2 Binding in a Harmonic Potential -- 1.4 Strategies for Calculating Binding Free Energies -- 1.4.1 Direct Association Simulations -- 1.4.2 The Quasi-Harmonic Approximation -- 1.4.3 Estimation of Entropy Contributions to Binding -- 1.4.4 The MoleculeMechanics Poisson-Boltzmann Surface AreaMethod -- 1.4.5 Thermodynamic Work Methods -- 1.4.6 Ligand Decoupling -- 1.4.7 Linear Interaction Methods -- 1.4.8 Salt Effects on Binding -- 1.4.9 Statistical Potentials -- 1.4.10 Empirical Potentials -- References -- 2 Some Practical Rules for the Thermodynamic Optimization of Drug Candidates -- 2.1 Engineering Binding Contributions -- 2.2 Eliminating Unfavorable Enthalpy -- 2.3 Improving Binding Enthalpy -- 2.4 Improving Binding Affinity -- 2.5 Improving Selectivity -- 2.6 Thermodynamic Optimization Plot -- Acknowledgments -- References -- 3 Enthalpy-Entropy Compensation as Deduced from Measurements of Temperature Dependence -- 3.1 Introduction -- 3.2 The Current Status of Enthalpy-Entropy Compensation -- 3.3 Measurement of the Entropy and Enthalpy of Activation -- 3.4 An Example -- 3.5 The Compensation Temperature -- 3.6 Effect of High Correlation on Estimates of Entropy and Enthalpy -- 3.7 Evolutionary Considerations -- 3.8 Textbooks -- References -- Part II: Learning from Biophysical Experiments -- 4 Interaction Kinetic Data Generated by Surface Plasmon Resonance Biosensors and the Use of Kinetic Rate Constants in Lead Generation and Optimization -- 4.1 Background. , 4.2 SPR Biosensor Technology -- 4.2.1 Principles -- 4.2.2 Sensitivity -- 4.2.3 Kinetic Resolution -- 4.2.4 Performance for Drug Discovery -- 4.3 From Interaction Models to Kinetic Rate Constants and Affinity -- 4.3.1 Determination of Interaction Kinetic Rate Constants -- 4.3.2 Determination of Affinities -- 4.3.3 Steady-State Analysis versus Analysis of Complete Sensorgrams -- 4.4 Affinity versus Kinetic Rate Constants for Evaluation of Interactions -- 4.5 From Models to Mechanisms -- 4.5.1 Irreversible Interactions -- 4.5.2 Induced Fit -- 4.5.3 Conformational Selection -- 4.5.4 Unified Model for Dynamic Targets -- 4.5.5 Heterogeneous Systems/Parallel Reactions -- 4.5.6 Mechanism-Based Inhibitors -- 4.5.7 Multiple Binding Sites and Influence of Cofactors -- 4.6 Structural Information -- 4.7 The Use of Kinetic Rate Constants in Lead Generation and Optimization -- 4.7.1 Structure-Kinetic Relationships -- 4.7.2 Selectivity/Specificity and Resistance -- 4.7.3 Chemodynamics -- 4.7.4 Thermodynamics -- 4.8 Designing Compounds with Optimal Properties -- 4.8.1 Correlation between Kinetic and Thermodynamic Parameters and Pharmacological Efficacy -- 4.8.2 Structural Modeling -- 4.9 Conclusions -- Acknowledgments -- References -- 5 NMR Methods for the Determination of Protein-Ligand Interactions -- 5.1 Experimental Parameters from NMR -- 5.2 Aspects of Protein-Ligand Interactions That Can Be Addressed by NMR -- 5.2.1 Detection and Verification of Ligand Binding -- 5.2.2 Interaction Site Mapping -- 5.2.3 Interaction Models and Binding Affinity -- 5.2.4 Molecular Recognition -- 5.2.5 Structure of Protein-Ligand Complexes -- 5.3 Ligand-Induced Conformational Changes of a Cyclic Nucleotide Binding Domain -- 5.4 Ligand Binding to GABARAP Binding Site and Affinity Mapping -- 5.5 Transient Binding of Peptide Ligands to Membrane Proteins -- References. , Part III: Modeling Protein-Ligand Interactions -- 6 Polarizable Force Fields for Scoring Protein-Ligand Interactions -- 6.1 Introduction and Overview -- 6.2 AMOEBA Polarizable Potential Energy Model -- 6.2.1 Bond, Angle, and Cross-Energy Terms -- 6.2.2 Torsional Energy Term -- 6.2.3 Van der Waals Interactions -- 6.2.4 Permanent Electrostatic Interactions -- 6.2.5 Electronic Polarization -- 6.2.6 Polarization Energy -- 6.3 AMOEBA Explicit Water Simulation Applications -- 6.3.1 Small-Molecule Hydration Free Energy Calculations -- 6.3.2 Ion Solvation Thermodynamics -- 6.3.3 Binding Free Energy of Trypsin and Benzamidine Analogs -- 6.4 Implicit Solvent Calculation Using AMOEBA Polarizable Force Field -- 6.5 Conclusions and Future Directions -- References -- 7 Quantum Mechanics in Structure-Based Ligand Design -- 7.1 Introduction -- 7.2 Three MM-Based Methods -- 7.3 QM-Based Force Fields -- 7.4 QM Calculations of Ligand Binding Sites -- 7.5 QM/MM Calculations -- 7.6 QM Calculations of Entire Proteins -- 7.6.1 Linear Scaling Methods -- 7.6.2 Fragmentation Methods -- 7.7 Concluding Remarks -- Acknowledgments -- References -- 8 Hydrophobic Association and Volume-Confined Water Molecules -- 8.1 Introduction -- 8.2 Water as a Whole in Hydrophobic Association -- 8.2.1 Background -- 8.2.2 Computational Modeling of Hydrophobic Association -- 8.2.2.1 Explicit versus Implicit Solvent: Is the Computational Cost Motivated? -- 8.3 Confined Water Molecules in Protein-Ligand Binding -- 8.3.1 Protein Hydration Sites -- 8.3.2 Thermodynamics of Volume-Confined Water Localization -- 8.3.3 Computational Modeling of Volume-Confined Water Molecules -- 8.3.4 Identifying Hydration Sites -- 8.3.5 Water in Protein-Ligand Docking -- Acknowledgments -- References -- 9 Implicit Solvent Models and Electrostatics in Molecular Recognition -- 9.1 Introduction. , 9.2 Poisson-Boltzmann Methods -- 9.3 The Generalized Born Model -- 9.4 Reference Interaction Site Model of Molecular Solvation -- 9.5 Applications -- 9.5.1 The ''MM-PBSA'' Model -- 9.5.2 Rescoring Docking Poses -- 9.5.3 MM/3D-RISM -- Acknowledgments -- References -- 10 Ligand and Receptor Conformational Energies -- 10.1 The Treatment of Ligand and Receptor Conformational Energy in Various Theoretical Formulations of Binding -- 10.1.1 Double Decoupling Free Energy Calculations -- 10.1.2 MM-PB(GB)SA -- 10.1.3 Mining Minima -- 10.1.4 Free Energy Functional Approach -- 10.1.5 Linear Interaction Energy Methods -- 10.1.6 Scoring Functions -- 10.2 Computational Results on Ligand Conformational Energy -- 10.3 Computational Results on Receptor Conformational Energy -- 10.4 Concluding Remarks -- Acknowledgments -- References -- 11 Free Energy Calculations in Drug Lead Optimization -- 11.1 Modern Drug Design -- 11.1.1 In Silico Drug Design -- 11.2 Free Energy Calculations -- 11.2.1 Considerations for Accurate and Precise Results -- 11.3 Example Protocols and Applications -- 11.3.1 Example 1: Disappearing an Ion -- 11.3.2 Example 2: Relative Ligand Binding Strengths -- 11.3.3 Applications -- 11.4 Discussion -- References -- 12 Scoring Functions for Protein-Ligand Interactions -- 12.1 Introduction -- 12.2 Scoring Protein-Ligand Interactions: What for and How to? -- 12.2.1 Knowledge-Based Scoring Functions -- 12.2.2 Force Field-Based Methods -- 12.2.3 Empirical Scoring Functions -- 12.2.4 Further Approaches -- 12.3 Application of Scoring Functions: What Is Possible and What Is Not? -- 12.4 Thermodynamic Contributions and Intermolecular Interactions: Which Are Accounted for and Which Are Not? -- 12.5 Conclusions or What Remains to be Done and What Can be Expected? -- Acknowledgments -- References -- Part IV: Challenges in Molecular Recognition. , 13 Druggability Prediction -- 13.1 Introduction -- 13.2 Druggability: Ligand Properties -- 13.3 Druggability: Ligand Binding -- 13.4 Druggability Prediction by Protein Class -- 13.5 Druggability Predictions: Experimental Methods -- 13.5.1 High-Throughput Screening -- 13.5.2 Fragment Screening -- 13.5.3 Multiple Solvent Crystallographic Screening -- 13.6 Druggability Predictions: Computational Methods -- 13.6.1 Cavity Detection Algorithms -- 13.6.2 Empirical Models -- 13.6.2.1 Training Sets -- 13.6.2.2 Applicability and Prediction Performance -- 13.6.3 Physical Chemistry Predictions -- 13.7 A Test Case: PTP1B -- 13.8 Outlook and Concluding Remarks -- References -- 14 Embracing Protein Plasticity in Ligand Docking -- 14.1 Introduction -- 14.2 Docking by Sampling Internal Coordinates -- 14.3 Fast Docking to Multiple Receptor Conformations -- 14.4 Single Receptor Conformation -- 14.5 Multiple Receptor Conformations -- 14.5.1 Exploiting Existing Experimental Conformational Diversity -- 14.5.2 Selecting ''Important'' Conformations -- 14.5.3 Generating In Silico Models -- 14.6 Improving Poor Homology Models of the Binding Pocket -- 14.7 State of the Art: GPCR Dock 2010 Modeling and Docking Assessment -- 14.8 Conclusions and Outlook -- Acknowledgments -- References -- 15 Prospects of Modulating Protein-Protein Interactions -- 15.1 Introduction -- 15.2 Thermodynamics of Protein-Protein Interactions -- 15.3 CADD Methods for the Identi.cation and Optimization of Small-Molecule Inhibitors of PPIs -- 15.3.1 Identifying Inhibitors of PPIs Using SBDD -- 15.3.1.1 Protein Structure Preparation -- 15.3.1.2 Binding Site Identification -- 15.3.1.3 Virtual Chemical Database -- 15.3.1.4 Virtual Screening of Compound Database -- 15.3.1.5 Rescoring -- 15.3.1.6 Final Selection of Ligands for Experimental Assay -- 15.3.2 Lead Optimization -- 15.3.2.1 Ligand-Based Optimization. , 15.3.2.2 Computation of Binding Free Energy.

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