
Protein-Ligand Interactions.
Title:
Protein-Ligand Interactions.
Author:
Mannhold, Raimund.
ISBN:
9783527645978
Personal Author:
Edition:
1st ed.
Physical Description:
1 online resource (361 pages)
Series:
Methods and Principles in Medicinal Chemistry Ser. ; v.53
Methods and Principles in Medicinal Chemistry Ser.
Contents:
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.
Abstract:
Innovative and forward-looking, this volume focuses on recent achievements in this rapidly progressing field and looks at future potential for development. The first part provides a basic understanding of the factors governing protein-ligand interactions, followed by a comparison of key experimental methods (calorimetry, surface plasmon resonance, NMR) used in generating interaction data. The second half of the book is devoted to insilico methods of modeling and predicting molecular recognition and binding, ranging from first principles-based to approximate ones. Here, as elsewhere in the book, emphasis is placed on novel approaches and recent improvements to established methods. The final part looks at unresolved challenges, and the strategies to address them. With the content relevant for all drug classes and therapeutic fields, this is an inspiring and often-consulted guide to the complexity of protein-ligand interaction modeling and analysis for both novices and experts.
Local Note:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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