Includes bibliographical references and index.

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 interaction, followed by a comparison of the four key experimental methods (calorimetry, surface plasmon resonance, NMR and X-ray crystallography) used in generating interaction data. The second half of the book is devoted to in-silico methods of modeling and predicting molecular recognition and binding. 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.

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 AreaMethod1.4.5 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 Dependence3.1 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 Background4.2 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 Targets4.5.5 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.

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