Holger Gohlke is Professor of Pharmaceutical and Medicinal Chemistry at the Heinrich-Heine-University, Düsseldorf, Germany. He obtained his diploma in chemistry from the Technical University of Darmstadt and his PhD from Philipps-University, Marburg, working with Gerhard Klebe, where he developed the DrugScore and AFMoC approaches. He then did postdoctoral research at The Scripps Research Institute, La Jolla, USA, working with David Case on developing and evaluating computational biophysical methods to predict protein-protein interactions. After appointments as Assistant Professor at Goethe University Frankfurt and Professor at Christian-Albrechts-University, Kiel, he moved to Düsseldorf in 2009. He was awarded the 'Innovationspreis in Medizinischer und Pharmazeutischer Chemie' from the Gesellschaft Deutscher Chemiker and the Deutsche Pharmazeutische Gesellschaft, and the Hansch Award of the Cheminformatics and QSAR Society.His current research focuses on the understanding, prediction, and modulation of interactions involving biological macromolecules from a theoretical perspective. His group applies and develops techniques grounded in bioinformatics, computational biology, and computational biophysics.
Innovative and forward-looking, this volume focuses on recent achievements in this rapidly progressing field and looks at future potential fordevelopment. 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 atunresolved 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 ofprotein-ligand interaction modeling and analysis for both novices and experts.
Key content for every medicinal chemist: The understanding of ligand-target interactions is the basic skill that every medicinal chemist needs.
- Key content for every medicinal chemist: The understanding of ligand-target interactions is the basic skill that every medicinal chemist needs.
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.
PREFACE
PART I: Binding Thermodynamics
STATISTICAL THERMODYNAMICS OF BINDING AND MOLECULAR RECOGNITION MODELS
Introductory Remarks
The Binding Constant and Free Energy
A Statistical Mechanical Treatment of Binding
Strategies for Calculating Binding Free Energies
SOME PRACTICAL RULES FOR THE THERMODYNAMIC OPTIMIZATION
OF DRUG CANDIDATES
Engineering Binding Contributions
Eliminating Unfavorable Enthalpy
Improving Binding Enthalpy
Improving Binding Affinity
Improving Selectivity
Thermodynamic Optimization Plot
ENTHALPY?ENTROPY COMPENSATION AS DEDUCED FROM MEASUREMENTS
OF TEMPERATURE DEPENDENCE
Introduction
The Current Status of Enthalpy?Entropy Compensation
Measurement of the Entropy and Enthalpy of Activation
An Example
The Compensation Temperature
Effect of High Correlation on Estimates of Entropy and Enthalpy
Evolutionary Considerations
Textbooks
PART II: Learning from Biophysical Experiments
INTERACTION KINETIC DATA GENERATED BY SURFACE PLASMON RESONANCE BIOSENSORS AND THE USE OF KINETIC RATE CONSTANTS IN LEAD GENERATION AND OPTIMIZATION
Background
SPR Biosensor Technology
From Interaction Models to Kinetic Rate Constants and Affinity
Affinity versus Kinetic Rate Constants for Evaluation of Interactions
From Models to Mechanisms
Structural Information
The Use of Kinetic Rate Constants in Lead Generation and Optimization
Designing Compounds with Optimal Properties
Conclusions
NMR METHODS FOR THE DETERMINATION OF PROTEIN?LIGAND INTERACTIONS
Experimental Parameters from NMR
Aspects of Protein?Ligand Interactions That Can Be Addressed by NMR
Ligand-Induced Conformational Changes of a Cyclic Nucleotide Binding Domain
Ligand Binding to GABARAP Binding Site and Affinity Mapping
Transient Binding of Peptide Ligands to Membrane Proteins
PART III: Modeling Protein?Ligand Interactions
POLARIZABLE FORCE FIELDS FOR SCORING PROTEIN?LIGAND INTERACTIONS
Introduction and Overview
AMOEBA Polarizable Potential Energy Model
AMOEBA Explicit Water Simulation Applications
Implicit Solvent Calculation Using AMOEBA Polarizable Force Field
Conclusions and Future Directions
QUANTUM MECHANICS IN STRUCTURE-BASED LIGAND DESIGN
Introduction
Three MM-Based Methods
QM-Based Force Fields
QM Calculations of Ligand Binding Sites
QM/MM Calculations
QM Calculations of Entire Proteins
Concluding Remarks
HYDROPHOBIC ASSOCIATION AND VOLUME-CONFINED WATER MOLECULES
Introduction
Water as a Whole in Hydrophobic Association
Confined Water Molecules in Protein?Ligand Binding
IMPLICIT SOLVENT MODELS AND ELECTROSTATICS IN MOLECULAR RECOGNITION
Introduction
Poisson?Boltzmann Methods
The Generalized Born Model
Reference Interaction Site Model of Molecular Solvation
Applications
LIGAND AND RECEPTOR CONFORMATIONAL ENERGIES
The Treatment of Ligand and Receptor Conformational Energy in Various Theoretical Formulations of Binding
Computational Results on Ligand Conformational Energy
Computational Results on Receptor Conformational Energy
Concluding Remarks
FREE ENERGY CALCULATIONS IN DRUG LEAD OPTIMIZATION
Modern Drug Design
Free Energy Calculations
Example Protocols and Applications
Discussion
SCORING FUNCTIONS FOR PROTEIN?LIGAND INTERACTIONS
Introduction
Scoring Protein?Ligand Interactions: What for and How to?
Application of Scoring Functions: What Is Possible and What Is Not?
Thermodynamic Contributions and Intermolecular Interactions: Which Are Accounted for and Which Are Not?
Conclusions or What Remains to be Done and What Can be Expected?
PART IV: Challenges in Molecular Recognition
DRUGGABILITY PREDICTION
Introduction
Druggability: Ligand Properties
Holger Gohlke is Professor of Pharmaceutical and Medicinal Chemistry at the Heinrich-Heine-University, Düsseldorf, Germany. He obtained his diploma in chemistry from the Technical University of Darmstadt and his PhD from Philipps-University, Marburg, working with Gerhard Klebe, where he developed the DrugScore and AFMoC approaches. He then did postdoctoral research at The Scripps Research Institute, La Jolla, USA, working with David Case on developing and evaluating computational biophysical methods to predict protein-protein interactions. After appointments as Assistant Professor at Goethe University Frankfurt and Professor at Christian-Albrechts-University, Kiel, he moved to Düsseldorf in 2009.
He was awarded the 'Innovationspreis in Medizinischer und Pharmazeutischer Chemie' from the Gesellschaft Deutscher Chemiker and the Deutsche Pharmazeutische Gesellschaft, and the Hansch Award of the Cheminformatics and QSAR Society.
His current research focuses on the understanding, prediction, and modulation of interactions involving biological macromolecules from a theoretical perspective. His group applies and develops techniques grounded in bioinformatics, computational biology, and computational biophysics.
Über den Autor
Holger Gohlke is Professor of Pharmaceutical and Medicinal Chemistry at the Heinrich-Heine-University, Düsseldorf, Germany. He obtained his diploma in chemistry from the Technical University of Darmstadt and his PhD from Philipps-University, Marburg, working with Gerhard Klebe, where he developed the DrugScore and AFMoC approaches. He then did postdoctoral research at The Scripps Research Institute, La Jolla, USA, working with David Case on developing and evaluating computational biophysical methods to predict protein-protein interactions. After appointments as Assistant Professor at Goethe University Frankfurt and Professor at Christian-Albrechts-University, Kiel, he moved to Düsseldorf in 2009. nHe was awarded the 'Innovationspreis in Medizinischer und Pharmazeutischer Chemie' from the Gesellschaft Deutscher Chemiker and the Deutsche Pharmazeutische Gesellschaft, and the Hansch Award of the Cheminformatics and QSAR Society.nHis current research focuses on the understanding, prediction, and modulation of interactions involving biological macromolecules from a theoretical perspective. His group applies and develops techniques grounded in bioinformatics, computational biology, and computational biophysics.n
Inhaltsverzeichnis
PREFACEnnPART I: Binding ThermodynamicsnnSTATISTICAL THERMODYNAMICS OF BINDING AND MOLECULAR RECOGNITION MODELSnIntroductory RemarksnThe Binding Constant and Free EnergynA Statistical Mechanical Treatment of BindingnStrategies for Calculating Binding Free EnergiesnnSOME PRACTICAL RULES FOR THE THERMODYNAMIC OPTIMIZATIONnOF DRUG CANDIDATESnEngineering Binding ContributionsnEliminating Unfavorable EnthalpynImproving Binding EnthalpynImproving Binding AffinitynImproving SelectivitynThermodynamic Optimization PlotnnENTHALPY?ENTROPY COMPENSATION AS DEDUCED FROM MEASUREMENTSnOF TEMPERATURE DEPENDENCEnIntroductionnThe Current Status of Enthalpy?Entropy CompensationnMeasurement of the Entropy and Enthalpy of ActivationnAn ExamplenThe Compensation TemperaturenEffect of High Correlation on Estimates of Entropy and EnthalpynEvolutionary ConsiderationsnTextbooksnnPART II: Learning from Biophysical ExperimentsnnINTERACTION KINETIC DATA GENERATED BY SURFACE PLASMON RESONANCE BIOSENSORS AND THE USE OF KINETIC RATE CONSTANTS IN LEAD GENERATION AND OPTIMIZATIONnBackgroundnSPR Biosensor TechnologynFrom Interaction Models to Kinetic Rate Constants and AffinitynAffinity versus Kinetic Rate Constants for Evaluation of InteractionsnFrom Models to MechanismsnStructural InformationnThe Use of Kinetic Rate Constants in Lead Generation and OptimizationnDesigning Compounds with Optimal PropertiesnConclusionsnnNMR METHODS FOR THE DETERMINATION OF PROTEIN?LIGAND INTERACTIONSnExperimental Parameters from NMRnAspects of Protein?Ligand Interactions That Can Be Addressed by NMRnLigand-Induced Conformational Changes of a Cyclic Nucleotide Binding DomainnLigand Binding to GABARAP Binding Site and Affinity MappingnTransient Binding of Peptide Ligands to Membrane ProteinsnnPART III: Modeling Protein?Ligand InteractionsnnPOLARIZABLE FORCE FIELDS FOR SCORING PROTEIN?LIGAND INTERACTIONSnIntroduction and OverviewnAMOEBA Polarizable Potential Energy ModelnAMOEBA Explicit Water Simulation ApplicationsnImplicit Solvent Calculation Using AMOEBA Polarizable Force FieldnConclusions and Future DirectionsnnQUANTUM MECHANICS IN STRUCTURE-BASED LIGAND DESIGNnIntroductionnThree MM-Based MethodsnQM-Based Force FieldsnQM Calculations of Ligand Binding SitesnQM/MM CalculationsnQM Calculations of Entire ProteinsnConcluding RemarksnnHYDROPHOBIC ASSOCIATION AND VOLUME-CONFINED WATER MOLECULESnIntroductionnWater as a Whole in Hydrophobic AssociationnConfined Water Molecules in Protein?Ligand BindingnnIMPLICIT SOLVENT MODELS AND ELECTROSTATICS IN MOLECULAR RECOGNITIONnIntroductionnPoisson?Boltzmann MethodsnThe Generalized Born ModelnReference Interaction Site Model of Molecular SolvationnApplicationsnnLIGAND AND RECEPTOR CONFORMATIONAL ENERGIESnThe Treatment of Ligand and Receptor Conformational Energy in Various Theoretical Formulations of BindingnComputational Results on Ligand Conformational EnergynComputational Results on Receptor Conformational EnergynConcluding RemarksnnFREE ENERGY CALCULATIONS IN DRUG LEAD OPTIMIZATIONnModern Drug DesignnFree Energy CalculationsnExample Protocols and ApplicationsnDiscussionnnSCORING FUNCTIONS FOR PROTEIN?LIGAND INTERACTIONSnIntroductionnScoring Protein?Ligand Interactions: What for and How to?nApplication of Scoring Functions: What Is Possible and What Is Not?nThermodynamic Contributions and Intermolecular Interactions: Which Are Accounted for and Which Are Not?nConclusions or What Remains to be Done and What Can be Expected?nnPART IV: Challenges in Molecular RecognitionnnDRUGGABILITY PREDICTIONnIntroductionnDruggability: Ligand PropertiesnDruggability: Ligand BindingnDruggability Prediction by Protein ClassnDruggability Predictions: Experimental MethodsnDruggability Predictions: Computational MethodsnA Test Case: PTP1BnOutlook and Concluding RemarksnnEMBRACING PROTEIN PLASTICITY IN LIGAND DOCKINGnIntroductionnDocking by Sampling Internal CoordinatesnFast Docking to Multiple Receptor ConformationsnSingle Receptor ConformationnMultiple Receptor ConformationsnImproving Poor Homology Models of the Binding PocketnState of the Art: GPCR Dock 2010 Modeling and Docking AssessmentnConclusions and OutlooknnPROSPECTS OF MODULATING PROTEIN?PROTEIN INTERACTIONSnIntroductionnThermodynamics of Protein?Protein InteractionsnCADD Methods for the Identification and Optimization of Small-Molecule Inhibitors of PPIsnExamples of CADD Applied to PPIsnSummaryn
Klappentext
Innovative and forward-looking, this volume focuses on recent achievements in this rapidly progressing field and looks at future potential forndevelopment. nThe 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,nas elsewhere in the book, emphasis is placed on novel approaches and recent improvements to established methods. The final part looks atnunresolved challenges, and the strategies to address them.nWith the content relevant for all drug classes and therapeutic fields, this is an inspiring and often-consulted guide to the complexity ofnprotein-ligand interaction modeling and analysis for both novices and experts.
