| 000 -LEADER |
|---|
| fixed length control field |
12554cam a22004577a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
CITU |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20241003124234.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS--GENERAL INFORMATION |
|---|
| fixed length control field |
m o d |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
|---|
| fixed length control field |
cr cnu---unuuu |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
241003b ||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9783527342655 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9783527806843 |
| Qualifying information |
(electronic bk.) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
3527806849 |
| Qualifying information |
(electronic bk.) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9783527806850 |
| Qualifying information |
(electronic bk.) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
3527806857 |
| Qualifying information |
(electronic bk.) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9783527806836 |
| Qualifying information |
(electronic bk.) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
3527806830 |
| Qualifying information |
(electronic bk.) |
| 035 ## - SYSTEM CONTROL NUMBER |
|---|
| System control number |
(OCoLC)1079363260 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
N$T |
| Language of cataloging |
eng |
| Description conventions |
rda |
| -- |
pn |
| Transcribing agency |
N$T |
| Modifying agency |
N$T |
| -- |
DG1 |
| -- |
OCLCF |
| 041 ## - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
eng |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
RM301.3.G45 |
| 072 #7 - SUBJECT CATEGORY CODE |
|---|
| Subject category code |
MED |
| Subject category code subdivision |
071000 |
| Source |
bisacsh |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
615.7 |
| Edition number |
23 |
| 245 00 - TITLE STATEMENT |
|---|
| Title |
Biomolecular simulations in structure-based drug discovery / |
| Statement of responsibility, etc |
edited by Francesco L. Gervasio and Vojtech Spiwok. |
| 264 #1 - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc |
Weinheim, Germany : |
| Name of publisher, distributor, etc |
Wiley-VCH, |
| Date of publication, distribution, etc |
2019. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
1 online resource. |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Content type code |
txt |
| Source |
rdacontent. |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
computer |
| Media type code |
c |
| Source |
rdamedia. |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
online resource |
| Carrier type code |
cr |
| Source |
rdacarrier. |
| 340 ## - PHYSICAL MEDIUM |
|---|
| Source |
rdacc |
| Authority record control number or standard number |
http://rdaregistry.info/termList/RDAColourContent/1003. |
| 490 1# - SERIES STATEMENT |
|---|
| Series statement |
Methods and principles in medicinal chemistry ; |
| Volume number/sequential designation |
volume 75. |
| 505 0# - CONTENTS |
|---|
| Formatted contents note |
Table of Contents<br/>Foreword xiii<br/><br/>Part I Principles 1<br/><br/>1 Predictive Power of Biomolecular Simulations 3<br/>Vojtech Spiwok<br/><br/>1.1 Design of Biomolecular Simulations 4<br/><br/>1.2 Collective Variables and Trajectory Clustering 6<br/><br/>1.3 Accuracy of Biomolecular Simulations 8<br/><br/>1.4 Sampling 10<br/><br/>1.5 Binding Free Energy 14<br/><br/>1.6 Convergence of Free Energy Estimates 16<br/><br/>1.7 Future Outlook 20<br/><br/>References 21<br/><br/>2 Molecular Dynamics–Based Approaches Describing Protein Binding 29<br/>Andrea Spitaleri and Walter Rocchia<br/><br/>2.1 Introduction 29<br/><br/>2.1.1 Protein Binding: Molecular Dynamics Versus Docking 30<br/><br/>2.1.2 Molecular Dynamics –The Current State of the Art 31<br/><br/>2.2 Protein–Protein Binding 32<br/><br/>2.3 Protein–Peptide Binding 34<br/><br/>2.4 Protein–Ligand Binding 36<br/><br/>2.5 Future Directions 38<br/><br/>2.5.1 Modeling of Cation-p Interactions 38<br/><br/>2.6 Grand Challenges 39<br/><br/>References 39<br/><br/>Part II Advanced Algorithms 43<br/><br/>3 Modeling Ligand–Target Binding with Enhanced Sampling Simulations 45<br/>Federico Comitani and Francesco L. Gervasio<br/><br/>3.1 Introduction 45<br/><br/>3.2 The Limits of Molecular Dynamics 46<br/><br/>3.3 TemperingMethods 47<br/><br/>3.4 Multiple Replica Methods 48<br/><br/>3.5 Endpoint Methods 50<br/><br/>3.5.1 Alchemical Methods 50<br/><br/>3.6 Collective Variable-Based Methods 51<br/><br/>3.6.1 Metadynamics 52<br/><br/>3.7 Binding Kinetics 57<br/><br/>3.8 Conclusions 59<br/><br/>References 60<br/><br/>4 Markov State Models in Drug Design 67<br/>Bettina G. Keller, Stevan Aleksic, and Luca Donati<br/><br/>4.1 Introduction 67<br/><br/>4.2 Markov State Models 68<br/><br/>4.2.1 MD Simulations 68<br/><br/>4.2.2 The Molecular Ensemble 69<br/><br/>4.2.3 The Propagator 69<br/><br/>4.2.4 The Dominant Eigenspace 70<br/><br/>4.2.5 The Markov State Model 72<br/><br/>4.3 Microstates 75<br/><br/>4.4 Long-Lived Conformations 77<br/><br/>4.5 Transition Paths 79<br/><br/>4.6 Outlook 81<br/><br/>Acknowledgments 82<br/><br/>References 82<br/><br/>5 Monte Carlo Techniques for Drug Design: The Success Case of PELE 87<br/>Joan F. Gilabert, Daniel Lecina, Jorge Estrada, and Victor Guallar<br/><br/>5.1 Introduction 87<br/><br/>5.1.1 First Applications 88<br/><br/>5.1.2 Free Energy Calculations 88<br/><br/>5.1.3 Optimization 88<br/><br/>5.1.4 MC and MD Combinations 89<br/><br/>5.2 The PELE Method 90<br/><br/>5.2.1 MC Sampling Procedure 91<br/><br/>5.2.2 Ligand Perturbation 91<br/><br/>5.2.3 Receptor Perturbation 91<br/><br/>5.2.4 Side-Chain Adjustment 93<br/><br/>5.2.5 Minimization 93<br/><br/>5.2.6 Coordinate Exploration 93<br/><br/>5.2.7 Energy Function 94<br/><br/>5.3 Examples of PELE’s Applications 94<br/><br/>5.3.1 Mapping Protein Ligand and Biomedical Studies 94<br/><br/>5.3.2 Enzyme Characterization 96<br/><br/>Acknowledgments 97<br/><br/>References 97<br/><br/>6 Understanding the Structure and Dynamics of Peptides and Proteins Through the Lens of Network Science 105<br/>Mathieu Fossepre, Laurence Leherte, Aatto Laaksonen, and Daniel P. Vercauteren<br/><br/>6.1 Insight into the Rise of Network Science 105<br/><br/>6.2 Networks of Protein Structures: Topological Features and Applications 107<br/><br/>6.2.1 Topological Features and Analysis of Networks: A Brief Overview 107<br/><br/>6.2.2 Centrality Measures and Protein Structures 110<br/><br/>6.2.3 Software 114<br/><br/>6.3 Networks of Protein Dynamics: Merging Molecular Simulation Methods and Network Theory 117<br/><br/>6.3.1 Molecular Simulations: A Brief Overview 117<br/><br/>6.3.2 How Can Network Science Help in the Analysis of Molecular Simulations? 118<br/><br/>6.3.3 Software 119<br/><br/>6.4 Coarse-Graining and Elastic Network Models: Understanding Protein Dynamics with Networks 120<br/><br/>6.4.1 Coarse-Graining: A Brief Overview 120<br/><br/>6.4.2 Elastic Network Models: General Principles 123<br/><br/>6.4.3 Elastic Network Models: The Design of Residue Interaction Networks 124<br/><br/>6.5 Network Modularization to Understand Protein Structure and Function 128<br/><br/>6.5.1 Modularization of Residue Interaction Networks 128<br/><br/>6.5.2 Toward the Design of Meso scale Protein Models with Network Modularization Techniques 130<br/><br/>6.6 Laboratory Contributions in the Field of Network Science 131<br/><br/>6.6.1 Graph Reduction of Three-Dimensional Molecular Fields of Peptides and Proteins 132<br/><br/>6.6.2 Design of Multi scale Elastic Network Models to Study Protein Dynamics 135<br/><br/>6.7 Conclusions and Perspectives 140<br/><br/>Acknowledgments 142<br/><br/>References 142<br/><br/>Part III Applications and Success Stories 163<br/><br/>7 From Computers to Bedside: Computational Chemistry Contributing to FDA Approval 165<br/>Christina Athanasiou and Zoe Cournia<br/><br/>7.1 Introduction 165<br/><br/>7.2 Rationalizing the Drug Discovery Process: Early Days 166<br/><br/>7.2.1 Captopril (Capoten®) 167<br/><br/>7.2.2 Saquinavir (Invirase®) 167<br/><br/>7.2.3 Ritonavir (Norvir®) 168<br/><br/>7.3 Use of Computer-Aided Methods in the Drug Discovery Process 168<br/><br/>7.3.1 Ligand-Based Methods 169<br/><br/>7.3.1.1 Overlay of Structures 169<br/><br/>7.3.1.2 Pharmacophore Modeling 171<br/><br/>7.3.1.3 Quantitative Structure–Activity Relationships (QSAR) 172<br/><br/>7.3.2 Structure-Based Methods 173<br/><br/>7.3.2.1 Molecular Docking – Virtual Screening 175<br/><br/>7.3.2.2 Flexible Receptor Molecular Docking 179<br/><br/>7.3.2.3 Molecular Dynamics Simulations 179<br/><br/>7.3.2.4 De Novo Drug Design 180<br/><br/>7.3.2.5 Protein Structure Prediction 181<br/><br/>7.3.2.6 Rucaparib (Zepatier®) 184<br/><br/>7.3.3 Ab InitioQuantumChemical Methods 185<br/><br/>7.4 Future Outlook 186<br/><br/>References 190<br/><br/>8 Application of Biomolecular Simulations to G Protein–Coupled Receptors (GPCRs) 205<br/>Mariona Torrens-Fontanals, TomaszM. Stepniewski, Ismael Rodriguez-Espigares, and Jana Selent<br/><br/>8.1 Introduction 205<br/><br/>8.2 MD Simulations for Studying the Conformational Plasticity of GPCRs 207<br/><br/>8.2.1 Challenges in GPCR Simulations: The Sampling Problem and Simulation Timescales 208<br/><br/>8.2.2 Making Sense Out of Simulation Data 209<br/><br/>8.3 Application of MD Simulations to GPCR Drug Design:Why Should We Use MD? 210<br/><br/>8.4 Evolution of MD Timescales 214<br/><br/>8.5 Sharing MD Data via a Public Database 216<br/><br/>8.6 Conclusions and Perspectives 216<br/><br/>Acknowledgments 217<br/><br/>References 217<br/><br/>9 Molecular Dynamics Applications to GPCR Ligand Design 225<br/>Andrea Bortolato, Francesca Deflorian, Giuseppe Deganutti, Davide Sabbadin,StefanoMoro, and Jonathan S.Mason<br/><br/>9.1 Introduction 225<br/><br/>9.2 The Role of Water in GPCR Structure-Based Ligand Design 226<br/><br/>9.2.1 WaterMap and WaterFLAP 228<br/><br/>9.3 Ligand-Binding Free Energy 230<br/><br/>9.4 Ligand-Binding Kinetics 233<br/><br/>9.4.1 Supervised Molecular Dynamics (SuMD) 235<br/><br/>9.4.2 Adiabatic Bias Metadynamics 238<br/><br/>9.5 Conclusion 241<br/><br/>References 242<br/><br/>10 Ion Channel Simulations 247<br/>Saurabh Pandey, Daniel Bonhenry, and Rudiger H. Ettrich<br/><br/>10.1 Introduction 247<br/><br/>10.2 Overview of Computational Methods Applied to Study Ion Channels 248<br/><br/>10.2.1 Homology Modeling 248<br/><br/>10.2.2 All-atom Molecular Dynamics Simulations 249<br/><br/>10.2.2.1 Force Fields 250<br/><br/>10.2.3 Methods for Calculation of Free Energy 251<br/><br/>10.2.3.1 Free Energy Perturbation 251<br/><br/>10.2.3.2 Umbrella Sampling 251<br/><br/>10.2.3.3 Metadynamics 252<br/><br/>10.2.3.4 Adaptive Biased Force Method 252<br/><br/>10.3 Properties of Ion Channels Studied by Computational Modeling 253<br/><br/>10.3.1 A Refined Atomic Scale Model of the Saccharomyces cerevisiae K+-translocation Protein Trk1p 253<br/><br/>10.3.2 Homology Modeling, Docking, and Mutagenesis Studies of Human Melatonin Receptors 254<br/><br/>10.3.3 Selectivity and Permeation in Voltage-Gated Sodium (NaV) Channels 254<br/><br/>10.3.4 Study of Ion Conduction Mechanism, Favorable Translocation Path,and Ion Selectivity in KcsA Using Free Energy Perturbation and Umbrella Sampling 257<br/><br/>10.3.5 Ion Conductance Calculations 260<br/><br/>10.3.5.1 Voltage-Dependent Anion Channel (VDAC) 261<br/><br/>10.3.5.2 Calculation of Ion Conduction in Low-Conductance GLIC Channel 261<br/><br/>10.3.6 Transient Receptor Potential (TRP) Channels 263<br/><br/>10.4 Free Energy Methods Applied to Channels Bearing Hydrophobic Gates 264<br/><br/>10.5 Conclusion 270<br/><br/>Acknowledgments 271<br/><br/>References 271<br/><br/>11 Understanding Allostery to Design New Drugs 281<br/>Giulia Morra and Giorgio Colombo<br/><br/>11.1 Introduction 281<br/><br/>11.2 Protein Allostery: Basic Concepts and Theoretical Framework 282<br/><br/>11.2.1 The Classic View of Allostery 283<br/><br/>11.2.2 The Thermodynamic Two-State Model of Allostery 283<br/><br/>11.2.3 From Thermodynamics to Protein Structure and Dynamics 285<br/><br/>11.2.4 Entropy in Allostery: The Ensemble Allostery Model 287<br/><br/>11.3 Exploiting Allostery in Drug Discovery and Design 288<br/><br/>11.3.1 Computational Prediction of Allosteric Behavior and Application to Drug Discovery 288<br/><br/>11.3.2 Identification of Allosteric Binding Sites Through Structural and Dynamic approaches 289<br/><br/>11.4 Chaperones 291<br/><br/>11.5 Kinases 293<br/><br/>11.6 GPCRs 294<br/><br/>11.7 Conclusions 296<br/><br/>References 296<br/><br/>12 Structure and Stability of Amyloid Protofibrils of Polyglutamine and Polyasparagine from Molecular Dynamics Simulations 301 <br/>Viet HoangMan, Yuan Zhang, Christopher Roland, and Celeste Sagui<br/><br/>12.1 Introduction 301<br/><br/>12.2 Polyglutamine Protofibrils and Aggregates 303<br/><br/>12.2.1 Investigations of Oligomeric Q8 Structures 303<br/><br/>12.2.2 Time Evolution, Steric Zippers, and Crystal Structures of 4 × 4 Q8Aggregates 306<br/><br/>12.2.3 Monomeric Q40 Protofibrils 308<br/><br/>12.3 Amyloid Models of Asparagine (N) and Glutamine(Q) 311<br/><br/>12.3.1 Initial Structures 313<br/><br/>12.3.2 Monomeric PolyQ βHairpinsAre More Stable than PolyN Hairpins 314<br/><br/>12.3.3 N-rich Oligomers Are Most Stable in Class 1 Steric Zippers with 2-by-2 Interdigitation 315<br/><br/>12.3.4 PolyQ Oligomers Are Most Stable in Antiparallel Stranded β Sheets with 1-by-1 Steric Zippers 316<br/><br/>12.3.5 PolyQ Structures Show Higher Stability than Most Stable PolyN Structures 317<br/><br/>12.3.6 Thermodynamic Considerations of Aggregate Formation 318<br/><br/>12.4 Summary 319<br/><br/>Acknowledgments 320<br/><br/>References 320<br/><br/>13 Using Biomolecular Simulations to Target Cdc34 in Cancer 325<br/>Miriam Di Marco, Matteo Lambrughi, and Elena Papaleo<br/><br/>13.1 Background 325<br/><br/>13.2 Families of E2 Enzymes 327<br/><br/>13.3 Cdc34 Protein Sequence and Structure 328<br/><br/>13.4 Cdc34 Heterogeneous Conformational Ensemble in Solution 329<br/><br/>13.5 Long-Range Communication in Family 3 Enzymes: A Structural Path from the Ub-Binding Site to the E3 Recognition Site 330<br/><br/>13.6 Cdc34 Modulation by Phosphorylation: From Phenotype to Structure 331<br/><br/>13.7 The Dual Role of the Acidic Loop of Cdc34: Regulator of Activity and Interface for E3 Binding 332<br/><br/>13.8 Different Strategies to Target Cdc34 with Small Molecules 333<br/><br/>13.9 Conclusions and Perspectives 334<br/><br/>Acknowledgments 336<br/><br/>References 336<br/><br/>Index 343 |
| 545 0# - BIOGRAPHICAL OR HISTORICAL DATA |
|---|
| Biographical or historical note |
About the Author<br/>Francesco Luigi Gervasio holds a chair in Biomolecular Modelling and is professor of Chemistry and professor of Structural and Molecular Biology at University College London (UK).<br/><br/>Vojtech Spiwok is a researcher of University of Chemistry and Technology, Prague (Czech Republic). He has authored numerous scientific publications on biomolecular simulations with a special emphasis on development and application of enhanced sampling techniques. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Pharmacogenomics. |
| Authority record control number |
http://id.loc.gov/authorities/subjects/sh99000126. |
| 655 #4 - INDEX TERM--GENRE/FORM |
|---|
| Genre/form data or focus term |
Electronic books. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Gervasio, Francesco L., |
| Relator term |
editor. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Spiwok, Vojtech, |
| Relator term |
editor. |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
Methods and principles in medicinal chemistry ; |
| Authority record control number |
http://id.loc.gov/authorities/names/n94037416 |
| Volume number/sequential designation |
volume 75. |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| Uniform Resource Identifier |
https://onlinelibrary.wiley.com/doi/book/10.1002/9783527806836 |
| Link text |
Full text is available at Wiley Online Library Click here to view |
| 942 ## - ADDED ENTRY ELEMENTS |
|---|
| Source of classification or shelving scheme |
|
| Item type |
BOOK |