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Virtual Screening for Bioactive Molecules [Hardback]

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  • Formāts: Hardback, 325 pages, height x width: 245x175 mm, weight: 740 g, Illustrations
  • Sērija : Methods and Principles in Medicinal Chemistry
  • Izdošanas datums: 10-Oct-2000
  • Izdevniecība: Wiley-VCH Verlag GmbH
  • ISBN-10: 3527301534
  • ISBN-13: 9783527301539
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  • Cena: 146,18 €*
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  • Formāts: Hardback, 325 pages, height x width: 245x175 mm, weight: 740 g, Illustrations
  • Sērija : Methods and Principles in Medicinal Chemistry
  • Izdošanas datums: 10-Oct-2000
  • Izdevniecība: Wiley-VCH Verlag GmbH
  • ISBN-10: 3527301534
  • ISBN-13: 9783527301539
Citas grāmatas par šo tēmu:
1>Recent progress in high-throughput screening, combinatorial chemistry and molecular biology has radically changed the approach to drug discovery in the pharmaceutical industry. New challenges in synthesis result in new analytical methods. At present, typically 100,000 to one million molecules have to be tested within a short period and, therefore, highly effective screening methods are necessary for today's researchers - preparing and characterizing one compound after another belongs to the past. Intelligent, computer-based search agents are needed and "virtual screening" provides solutions to many problems. Such screening comprises innovative computational techniques designed to turn raw data into valuable chemical information and to assist in extracting the relevant molecular features.

This handbook is unique in bringing together the various efforts in the field of virtual screening to provide the necessary methodological framework for more effective research. Leading experts give a thorough introduction to the state of the art along with a critical assessment of both successful applications and drawbacks. The information collated here will be indispensable for experienced scientists, as well as novices, working in medicinal chemistry and related disciplines.

Recenzijas

"There is little in the book that can be criticised" (Chemistry & Industry, 19 November, 2001)

Preface v A Personal Foreword vi List of Contributors xiii Prologue xvii Jonathan Knowles High-Throughput Screening and Virtual Screening: Entry Points to Drug Discovery 1(14) Richard M. Eglen Gisbert Schneider Hans-Joachim Bohm Introduction 1(2) Miniaturization and Detection Strategies 3(4) Screening Plate Format and Fluidics 3(1) Detection Strategies 4(1) Cell-Based Reporter Gene Assays 5(1) Fluorescence Correlation Spectroscopy 6(1) Microchip Fabrication 6(1) Remarks and Summary 6(1) Compound Libraries 7(3) Multi-Dimensional Optimization: Qualifying HTS Lead Candidates 10(3) Conclusions 13(2) References 14(1) Library Filtering Systems and Prediction of Drug-Like Properties 15(18) W. Patrick Walters Mark A. Murcko Introduction 15(1) Simple Counting Methods to Predict Drug-Likeness 15(2) Functional Group Filters 17(6) ``Chemistry Space Methods 23(1) Examination of Building Blocks in Known Drugs 24(4) Other Methods 28(2) Conclusions and Future Directions 30(3) References 31(2) Prediction of Physicochemical Properties 33(26) Jeff J. Morris Pierre P. Bruneau Introduction 33(1) Prediction of Lipophilicity 33(9) Fragment-Based Methods 34(2) Methods Based on Molecular Properties 36(2) Predictive Ability of Existing Techniques 38(2) Other Solvent Systems 40(1) Effect of Ionization 41(1) Prediction of Solubility 42(7) Fragmental Approaches 42(2) Property-Based Methods 44(4) Conclusions 48(1) Prediction of pKa 49(4) Fragment-Based Methods 50(1) Methods Based on Molecular Properties 51(2) Conclusions 53(1) Prediction of Protein Binding 53(2) Conclusions 55(4) References 56(3) Descriptor-Based Similarity Measures for Screening Chemical Databases 59(22) John M. Barnard Geoffrey M. Downs Peter Willett Introduction 59(1) Fragment-Based Similarity Searching 60(2) Association and Distance Coefficients for Similarity Searching 62(8) Structural Representations for Similarity Searching 70(7) Descriptor Selection 71(4) Descriptor Encoding 75(2) Conclusions 77(4) References 79(2) Modelling Structure--Activity Relationships 81(36) Gianpaolo Bravi Emanuela Gancia Darren V. S. Green Mike M. Hann Introduction 81(1) Hansch Analysis 82(2) 3-D QSAR 84(5) Alignment-Free 3-D Descriptors 89(6) Topological Descriptors 95(4) Pharmacophores and Pharmacophoric Keys 99(4) Conclusions 103(2) Appendix--Statistical Techniques in QSAR and Pattern Recognition 105(12) Data Reduction and Display 105(1) Principal Component Analysis 105(1) Non-Linear Mapping 106(1) Neural Networks 107(1) Regression Techniques 107(1) Multiple Linear Regression 107(2) Principal Component Regression and Partial Least Squares 109(2) Classification Techniques 111(1) Linear Discriminant Analysis 111(1) Soft Independent Modelling of Class Analogy 111(1) Recursive Partitioning 112(1) References 113(4) Database Profiling by Neural Networks 117(14) Jens Sadowski ``Drug-Likeness: A General Compound Property? 117(1) Methods and Programs 118(2) Databases 118(1) Descriptors 118(1) Classification Tools 119(1) Complete Algorithm 119(1) Applications 120(8) Drug-Likeness and a Recipe for a Computational Filter 120(2) Crop Protection Compounds 122(2) Virtual High-Throughput Screens 124(2) Optimization of Combinatorial Libraries 126(2) Conclusions 128(3) References 128(3) Pharmacophore Pattern Application in Virtual Screening, Library Design and QSAR 131(30) Andrew C. Good Jonathan S. Mason Stephen D. Pickett Introduction 131(1) Preparations for Pharmacophore Screening 131(5) 3-D Structure Generation 132(1) Pharmacophore Atom-Typing 132(1) Conformational Flexibility 133(2) Conformation Search Techniques 135(1) Torsion Fitting 136(1) Screening by Single Pharmacophore: Elucidation and Execution 136(2) Pharmacophore Constrained Structure-Based Virtual Screening 138(2) Pharmacophores as Full Molecular Descriptors 140(16) Screening by Molecular Similarity 142(1) Geometric Atom Pair Descriptors 143(1) Fingerprints Based on Pharmacophore Triplets and Quartets 144(3) Relative Diversity/Similarity Using Pharmacophores 147(1) Pharmacophore Fingerprints from Protein-Binding Sites 148(2) Combinatorial Library Design Using Pharmacophore Fingerprint Ensemble 150(1) Binary Pharmacophore Ensemble Descriptors and Beyond 150(5) Pharmacophore Fingerprint Ensembles as QSAR Descriptors 155(1) Conclusions 156(5) References 156(5) Evolutionary Molecular Design in Virtual Fitness Landscapes 161(26) Gisbert Schneider Introduction 161(1) De Novo Design is an Optimization Process 162(3) An Evolution Strategy for Systematic Search in Chemical Space 165(3) Structure of Chemical Space and the ``Principle of Strong Causality 168(4) Spanning a Topological Pharmacophore Space for Similarity Searching 172(4) Combinatorial Evolutionary Design of ``Drug-Like Molecules 176(7) Conclusions 183(4) References 184(3) Practical Approaches to Evolutionary Design 187(20) Lutz Weber Introduction 187(1) The Structure of the Search Space 188(2) Genetic Algorithms 190(3) Genetic Operators and the Building Block Hypothesis 193(1) Practical Examples 194(5) Efficiency of Genetic Algorithms 199(5) The Use of GA-Driven Evolutionary Experiments 204(3) References 205(2) Understanding Receptor--Ligand Interactions as a Prerequisite for Virtual Screening 207(22) Gerhard Klebe Ulrich Gradler Sven Gruneberg Oliver Kramer Holger Gohlke Introduction 207(1) The Structure of the Target Protein: Starting Point for Virtual Screening Experiments 207(1) Thermodynamic Parameters Determining Ligand Binding 208(2) Spatial Location of Putative Interaction Sites Between Ligands and Proteins 210(2) Using Putative Interaction Sites for the Placement of Possible Ligands 212(1) Consecutive Hierachical Filtering as a Strategy for Virtual Screening of Larger Ligands 213(3) Of Ultimate Importance: A Discriminative and Reliable Scoring Function 216(1) The Targets used for Virtual Screening 217(7) First Leads for tRNA-Guanin-Transglycosylase by Searches with LUDI 217(3) Commercially Available Candidates with Carbonic Anhydrase Inhibitory Potency Discovered by a Structure-Based Pharmacophore Hypothesis 220(2) Virtual Screening with Aldose Reductase, an Enzyme Performing Pronounced Induced Fit upon Ligand Binding 222(2) 3-D QSAR Analysis to Rank and Predict Binding Affinities of Mutually Superimposed Ligands 224(1) Summary and Conclusions 225(4) References 226(3) Structure-Based Library Design 229(36) Martin Stahl Introduction 229(3) Scoring Functions for Receptor--Ligand Interactions 232(8) Force Field-Based Methods 232(1) Empirical Scoring Functions 233(2) Knowledge-Based Methods 235(2) Assessment of Current Scoring Functions for Virtual Screening 237(3) Receptor--Ligand Docking 240(6) Docking of Rigid Molecules 241(1) Conformationally Flexible Docking 242(1) Multi-Conformer Docking 243(1) Incremental Construction Algorithms 243(1) Stochastic Search Algorithms 244(1) Current Status of Docking Methods 245(1) Ligand Design 246(5) De Novo Design Techniques 247(3) Design of Combinatorial Libraries 250(1) Practical Applictions of Structure-Based Library Design 251(7) Database Ranking 251(4) Design of Combinatorial Libraries 255(3) Conclusions 258(7) References 259(6) The Measurement of Molecular Diversity 265(36) Dimitris K. Agrafiotis Victor S. Lobanov Dmitrii N. Rassokhin Sergei Izrailev Introduction 265(1) Diversity Metrics 266(14) Distance-Based Diversity Metrics 266(9) Cell-Based Diversity Metrics 275(3) Variance-Based Diversity Metrics 278(2) Diversity Spaces 280(6) Two-Dimensional Descriptors 280(2) Three-Dimensional Descriptors 282(1) Physicochemical and Electronic Descriptors 283(1) Dimensionality Reduction 283(3) Diversity Sampling 286(3) Selection Algorithms 286(2) Reagents versus Products 288(1) Advanced Techniques 289(8) Conclusions 297(4) References 299(2) Index 301