LEADER 05302nam 2200637 450 001 9910830794003321 005 20170817192305.0 010 $a3-527-67703-8 010 $a3-527-67701-1 010 $a3-527-67700-3 035 $a(CKB)2550000001130047 035 $a(EBL)1471874 035 $a(OCoLC)860923427 035 $a(SSID)ssj0001155705 035 $a(PQKBManifestationID)11624544 035 $a(PQKBTitleCode)TC0001155705 035 $a(PQKBWorkID)11187564 035 $a(PQKB)10365726 035 $a(MiAaPQ)EBC1471874 035 $a(PPN)178989681 035 $a(EXLCZ)992550000001130047 100 $a20131109d2014 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aDe novo molecular design /$fedited by Gisbert Schneider ; cover design Mannheim Formgeber 210 1$aWeinheim, Germany :$cWiley-VCH,$d2014. 210 4$dİ2014 215 $a1 online resource (578 p.) 300 $aDescription based upon print version of record. 311 $a3-527-33461-0 311 $a1-299-98843-1 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aDe novo Molecular Design; Title Page; Copyright; Contents; List of Contributors; Foreword; Preface; Chapter 1 De Novo Design: From Models to Molecules; 1.1 Molecular Representation; 1.2 The Molecular Design Cycle; 1.3 Receptor-Ligand Interaction; 1.4 Modeling Fitness Landscapes; 1.4.1 Na ?ive Bayes Classifier; 1.4.2 Artificial Neural Network; 1.4.3 Support Vector Machine; 1.4.4 Gaussian Process; 1.5 Strategies for Compound Construction; 1.6 Strategies for Compound Scoring; 1.6.1 Receptor-Based Scoring; 1.6.2 Ligand-Based Scoring; 1.7 Flashback Forward: A Brief History of De Novo Drug Design 327 $a1.8 ConclusionsAcknowledgments; References; Chapter 2 Coping with Complexity in Molecular Design; 2.1 Introduction; 2.2 A Simple Model of Molecular Interactions; 2.3 Enhancements to the Simple Complexity Model; 2.4 Enumerating and Sampling the Complexity of Chemical Space; 2.5 Validation of the Complexity Model; 2.6 Reductionism and Drug Design; 2.7 Complexity and Information Content as a Factor in De Novo Design; 2.8 Complexity of Thermodynamic Entropy and Drug Design; 2.9 Complex Systems, Emergent Behavior, and Molecular Design; Acknowledgments; References; Chapter 3 The Human Pocketome 327 $a3.1 Predicted Pockets3.2 Compilation of the Validated Human Pocketome; 3.3 Diversity and Redundancy of the Human Pocketome; 3.4 Compound Activity Prediction by Ligand-Pocket Docking and Scoring; 3.4.1 Optimizing Pocket Sets for Reliable Docking and Scoring Results; 3.4.2 Difficult Cases: Unusually Large and Multifunctional Pockets; 3.5 Pocketome-Derived 3D Chemical Fields as Activity Prediction Models; 3.6 Clustering the Ligands by Function and Subpockets; 3.7 Conclusions; Acknowledgments; References; Chapter 4 Structure-Based De Novo Drug Design; 4.1 Introduction 327 $a4.2 Current Progress in SBDND Methodologies4.2.1 Identification of Binding Site; 4.2.2 Design of Molecules; 4.2.2.1 Atom-Based versus Fragment-Based Methods; 4.2.2.2 Pharmacophore-Based Methods; 4.2.3 Searching the Chemical Space; 4.2.3.1 Monte Carlo-Based Methods; 4.2.3.2 Evolutionary Algorithms; 4.2.4 Scoring Methods; 4.2.4.1 Force-Field-Based Scoring Functions; 4.2.4.2 Empirical Scoring Functions; 4.2.4.3 Knowledge-Based Scoring Functions; 4.2.4.4 Consensus Scoring; 4.2.5 Synthetic Accessibility; 4.3 Recent Applications of Structure-Based De Novo Design; 4.4 Perspectives and Conclusion 327 $aAcknowledgmentReferences; Chapter 5 De Novo Design by Fragment Growing and Docking; 5.1 Introduction; 5.2 Case Study I: High-Throughput Screening with Dr Feils; 5.2.1 Target Identification; 5.2.2 Small-Molecule Library Design; 5.2.2.1 Computer Docking; 5.2.2.2 Pharmacophore Searching; 5.2.3 High-Throughput Screening; 5.2.4 Optimization; 5.3 Case Study II: Fragment-Based Drug Design with Dr Goode; 5.3.1 Library Generation; 5.3.1.1 Computational Techniques for Library Refinement; 5.3.2 Detection Methods; 5.3.2.1 Functional/High-Concentration Screening 327 $a5.3.2.2 Fluorescence-Based Thermal Shift Assay (TSA) 330 $aSystematically examining current methods and strategies, this ready reference covers a wide range of molecular structures, from organic-chemical drugs to peptides, proteins and nucleic acids, in line with emerging new drug classes derived from biomacromolecules.A leader in the field and one of the pioneers of this young discipline has assembled here the most prominent experts from across the world to provide first-hand knowledge. While most of their methods and examples come from the area of pharmaceutical discovery and development, the approaches are equally applicable for molecular probe 606 $aDrugs$xDesign 606 $aMolecular structure 615 0$aDrugs$xDesign. 615 0$aMolecular structure. 676 $a639.485 701 $aSchneider$b Gisbert$0855861 701 $aFormgeber$b Mannheim$01702445 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830794003321 996 $aDe novo molecular design$94086984 997 $aUNINA