Virtual screening : principles, challenges, and practical guidelines /: principles, challenges, and practical guidelines. (2011)

• Record Type: Book
• Further Information: Note: Edited by Christoph Sotriffer.
• Other Names: Sotriffer, Christoph
• Contents: List of Contributors XVII Preface XXIII A Personal Foreword XXV Part One Principles 1 1 Virtual Screening of Chemical Space: From Generic Compound Collections to Tailored Screening Libraries 3 ; Markus Boehm 1.1 Introduction 3 1.2 Concepts of Chemical Space 4 1.3 Concepts of Druglikeness and Leadlikeness 6 1.4 Diversity-Based Libraries 8 1.4.1 Concepts of Molecular Diversity 8 1.4.2 Descriptor-Based Diversity Selection 9 1.4.3 Scaffold-Based Diversity Selection 12 1.4.4 Sources of Diversity 13 1.5 Focused Libraries 15 1.5.1 Concepts of Focused Design 15 1.5.2 Ligand-Based Focused Design 16 1.5.3 Structure-Based Focused Design 17 1.5.4 Chemogenomics Approaches 18 1.6 Virtual Combinatorial Libraries and Fragment Spaces 20 1.7 Databases of Chemical and Biological Information 21 1.8 Conclusions and Outlook 24 1.9 Glossary 25 References 26 2 Preparing and Filtering Compound Databases for Virtual and Experimental Screening 35 ; Maxwell D. Cummings, Éric Arnoult, Christophe Buyck, Gary Tresadern, Ann M. Vos, and Jörg K. Wegner 2.1 Introduction 35 2.2 Ligand Databases 36 2.2.1 Chemical Data Structures 36 2.2.2 3D Conformations 38 2.2.3 Data Storage 39 2.2.4 Workflow Tools 39 2.2.5 Past Reviews and Recent Papers 40 2.3 Considering Physicochemical Properties 42 2.3.1 Druglikeness 42 2.3.2 Leadlikeness and Beyond 43 2.4 Undesirables 43 2.4.1 Screening Artifacts 44 2.4.2 Pharmacologically Promiscuous Compounds 45 2.5 Property-Based Filtering for Selected Targets 46 2.5.1 Antibacterials 47 2.5.2 CNS 49 2.5.3 Protein–Protein Interactions 51 2.6 Summary 52 References 53 3 Ligand-Based Virtual Screening 61 ; Herbert Koeppen, Jan Kriegl, Uta Lessel, Christofer S. Tautermann, and Bernd Wellenzohn 3.1 Introduction 61 3.2 Descriptors 62 3.3 Search Databases and Queries 67 3.3.1 Selection of Reference Ligands 67 3.3.2 Preparation of the Search Database 68 3.4 Virtual Screening Techniques 68 3.4.1 Similarity Searches 69 3.4.2 Similarity Searches in Very Large Chemical Spaces 72 3.4.3 Machine Learning in Virtual Screening 74 3.4.4 Validation of Methods and Prediction of Success 78 3.5 Conclusions 79 References 80 4 The Basis for Target-Based Virtual Screening: Protein Structures 87 ; Jason C. Cole, Oliver Korb, Tjelvar S.G. Olsson, and John Liebeschuetz 4.1 Introduction 87 4.2 Selecting a Protein Structure for Virtual Screening 87 4.2.1 Why Are There Errors in Crystal Structures? 87 4.2.2 Possible Problems That May Occur in a Crystal Structure 91 4.2.3 Structural Relevance 95 4.2.4 Critical Evaluation of Models: Recognizing Issues in Structures 98 4.3 Setting Up a Protein Model for vHTS 101 4.3.1 Binding Site Definition 101 4.3.2 Protonation 104 4.3.3 Treatment of Solvent in Docking 104 4.3.4 Use of Protein-Based Constraints in Docking 105 4.3.5 Protein Flexibility 106 4.4 Summary 109 4.5 Glossary of Crystallographic Terms 110 4.5.1 R-Factor 110 4.5.2 Resolution 110 4.5.3 2mFo-DFc Map 110 References 110 5 Pharmacophore Models for Virtual Screening 115 ; Patrick Markt, Daniela Schuster, and Thierry Langer 5.1 Introduction 115 5.2 Compilation of Compounds 116 5.2.1 Chemical Structure Generation 116 5.2.2 Conformational Analysis 116 5.3 Pharmacophore Model Generation 117 5.3.1 State of the Art 117 5.3.2 Structure-Based Methods 117 5.3.3 Ligand-Based Methods 118 5.3.4 Limitations of Ligand-Based Methods 119 5.4 Validation of Pharmacophore Models 119 5.4.1 Chemical Databases for Validation 119 5.4.2 Enrichment Assessment 121 5.4.3 Enrichment Metrics 122 5.4.4 Receiver Operating Characteristic Curve Analysis 124 5.4.5 Area Under the ROC Curve 125 5.5 Pharmacophore-Based Screening 127 5.5.1 DS CATALYST 128 5.5.2 UNITY (GALAHAD/GASP) 128 5.5.3 LIGANDSCOUT 129 5.5.4 MOE 130 5.5.5 PHASE 130 5.6 Postprocessing of Pharmacophore-Based Screening Hits 131 5.6.1 Lead- and Druglikeness 131 5.6.2 Structural Similarity Analysis 131 5.7 Pharmacophore-Based Parallel Screening 132 5.8 Application Examples for Synthetic Compound Screening 133 5.8.1 17b-Hydroxysteroid Dehydrogenase 1 Inhibitors 133 5.8.2 Cannabinoid Receptor 2 (CB2) Ligands 134 5.8.3 Further Application Examples 136 5.9 Application Examples for Natural Product Screening 136 5.9.1 Cyclooxygenase (COX) Inhibitors 139 5.9.2 Sigma-1 (s1) Receptor Ligands 139 5.9.3 Acetylcholinesterase Inhibitors 140 5.9.4 Human Rhinovirus Coat Protein Inhibitors 141 5.9.5 Quorum-Sensing Inhibitors 141 5.9.6 Peroxisome Proliferator-Activated Receptor c Ligands 141 5.9.7 b-Ketoacyl-Acyl Carrier Protein Synthase III Inhibitors 142 5.9.8 5-Lipoxygenase Inhibitors 142 5.9.9 11b-Hydroxysteroid Dehydrogenase Type 1 Inhibitors 142 5.9.10 Pharmacophore-Based Parallel Screening of Natural Products 143 5.10 Conclusions 143 References 144 6 Docking Methods for Virtual Screening: Principles and Recent Advances 153 ; Didier Rognan 6.1 Principles of Molecular Docking 153 6.1.1 Sampling Degrees of Freedom of the Ligand 154 6.1.2 Scoring Ligand Poses 156 6.2 Docking-Based Virtual Screening Flowchart 158 6.2.1 Ligand Setup 158 6.2.2 Protein Setup 159 6.2.3 Docking 160 6.2.4 Postdocking Analysis 161 6.3 Recent Advances in Docking-Based VS Methods 162 6.3.1 Novel Docking Algorithms 162 6.3.2 Fragment Docking 164 6.3.3 Postdocking Refinement 164 6.3.4 Addressing Protein Flexibility 166 6.3.5 Solvated or Dry? 168 6.4 Future Trends in Docking 168 References 169 Part Two Challenges 177 7 The Challenge of Affinity Prediction: Scoring Functions for Structure-Based Virtual Screening 179 ; Christoph Sotriffer and Hans Matter 7.1 Introduction 179 7.2 Physicochemical Basis of Protein–Ligand Recognition 180 7.3 Classes of Scoring Functions 185 7.3.1 Force Field-Based Methods 185 7.3.2 Empirical Scoring Functions 189 7.3.3 Knowledge-Based Scoring Functions 191 7.4 Interesting New Approaches to Scoring Functions 192 7.4.1 Improved Treatment of Hydrophobicity and Dehydration 192 7.4.2 Development and Validation of SFCscore 194 7.4.3 Consensus Scoring 195 7.4.4 Tailored Scoring Functions 196 7.4.5 Structural Interaction Fingerprints 199 7.5 Comparative Assessment of Scoring Functions 200 7.6 Tailoring Scoring Strategies in Virtual Screening 203 7.6.1 Toward a Strategy for Applying Scoring Functions 203 7.6.2 Retrospective Validation Prior to Prospective Virtual Screening 204 7.6.3 Lessons Learned: Improvements in Scoring Evaluations 205 7.6.4 Postfiltering Results of Virtual Screenings 205 7.7 Caveats for Development of Scoring Functions 206 7.7.1 General Points 206 7.7.2 Biological Data 207 7.7.3 Structural Data on Protein–Ligand Complexes and Decoy Data Sets 207 7.7.4 Cooperativity and Other Model Defic
• Publisher Details: Place of publication not identified : Wiley-VCH
• Publication Date: 2011
• Extent: 1 online resource (550 pages)
• Subjects: 615.1900113; High throughput screening (Drug development) -- Computer simulation
• Languages: English
• ISBNs: 9783527633340
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.