Open Access Databases and Datasets for Drug Discovery -

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Editeur : Wiley-Vch Gmbh

Langue : Anglais

Parution : 01/11/2023

Format : Moyen, de 350g à 1kg

Nombre de pages : 352.0

Expédition : 814

Dimensions : 24.8 x 17.3 x 2.2

ISBN : 9783527348398

Résumé :
Open Access Databases and Datasets for Drug Discovery

Timely resource discussing the future of data-driven drug discovery and the growing number of open-source databases

With an overview of 90 freely accessible databases and datasets on all aspects of drug design, development, and discovery, Open Access Databases and Datasets for Drug Discovery is a comprehensive guide to the vast amount of free data available to today's pharmaceutical researchers. The applicability of open-source data for drug discovery and development is analyzed, and their usefulness in comparison with commercially available tools is evaluated.

The most relevant databases for small molecules, drugs and druglike substances, ligand design, protein 3D structures (both experimental and calculated), and human drug targets are described in depth, including practical examples of how to access and work with the data. The first part is focused on databases for small molecules, followed by databases for macromolecular targets and diseases. The final part shows how to integrate various open-source tools into the academic and industrial drug discovery and development process.

Contributed to and edited by experts with long-time experience in the field, Open Access Databases and Datasets for Drug Discovery includes information on:

• An extensive listing of open access databases and datasets for computer-aided drug design
• PubChem as a chemical database for drug discovery, DrugBank Online, and bioisosteric replacement for drug discovery supported by the SwissBioisostere database
• The Protein Data Bank (PDB) and macromolecular structure data supporting computer-aided drug design, and the SWISS-MODEL repository of 3D protein structures and models
• PDB-REDO in computational aided drug design (CADD), and using Pharos/TCRD for discovering druggable targets

Unmatched in scope and thoroughly reviewing small and large open data sources relevant for rational drug design, Open Access Databases and Datasets for Drug Discovery is an essential reference for medicinal and pharmaceutical chemists, and any scientists involved in the drug discovery and drug development....

Biographie:

Antoine Daina is a Senior Scientist at the Molecular Modelling Group of the SIB Swiss Institute of Bioinformatics in charge of methodological developments in the SwissDrugDesign program.

Michael Przewosny has over 20 years of experience in pharmaceutical research and drug discovery, having worked as laboratory manager for different pharmaceutical companies.

Vincent Zoete is a Group Leader at the Molecular Modelling Group of the SIB Swiss Institute of Bioinformatics and an Associate Professor at the University of Lausanne, Department of Oncology UNIL-CHUV, Ludwig Institute for Cancer Research.

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Sommaire:

Series Editors Preface xiii

Raimund Mannhold - A Personal Obituary from the Series Editors xvii

A Personal Foreword xxi

1 Open Access Databases and Datasets for Computer-Aided Drug Design. A Short List Used in the Molecular Modelling Group of the SIB 1
Antoine Daina, Mar?a Jos? Ojeda-Montes, Maiia E. Bragina, Alessandro Cuozzo, Ute F. R?hrig, Marta A.S. Perez, and Vincent Zoete

References 30

Part I Small Molecules 39

2 PubChem: A Large-Scale Public Chemical Database for Drug Discovery 41
Sunghwan Kim and Evan E. Bolton

2.1 Introduction 41

2.2 Data Content and Organization 42

2.3 Tools and Services 45

2.3.1 PubChem Search 45

2.3.2 Summary Pages 48

2.3.3 Literature Knowledge Panel 49

2.3.4 2D and 3D Neighbors 50

2.3.5 Classification Browser 51

2.3.6 Identifier Exchange Service 52

2.3.7 Programmatic Access 52

2.3.8 PubChem FTP Site and PubChemRDF 53

2.4 Drug- and Lead-Likeness of PubChem Compounds 54

2.5 Bioactivity Data in PubChem 56

2.6 Comparison with Other Databases 57

2.7 Use of PubChem Data for Drug Discovery 58

2.8 Summary 59

Acknowledgments 60

References 60

3 DrugBank Online: A How-to Guide 67
Christen M. Klinger, Jordan Cox, Denise So, Teira Stauth, Michael Wilson, Alex Wilson, and Craig Knox

3.1 Introduction 67

3.2 DrugBank 68

3.2.1 Overview of DrugBank 68

3.2.2 DrugBank Datasets 69

3.2.2.1 Drug Cards: An Overview and Navigation Guide 70

3.2.2.2 Identification 70

3.2.2.3 Pharmacology 71

3.2.2.4 Categories 73

3.2.2.5 Properties 73

3.2.2.6 Targets, Enzymes, Carriers, and Transporters 73

3.2.2.7 References 77

3.3 Protocols 77

3.3.1 General Workflows 77

3.3.1.1 Using DrugBank Online's Search Functionality 77

3.3.1.2 Using DrugBank Online's Advanced Search Functionality 80

3.3.1.3 Browsing Drugs Using DrugBank Online's Drug Categories 83

3.3.2 Identifying Chemicals and Relevant Sequences 86

3.3.2.1 Searching Using Chemical Structure Search 86

3.3.2.2 Using Sequence Search to Find Similar Targets 89

3.3.3 Extracting DrugBank Datasets for ml 93

3.4 Research Using DrugBank 94

3.5 Discussion and Conclusions 95

References 96

4 Bioisosteric Replacement for Drug Discovery Supported by the SwissBioisostere Database 101
Antoine Daina, Alessandro Cuozzo, Marta A.S. Perez, and Vincent Zoete

4.1 Introduction 101

4.1.1 Concept of Isosterism and Bioisosterism 101

4.1.2 Classical vs. Non-classical Bioisostere and Further Molecular Replacements 102

4.1.3 Bioisosteric Replacement in Drug Discovery 105

4.2 Construction and Dissemination of SwissBioisostere 106

4.2.1 Intention and Requirements 106

4.2.2 Bioactivity Data 107

4.2.3 Nonsupervised Matched Molecular Pair Analysis 108

4.2.4 Database 108

4.2.5 Web Interface 109

4.3 Content of SwissBioisostere 111

4.3.1 Global Content 111

4.3.2 Biological and Chemical Contexts 112

4.3.3 Fragment Shape Diversity 113

4.4 Usage of SwissBioisostere 115

4.4.1 Website Usage 115

4.4.2 Most Frequent Requests 117

4.4.3 Examples Related to Drug Discovery 117

4.4.3.1 Use Cases 117

4.4.3.2 Replacing Unwanted Chemical Groups 118

4.4.3.3 Optimization of Passive Absorption and Blood-Brain Barrier Diffusion 122

4.4.3.4 Reduction of Flexibility 124

4.4.3.5 Reduction of Aromaticity/Escape from Flatland 128

4.5 Conclusive Remarks 133