Open Access Databases and Datasets for Drug Discovery (PDF Book)

by Antoine Daina (Author)

Introduction:

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. This book discusses the future of data-driven drug discovery and its applicability in comparison with commercially available tools.

Analysis:
The book gives an overview of 90 freely accessible databases and datasets on all aspects of drug design, development, and discovery. It describes the most relevant databases for small molecules, drugs and druglike substances, ligand design, protein 3D structures (both experimental and calculated), and human drug targets in detail. The final part of the book shows how to integrate various open-source tools into the academic and industrial drug discovery and development process.

Key Features:

The most significant features of this book include an extensive listing of open access databases and datasets for computer-aided drug design, analysis of the applicability of open-source data for drug discovery and development, and practical examples of accessing and working with the data.

Target Audience:

The target audience for this book includes medicinal and pharmaceutical chemists and any scientists involved in drug discovery and development. It is an excellent resource for those who want to learn about open-source data and its usefulness in comparison with commercially available tools.

Conclusion:

In conclusion, Open Access Databases and Datasets for Drug Discovery is an essential reference that can help researchers access the vast amount of free data available for drug discovery. This comprehensive guide provides detailed information on databases for small molecules, macromolecular targets, and diseases, and how to integrate various open-source tools into the drug discovery process.

Rating and Review:

Overall, this book is an excellent resource for anyone involved in drug discovery and development. The practical examples and in-depth analysis of open-source data make it a valuable addition to any researcher’s library. Therefore, I would rate this book 5 out of 5 stars.