Unlock the Power of Cheminformatics, QSAR, and Machine Learning in Novel Drug Development

Written by renowned author Kunal Roy, this comprehensive guide delves into the world of structure-based, ligand-based, and machine learning tools used in drug design. The book provides an integrated presentation of chemometrics, cheminformatics, and machine learning methods, highlighting their applications in novel drug development.

Laying the Foundations

The first part of the book sets the stage by introducing recent trends in computational modeling of drugs. It covers essential topics such as:

• QSAR in medicinal chemistry
• Structure-based methods
• Chemoinformatics and chemometric approaches
• Machine learning methods in drug design

Methods and Case Studies

The second part of the book delves deeper into the world of methods and case studies, featuring:

• Molecular descriptors
• Molecular similarity
• Structure-based screening
• Homology modeling in protein structure predictions
• Molecular docking
• Stability of drug receptor interactions
• Deep learning and support vector machine in drug design

Special Topics in Computational Drug Design

The third part of the book is dedicated to special topics, including:

• Design of green pharmaceuticals
• Computational toxicology

Tools and Databases

The final part of the book provides an exhaustive list of available tools and databases, including:

• QSAR databases
• Free tools and databases in ligand and structure-based drug design
• Machine learning resources for drug design

The book concludes with a discussion on different web servers used for identifying drug candidates, making it a valuable resource for researchers, scientists, and students in the field of pharmaceuticals and drug development.

Product Details:

• Publisher: Elsevier Science
• Publication Date: May 23, 2023
• Language: English
• ISBN: 9780443186387, 9780443186394

This comprehensive guide is a must-have for anyone looking to stay ahead in the field of novel drug development. With its integrated approach and comprehensive coverage of cheminformatics, QSAR, and machine learning, it’s an invaluable resource for researchers, scientists, and students alike.