Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment

by Kunal Roy, Supratik Kar, Rudra Narayan Das

Overview

Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment describes the historical evolution of quantitative structure-activity relationship (QSAR) approaches and their fundamental principles. This book includes clear, introductory coverage of the statistical methods applied in QSAR and new QSAR techniques, such as HQSAR and G-QSAR. Containing real-world examples that illustrate important methodologies, this book identifies QSAR as a valuable tool for many different applications, including drug discovery, predictive toxicology and risk assessment. Written in a straightforward and engaging manner, this is the ideal resource for all those looking for general and practical knowledge of QSAR methods.

• Includes numerous practical examples related to QSAR methods and applications
• Follows the Organization for Economic Co-operation and Development principles for QSAR model development
• Discusses related techniques such as structure-based design and the combination of structure- and ligand-based design tools

Product Details

ISBN-13:	9780128016336
Publisher:	Elsevier Science
Publication date:	03/03/2015
Sold by:	Barnes & Noble
Format:	eBook
Pages:	484
File size:	24 MB
Note:	This product may take a few minutes to download.

About the Author

Dr. Kunal Roy is a Professor and Ex-Head in the Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India. He has been a recipient of Commonwealth Academic Staff Fellowship (University of Manchester, 2007) and Marie Curie International Incoming Fellowship (University of Manchester, 2013). The field of his research interest is QSAR and Molecular Modeling with application in Drug Design and Ecotoxicological Modeling. Dr. Roy has published more than 350 research articles in refereed journals (current SCOPUS h index 49). He has also coauthored two QSAR-related books, edited six QSAR books and published more than ten book chapters. Dr. Roy is a Co-Editor-in-Chief of Molecular Diversity (Springer Nature). He also serves as a member of the Editorial Boards of several International Journals.

Table of Contents

Chapter 1: Background of QSAR and Historical developmentsChapter 2: Chemical information and DescriptorsChapter 3: Classical QSARChapter 4: Topological QSARChapter 5: Computational chemistryChapter 6: Selected Statistical methods in QSARChapter 7: Validation of QSAR modelsChapter 8: Introduction to 3D-QSARChapter 9: Newer QSAR techniquesChapter 10: Other related techniquesChapter 11: Future avenues

What People are Saying About This

From the Publisher

An introductory book that provides instruction on the basic tools of QSAR and incorporates practical examples relating to the pharmaceutical sciences

Editorial Reviews

"... a handy reference for beginners in this field. Score: 62 - 2 Stars" —Doody's

From the Publisher

Reviewer: Rahmat M. Talukder, PhD, RPh (The University of Texas at Tyler)
Description: This book presents the basic concepts in quantitative structure-activity relationships (QSAR). It briefly discusses various QSAR techniques, based on the concept of molecular substructure, and provides a brief history of QSAR along with an overview of recent developments in QSAR methodologies.
Purpose: As computing technology becoming more powerful, the application of QSAR methodologies is growing in various fields, including medicinal chemistry, pharmacology, toxicology, and material sciences. Thus a book on basic aspects of QSAR is useful.
Audience: The authors seem to target beginners to QSAR. This book is expected to serve as a reference for anyone who wants to learn the basics of QSAR.
Features: For readers new to this field, the book introduces the concept of descriptors. Then it succinctly presents computation chemistry and related concepts, a few relevant statistical/mathematical methods with an emphasis on linear and nonlinear model development, and validation tools used in QSAR. A separate chapter briefly describes a few newer techniques, such as H-QSAR, G-QSAR, LQTA-QSAR, etc. An interesting chapter presents a few examples of approved and investigational drugs that have been developed based on QSAR principles. Readers will find this chapter valuable. There is a short chapter on future directions and applications of QSAR, but it could have been expanded. It would have been helpful to include a chapter on the application of QSAR to absorption, distribution, metabolism, and excretion (ADME) and another on the role of QSAR in regulatory assessment of pharmaceuticals.
Assessment: QSAR is a useful tool for predicting relationships between the effects of a molecule and its analogues with their structural properties. As computing power increases, the application of QSAR principles is expanding. There are a number of books related to this topic, but they are at a relatively advanced level. Thus, the coverage of the fundamental aspects of QSAR makes this book a handy reference for beginners in this field. This book has considerable overlap with another book by the same authors from the same publisher, A Primer on QSAR/QSPR Modeling, Roy et al. (Springer, 2015). It would have been more practical if the two books were merged into one.

Doody's Review Service