Quantitative Structure-Activity Relationships in Drug Design, Predictive Toxicology, and Risk Assessment

Quantitative Structure-Activity Relationships in Drug Design, Predictive Toxicology, and Risk Assessment

Kunal Roy (Jadavpur University, India)
Release Date: February, 2015|Copyright: © 2015 |Pages: 703
ISBN13: 9781466681361|ISBN10: 1466681365|EISBN13: 9781466681378|DOI: 10.4018/978-1-4666-8136-1

Description

Quantitative structure-activity relationships (QSARs) represent predictive models derived from the application of statistical tools correlating biological activity or other properties of chemicals with descriptors representative of molecular structure and/or property.

Quantitative Structure-Activity Relationships in Drug Design, Predictive Toxicology, and Risk Assessment discusses recent advancements in the field of QSARs with special reference to their application in drug development, predictive toxicology, and chemical risk analysis. Focusing on emerging research in the field, this book is an ideal reference source for industry professionals, students, and academicians in the fields of medicinal chemistry and toxicology.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • CORAL for QSAR/QSPR Studies
  • Environmental Exposure Assessment
  • Lead Optimization of Potential Drug Candidates
  • Novel Descriptors in QSAR
  • QSAR for Antioxidants
  • Toxicity of Nanomaterials

Reviews and Testimonials

Chemistry, pharmaceutical technology, and other researchers from around the world present 15 chapters detailing recent advancements in quantitative structure-activity relationships (QSAR) and their application to drug development, predictive toxicology, and chemical risk analysis. They discuss QSAR principles and tools; novel descriptors, including extended topochemical atom indices and their application to quantitative structure-activity/property/toxicity studies, multivariate image analysis descriptors for QSAR as applied to trypanosomiasis, and conceptual density functional theory-based descriptors; the role of applicability domain of QSAR models; and more.

– ProtoView Book Abstracts (formerly Book News, Inc.)

This is a unique resource for professionals interested in the QSAR field. It includes exceptional discussions of topics related to drug design, predictive toxicology, risk assessment, antioxidants, nanomaterials, and it is an important resource on QSAR studies using CORAL software. It provides a unique perspective on the future of this field.

– Hemantkumar Chavan, Ph.D., University of Kansas Medical Center, Doody’s Review Service

Table of Contents and List of Contributors

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Author(s)/Editor(s) Biography

Kunal Roy is an Associate Professor in the Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India, and Fellow in the Manchester Institute of Biotechnology, University of Manchester, United Kingdom. He is an Associate Editor of the Springer journal, Molecular Diversity, and a member of the Editorial Advisory Board of European Journal of Medicinal Chemistry (Elsevier). The field of his research interest is QSAR and Molecular Modeling. Dr. Roy has published more than 200 research papers in refereed journals.

Indices