Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development

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Kunal Roy (Professor, Drug Theoretics and Cheminformatics Lab, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India)

Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development

Kunal Roy (Professor, Drug Theoretics and Cheminformatics Lab, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India)

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English

Academic Press Inc
25 May 2023

Pre-clinical medicine: basic sciences; Pharmacology; Chemistry; Pharmaceutical technology; Machine learning

Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development aims at showcasing different structure-based, ligand-based, and machine learning tools currently used in drug design. It also highlights special topics of computational drug design together with the available tools and databases. The integrated presentation of chemometrics, cheminformatics, and machine learning methods under is one of the strengths of the book. The first part of the content is devoted to establishing the foundations of the area. Here recent trends in computational modeling of drugs are presented. Other topics present in this part include QSAR in medicinal chemistry, structure-based methods, chemoinformatics and chemometric approaches, and machine learning methods in drug design. The second part focuses on methods and case studies including molecular descriptors, molecular similarity, structure-based based screening, homology modeling in protein structure predictions, molecular docking, stability of drug receptor interactions, deep learning and support vector machine in drug design. The third part of the book is dedicated to special topics, including dedicated chapters on topics ranging from de design of green pharmaceuticals to computational toxicology. The final part is dedicated to present the available tools and databases, including QSAR databases, free tools and databases in ligand and structure-based drug design, and machine learning resources for drug design. The final chapters discuss different web servers used for identification of various drug candidates.

Edited by: Kunal Roy (Professor Drug Theoretics and Cheminformatics Lab Department of Pharmaceutical Technology Jadavpur University Kolkata India)
Imprint: Academic Press Inc
Country of Publication: United States
Dimensions: Height: 235mm, Width: 191mm,
Weight: 1.590kg
ISBN: 9780443186387
ISBN 10: 0443186383
Pages: 768
Publication Date: 25 May 2023
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

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.