Computational Biology in Drug Discovery and Repurposing

Rajani Sharma, A. V. Senthil Kumar, Kunal Kumar, Rajani Sharma, A. V. Senthil Kumar, Kunal Kumar

• Publisher: Apple Academic Press
• Year: 2024
• Print ISBN: 9781774915561
• eBook ISBN: 9781000988727
• Edition: 1
• Topic: Technology & Engineering
• Subtopic: Biotechnology
• Index: Technology & Engineering

This new book takes an in-depth look at the emerging and prospective field of computational biology and bioinformatics, which possesses the ability to analyze large accumulated biological data collected from sequence analysis of proteins and genes and cell population with an aim to make new predictions pertaining to drug discovery and new biology. The book explains the basic methodology associated with a bioinformatics and computational approach in drug designing. It then goes on to cover the implementation of computational programming, bioinformatics, pharmacophore modeling, biotechnological techniques, and pharmaceutical chemistry in designing drugs. The major advantage of intervention of computer language or programming is to cut down the number of steps and costs in the field of drug designing, reducing the repeating steps and saving time in screening the potent component for drug or vaccine designing.

The book describes algorithms used for drug designing and the use of machine learning and AI in drug delivery and disease diagnosis, which are valuable in clinical decision-making. The implementation of robotics in different diseases like stroke, cancer, COVID-19, etc. is also addressed. Topics include machine learning, AI, databases in drug design, molecular docking, bioinformatics tools, target-based drug design, and immunoinformatics, chemoinformatics, and nanoinformatics in drug design. Drug repurposing in drug design in general as well as for specific diseases, including cancer, Alzheimer's disease, tuberculosis, COVID-19, etc., is also addressed in depth.

Table of contents

• Cover Page
• Half Title Page
• Title Page
• Copyright Page
• About the Editors
• Contents
• Contributors
• Abbreviations
• Preface
• Introduction
• Chapter 1 Machine Learning for Drug Designing
• Chapter 2 Intervention of Artificial Intelligence in Disease Diagnosis
• Chapter 3 Bioinformatics for Determining the Active Site of a Target Proteins
• Chapter 4 Molecular Docking: A Pertinent Computational Tool in Modern Drug Designing and Discovery
• Chapter 5 Bioinformatics Tools to Study Homology Modeling
• Chapter 6 Target-Based Drug Designing
• Chapter 7 Immunoinformatics in Drug Designing
• Chapter 8 Chemoinformatics in Drug Designing
• Chapter 9 Drug Repurposing as an Emerging Field in Drug Designing
• Chapter 10 Databases in Drug Design
• Chapter 11 Computational Approach for Drug Repurposing
• Chapter 12 De Novo Drug Design Using Computational Tools: Inhibition of CoaBC for Tuberculosis Treatment as a Case Study
• Chapter 13 Role of Artificial Intelligence in Retrosynthesis Analysis of Natural Products for Drug Design
• Chapter 14 Drug Repurposing in Quest for Newer Therapeutic Options Against Cancer
• Chapter 15 Computational Approaches to Discover Novel Phytochemical Inhibitors Against Novel Coronavirus (Sars-CoV-2)
• Chapter 16 Insights into Computational Repurposing of Drugs for Alzheimer's Disease
• Chapter 17 Drug Design and Discovery
• Chapter 18 Sodium-Proton Transporter Proteins: Clinical Significance as a Potential Drug Target
• Chapter 19 Nanoinformatics and its Role in Drug Designing and Discovery
• Chapter 20 In Silico Homology Modeling to Identify the Anti-Inflammatory Proteins from Raphanus sativus and Brassica oleracea
• Index