Bioinformatics, Computational Chemistry and AI in Drug Innovation

This book comprehensively examines the applications of bioinformatics, computational chemistry and artificial intelligence in the field of drug discovery and innovation. It provides foundational insights into bioinformatics and its applications, from cutting-edge advancements in computational molecular phylogeny, structural bioinformatics, and metabolic computing to biological databases and data mining. Additionally, the book covers critical aspects of data storage, retrieval, database structure, and annotation, providing a robust foundation for understanding the complexities of biological data management. It discusses computational protein modeling, molecular docking, pharmacophore modeling, quantitative structure-activity relationships, and innovative approaches for drug target identification. The chapters explore protein-ligand interactions, molecular dynamics simulations, density function theory, and the strategic endeavor of drug repurposing. Towards the end, the book discusses Quality by Design (QbD) in drug formulation, artificial intelligence, and machine learning's transformative influence on drug discovery, computational tools for estimating pharmacokinetic parameters, and the conceptual underpinnings of computational genomics. This book will is useful for students, professionals and researchers in the fields of pharmaceutical Sciences, life sciences, pharmaceuticals, biotechnology and computational biology. Key feature · Discuses applications of bioinformatics, computational chemistry, and artificial intelligence in drug discovery and innovation · Covers essential aspects of data storage, retrieval, database structure, and annotation for managing complex biological data. · Reviews molecular docking, pharmacophore modeling, and quantitative structure-activity relationships for drug designing. · Explores the transformative influence of artificial intelligence and machine learning in drug discovery. · Emphasizes Quality by Design (QbD) principles, highlighting the importance of precision and quality in drug formulation design.