Computational Drug Design and Molecular Modelling

Computational Drug Design and Molecular Modelling by Uddipta Das is a comprehensive, authoritative, and forward-thinking guide covering the entire landscape of modern in silico drug discovery. Designed for students, researchers, industry scientists, and healthcare innovators, this book provides a seamless journey from foundational molecular modelling principles to cutting-edge AI-driven, quantum-enhanced drug design.
Spanning 40 meticulously structured chapters, the book integrates classical computational chemistry, protein modelling, docking, pharmacophore analysis, QSAR, machine learning, deep learning, ADMET prediction, molecular dynamics simulations, free-energy methods, PROTAC design, biologics modelling, membrane interactions, systems pharmacology, and computational toxicology. It also dives into transformative areas such as quantum computing, digital twins, big data pipelines, autonomous laboratories, and AI-native discovery ecosystems that are redefining the future of drug development.
This book emphasizes practical workflows, real-world applications, algorithmic insights, hands-on strategies, and advanced techniques used across academia and the pharmaceutical industry. Whether predicting molecular properties, designing small molecules, engineering proteins, modelling PROTAC ternary complexes, or exploring multi-target drug design, readers will gain both conceptual understanding and computational confidence.
With its deep scientific rigor, clarity of explanation, and visionary outlook, Computational Drug Design and Molecular Modelling stands as an essential resource for aspiring medicinal chemists, computational chemists, biotechnologists, pharmacists, and interdisciplinary scientists ready to embrace the rapidly evolving world of digital and AI-driven drug discovery.