This book presents the fundamental principles, contemporary methodologies, and practical applications that define modern computer-aided drug design. It explores the integration of Cryo-EM structures, AlphaFold predictions, and homology modeling to expand structural insight into biologically relevant targets. In addition, it covers molecular docking, molecular dynamics simulations, enhanced sampling approaches, and free energy calculations for robust hit-to-lead refinement. The book further examines in silico ADMET prediction, quantitative structure–activity relationships, machine learning–based modeling, and network pharmacology frameworks applied across therapeutic areas including oncology, infectious diseases, neurodegenerative disorders, and metabolic and cardiovascular conditions.
Key Features:
- Explores foundational and advanced CADD techniques, including molecular docking, molecular dynamics simulations, in silico ADMET prediction, and network pharmacology
- Integrates Cryo-EM, AlphaFold, and homology modeling to enhance structure-based drug discovery
- Details machine learning applications for pharmacokinetic profiling, toxicity prediction, and lead prioritization
- Discusses computational workflows to multi-target drug design across major therapeutic domains
- Presents systems biology perspectives and translational case examples linking computational discovery to experimental validation
This book is intended for researchers and students in pharmaceutical sciences, computational biology, bioinformatics, and related disciplines.
Table of Contents:
Chapter 1: Molecular Dynamics Simulations in Drug Discovery: Integration with Artificial Intelligence and Future Viewpoints. Chapter 2: In-Silico ADMT Prediction. Chapter 3: Multi-Target and Polypharmacology-Oriented Drug Design. Chapter 4: Computational Strategies for Cancer Drug Discovery. Chapter 5: Structure-based approaches for infectious disease therapeutics. Chapter 6: In Silico Drug Design for Metabolic and Cardiovascular Diseases. Chapter 7: Computational Design for Neurodegenerative Disease Targets.
About the Author :
Mohammad Kalim Ahmad Khan is a Professor of Bioengineering and Course Coordinator for M.Tech (Bioinformatics) and B.Tech (Biotechnology) at Integral University, Lucknow. An MSc alumnus of the same institution, he has cultivated more than sixteen years of expertise in computer-aided drug design, high-throughput virtual screening, ADMET profiling, and molecular-dynamics simulations. Dr. Khan has authored 82 peer-reviewed papers, two research monographs, and three book chapters, and is an invited reviewer for over thirty international journals. His laboratory focuses on structure-based inhibitor design for breast-cancer targets, emerging tuberculosis enzymes, and chemokine-mediated vitiligo pathways. In recognition of his scholarly contributions, he received the 2022 International Eminent Award in Engineering, Science, and Medicine. Within the university he leads NAAC quality-assurance initiatives, manages the Post-graduate Computational Biology Laboratory, and serves on the Board of Studies, Faculty Board, and Academic Council. Dr. Khan is a member of IAENG, IACSIT, and ISRD.
Mohammed Tarique is working in the Center for Interdisciplinary Research in Basic Sciences (CIRBSc), Jamia Millia Islamia, India. Holding a Ph.D. in Plasmodium Biology from the International Centre for Genetic Engineering and Biotechnology, New Delhi, India, his research focuses on understanding the biology of Plasmodium towards the development of novel drugs. He has published more than 40 research articles in peer-reviewed international journals. Currently serves on the editorial boards of numerous journals, and has published several books with international publishers.
