Artificial Intelligence-Driven Drug Discovery - Principles, Methods, and Applications

This book provides a comprehensive overview of how cutting-edge artificial intelligence technologies are transforming modern drug design. It examines the impact of deep learning, generative modeling, and advanced protein language models across the full spectrum of therapeutic development, from small molecules discovery to peptide engineering and antibody design. Building on breakthroughs such as AlphaFold, the chapters illustrate how AI enables accelerated virtual screening, efficient ADMET prediction, and de novo molecular generation with improved specificity and affinity. In addition to introducing the core machine learning concepts underpinning these advances, the book highlights real world applications and emerging strategies that are reshaping the future of pharmaceutical innovation. It serves as an essential reference for graduate students, researchers and practitioners seeking to understand and leverage AI-driven methodologies in drug discovery.