Drug discovery is no longer driven by chance-it is engineered through data, molecular insight, and predictive precision. As disease biology grows more complex, rational, mechanism-based design has become central to modern pharmaceutical science.
Molecules to Medicines: The Computational Logic of Modern Drug Discovery presents a structured exploration of Computer-Aided Drug Design (CADD), integrating molecular modeling, QSAR, pharmacophore mapping, docking, and ADME prediction into a unified framework. Rather than treating these as isolated tools, the text shows how each method supports molecular understanding and therapeutic innovation
.Designed for postgraduate pharmacy students, researchers, and early-career scientists, the book emphasizes conceptual clarity and examination readiness, enabling precise academic answers and practical insight into real-world drug development workflows.What distinguishes this work is its mechanistic depth-each concept is grounded in physicochemical principles and translated into pharmaceutical relevance, bridging computational abstraction and biological reality. The narrative aligns with current challenges in drug discovery, including target validation, translational failure, and predictive limitations.As pharmaceutical research becomes increasingly data-driven, this book provides a clear pathway to understand how molecules evolve into medicines, shaping the future of therapeutic innovation.