Book

Description

Antimicrobial Drug Discovery: In-Silico Design and Evaluation of Phenolic Acids as DHFR Inhibitors presents a timely and transformative exploration of how artificial intelligence is reshaping the fight against antimicrobial resistance. Bridging classical pharmaceutical science with cutting-edge computational innovation, this book provides an integrated, multidisciplinary perspective on target-based drug discovery, with a special focus on dihydrofolate reductase (DHFR) inhibition and the therapeutic potential of phenolic acids. Beginning with the global burden of infectious diseases and the historical evolution of antimicrobials, the book establishes the urgency of discovering new, selective, and safe drug candidates. It then delves into the biochemical and structural significance of DHFR as a validated therapeutic target across microbial and oncological diseases. Readers are introduced to the rich diversity, biosynthesis, pharmacology, and medicinal relevance of phenolic acids, natural compounds with promising antimicrobial, antioxidant, anticancer, and metabolic activitie. A comprehensive overview of modern in-silico drug design methodologies, including molecular docking, virtual screening, MM/GBSA analysis, and ADME profiling, guides readers through the computational backbone of contemporary drug discovery workflows. Building upon these foundations, the book presents AI-enabled screening and docking studies of phenolic acids against DHFR, combining theoretical insights with practical in vitro validations to highlight new lead molecules with therapeutic potential. The concluding chapter offers forward-looking perspectives on AI’s expanding role in antimicrobial discovery from generative chemistry and deep-learning-based scoring to predictive resistance modeling charting a progressive roadmap for next-generation DHFR inhibitors and beyond. This book serves as an essential resource for researchers, academicians, and students in pharmaceutical sciences, medicinal chemistry, biotechnology, and computational drug design, offering a compelling blend of scientific depth, methodological clarity, and visionary outlook.