Computer Aided Drug Design

Computer-Aided Drug Design (CADD) has emerged as a transformative approach in pharmaceutical research, integrating computational tools and molecular modeling techniques to accelerate and optimize the drug discovery process. This review provides a comprehensive overview of the fundamental principles, methodologies, and applications of CADD, including structure-based and ligand-based drug design, molecular docking, pharmacophore modeling, and virtual screening. Advances in bioinformatics, artificial intelligence, and high- performance computing have significantly enhanced the accuracy and efficiency of CADD, enabling the identification of novel therapeutic candidates with improved specificity and reduced development costs. Key case studies illustrating successful drug discoveries aided by CADD are discussed, highlighting its growing impact in both academia and industry. The review also addresses current challenges, such as the limitations of predictive models and the need for better integration with experimental data, while exploring future directions for innovation in this rapidly evolving field.