Modern drug discovery has undergone a profound transformation with the emergence of computational methodologies. This chapter provides an overview of computational drug discovery, a dynamic and interdisciplinary approach that harnesses the power of computers and advanced algorithms to expedite development of potential therapeutic compounds. Integration of techniques like ML and AI has streamlined early drug development stages. Leveraging bioinformatics, chemoinformatics, molecular docking, MD simulations, and quantum computing to analyze vast datasets, detect patterns, and predicting biological activities with precision has surpassed traditional methods, reducing time and cost associated with drug development. to maximizeitates personalized medicine by considering individual genetic variations and disease profiles, tailoring treatments to specific patient populations for maximized therapeutic outcomes. However, the field is not without its challenges, including issues related to data quality, model accuracy, and overall complexity of biological systems.