Quantitative Structure Activity Relationship (QSAR) in Drug Design – A Review

AbstractQuantitative Structure–Activity Relationship (QSAR) modeling has emerged as a pivotalcomputational approach in modern drug discovery, enabling the prediction of biologicalactivity based on molecular structure. By correlating physicochemical properties withpharmacological responses, QSAR significantly reduces the need for extensiveexperimental screening and accelerates lead optimization. This review presents acomprehensive overview of QSAR, including its theoretical foundations, descriptorsystems, model development strategies, validation techniques, and applications in drugdiscovery. Classical approaches such as Hansch and Free–Wilson analyses are discussedalongside contemporary machine learning-based QSAR models. The advantages,limitations, and future perspectives of QSAR in the era of artificial intelligence are alsohighlighted.