Structure-based drug design is a computational technique used in drug discovery to design and optimize the chemical structure of a drug based on the structure of its biological target. This approach involves the identification of a potential ligand binding site on the target molecule, obtaining accurate structural information, and using computer algorithms to dock massive databases of small molecules or fragments of compounds into the binding cavity. The ranked list of ligands is then evaluated and top-scoring molecules are tested in vitro in biochemical assays. The process of SBDD is iterative and fits nicely within the context of a larger drug discovery programme. SBDD has identified numerous drugs, including HIV-1-inhibiting FDA-approved drugs, a selective antiviral for influenza, and protease inhibitors for the treatment of hepatitis C. The use of artificial intelligence and machine learning has further sped up lead identification, evaluation, and big-data handling.