 Computer-aided drug discovery, CADD, tools have become an effective and indispensable tool in therapeutic development by expediting the challenging, time-consuming and expensive process of drug discovery and development, potentially reducing research and development costs. The Human Genome Project has made available substantial sequence data for various drug discovery projects, while increasing knowledge of biological structures and computer power have enabled computational methods to be used effectively in different phases of the drug discovery pipeline. This review highlights recent successes in virtual high-throughput screening, protein structure prediction methods, protein ligand docking, pharmacophore modeling, and QSAR techniques, both in structure-based and ligand-based drug discovery methods. This article was authored by Sumadu P. Lillinanda and Stefan Lindert.