Computer-aided drug discovery (CADD) tools have provided an effective way in the drug
discovery pipeline for expediting of this long process and economizing the cost of research and development.
Due to the dramatic increase in the availability of human proteins as drug targets and small
molecule information due to the advances in bioinformatics, cheminformatics, genomics, proteomics,
and structural information, the applicability of in silico drug discovery has been extended. Computational
approaches have been used at almost all stages in the drug discovery pipeline including target
identification and validation, lead discovery and optimization, and pharmacokinetic and toxicity profiles
prediction. As each area covers a variety of computational methods, it is unmanageable to assess comprehensively
all areas of CADD applications or every aspect of an area in one review article. However,
in this article, we tried to present an overview of computational methods used in almost all the areas
concerned with drug design and highlight some of the recent successes.
Keywords: Target identification, Lead discovery and optimization, Virtual screening, Virtual docking, QSAR, Pharmacophore
mapping, In silico ADMET/PBPK prediction.
Rights & PermissionsPrintExport