Current treatment of leishmaniasis is based on chemotherapy, which relies on a handful of drugs with serious limitations, such as high cost, toxicity, and lack of efficacy in endemic regions. Therefore, development of new, effective, and affordable anti-leishmanial drugs is a global health priority. Dipeptidylcarboxypeptidase has been characterized and established as a drug target for antileishmanial drug discovery. We virtually screened a large chemical library of 15 452 compounds against a 3D model of dipeptidylcarboxypeptidase to identify novel inhibitors. The initial virtual screening using a ligand-based pharmacophore model identified 103 compounds. Forty-six compounds were shortlisted based on the docking scores and other scoring functions. Further, these compounds were subjected to biological assay, and four of them belonging to two chemical classes were identified as the lead compounds. Identification of these novel and chemically diverse inhibitors should provide leads to be optimized into candidates to treat these protozoan infections.
© 2011 John Wiley & Sons A/S.