Combined structure- and ligand-based virtual screening aiding discovery of selenoglycolicamides as potential multitarget agents against Leishmania species

Abstract

Leishmaniasis is a neglected disease that does not have adequate treatment. We created a database with 30 selenoglycolicamides and evaluated their potential anti-Leishmanial activity (L. amazonensis and L. donovani) through ligand- and structure-based virtual screening. A diverse set selected from the ChEMBL databanks of 818 structures (L. donovani) and 722 structures (L. amazonensis), with tested anti-Leishmanial activity against promastigotes forms were classified according to pIC50 values to generate and validate a Random Forest model that shows higher statistical indices values. The structures of four different L. donovani enzymes were downloaded from the Protein Data Bank and the selenoglycolicamides' structures were submitted to molecular docking. In silico study allowed us to suggest that the selenoglycolicamides 18, 25, 27, 26, 6, 10 and 7 can be tested as potential multitarget molecules for leishmanial treatment, presenting activity probability against four strategic enzymes (Topoisomerase I, N-myristoyltransferase, cyclophilin and O-acetylserine sulfhydrylase). So, with the available materials and technical skills of our laboratories, we have synthesized and characterized 12 compounds to evaluate their anti-Leishmanial activity. The compounds 6, 7, 10, 12 and 13 tested presented pIC50 values greater than 5 for Leishmania amazonensis, being considered as active molecules, showing that our method was efficient in predicting both active and inactive molecules. In addition, selectivity index tests showed that our compounds are much more active against L. amazonensis cells than against peripheral blood mononuclear cells (PBMCs), with selectivity ranging from 23.4 to 114.5 times. In silico studies of the parameters of Lipinski's rule of five indicate that these compounds have the potential to be new drug candidates.