Virtual screening of a cyclics imides to evaluate potential new multi-target agents against species of Leishmania

Leishmaniasis is a neglected disease that does not have adequate treatment. To try to solve this problem, we have tested a database with 33 cyclic imides and evaluated their potential anti-Leishmanial activity (L. donovani) through ligand-based and structure based virtual screening. A diverse set selected from CHEMBL databanks of 818 structures (L. donovani) with tested antileishmanial activity against promastigotes forms, were classified according pIC50 values in order to generate and validate Random Forest model that show higher statistical indices values. The structure of four different L. donovani enzymes were downloaded from PDB databank and imides structures were submitted to molecular docking. In silico study allowed us to suggest that the cyclic imide 5₂₇ can be tested as a potential multitarget molecule for leishmanial treatment, presenting activity against four strategic enzymes to treatment with probability of activity of 60%.