RESUMO
The World Health Organization classifies Leishmania as one of the 17 "neglected diseases" that burden tropical and sub-tropical climate regions with over half a million diagnosed cases each year. Despite this, currently available anti-leishmania drugs have high toxicity and the potential to be made obsolete by parasite drug resistance. We chose to analyze organoselenides for leishmanicidal potential given the reduced toxicity inherent to selenium and the displayed biological activity of organoselenides against Leishmania. Thus, the biological activities of 77 selenoesters and their N-aryl-propanamide derivatives were predicted using robust in silico models of Leishmania infantum, Leishmania amazonensis, Leishmania major, and Leishmania (Viannia) braziliensis. The models identified 28 compounds with >60% probability of demonstrating leishmanicidal activity against L. infantum, and likewise, 26 for L. amazonesis, 25 for L. braziliensis, and 23 for L. major. The in silico prediction of ADMET properties suggests high rates of oral absorption and good bioavailability for these compounds. In the in silico toxicity evaluation, only seven compounds showed signs of toxicity in up to one or two parameters. The methodology was corroborated with the ensuing experimental validation, which evaluated the inhibition of the Promastigote form of the Leishmania species under study. The activity of the molecules was determined by the IC50 value (µM); IC50 values < 20 µM indicated better inhibition profiles. Sixteen compounds were synthesized and tested for their activity. Eight molecules presented IC50 values < 20 µM for at least one of the Leishmania species under study, with compound NC34 presenting the strongest parasite inhibition profile. Furthermore, the methodology used was effective, as many of the compounds with the highest probability of activity were confirmed by the in vitro tests performed.
RESUMO
BACKGROUND: Chemoinformatics has several applications in the field of drug design, helping to identify new compounds against a range of ailments. Among these are Leishmaniasis, effective treatments for which are currently limited. OBJECTIVE: To construct new indole 2-aminothiophene molecules using computational tools and to test their effectiveness against Leishmania amazonensis (sp.). METHODS: Based on the chemical structure of thiophene-indol hybrids, we built regression models and performed molecular docking, and used these data as bases for design of 92 new molecules with predicted pIC50 and molecular docking. Among these, six compounds were selected for the synthesis and to perform biological assays (leishmanicidal activity and cytotoxicity). RESULTS: The prediction models and docking allowed inference of characteristics that could have positive influences on the leishmanicidal activity of the planned compounds. Six compounds were synthesized, one-third of which showed promising antileishmanial activities, with IC50 ranging from 2.16 and 2.97 µM (against promastigote forms) and 0.9 and 1.71 µM (against amastigote forms), with selectivity indexes (SI) of 52 and 75. CONCLUSION: These results demonstrate the ability of Quantitative Structure-Activity Relationship (QSAR)-based rational drug design to predict molecules with promising leishmanicidal potential, and confirming the potential of thiophene-indole hybrids as potential new leishmanial agents.