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Background: Staphylococcus aureus is a gram-positive spherical bacterium commonly present in nasal fossae and in the skin of healthy people; however, in high quantities, it can lead to complications that compromise health. The pathologies involved include simple infections, such as folliculitis, acne, and delay in the process of wound healing, as well as serious infections in the CNS, meninges, lung, heart, and other areas., Aim: This research aims to propose a series of molecules derived from 2-naphthoic acid as a bioactive in the fight against S. aureus bacteria through in silico studies using molecular modeling tools., Methods: A virtual screening of analogues was done in consideration of the results that showed activity according to the prediction model performed in the KNIME Analytics Platform 3.6, violations of the Lipinski rule, absorption rate, cytotoxicity risks, energy of binder-receptor interaction through molecular docking, and the stability of the best profile ligands in the active site of the proteins used (PDB ID 4DXD and 4WVG)., Results: Seven of the 48 analogues analyzed showed promising results for bactericidal action against S. aureus., Conclusion: It is possible to conclude that ten of the 48 compounds derived from 2-naphthoic acid presented activity based on the prediction model generated, of which seven presented no toxicity and up to one violation to the Lipinski rule., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

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., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background: Hepatitis C is a disease that constitutes a serious global health problem, is often asymptomatic and difficult to diagnose and about 60-80% of infected patients develop chronic diseases over time. As there is no vaccine against hepatitis C virus (HCV), developing new cheap treatments is a big challenge., Objective: The search for new drugs from natural products has been outstanding in recent years. The aim of this study was to combine structure-based and ligand-based virtual screening (VS) techniques to select potentially active molecules against four HCV target proteins from in-house secondary metabolite dataset (SistematX)., Materials and Methods: From the ChEMBL database, we selected four sets of 1199, 355, 290 and 237chemical structures with inhibitory activity against different targets of HCV to create random forest models with an accuracy value higher than 82% for cross-validation and test sets. Afterward, a ligandbased virtual screen of the entire 1848 secondary metabolites database stored in SistematX was performed. In addition, a structure-based virtual screening was also performed for the same set of secondary metabolites using molecular docking., Results: Finally, using consensus analyses approach combining ligand-based and structure-based VS, three alkaloids were selected as potential anti-HCV compounds., Conclusion: The selected structures are a starting point for further studies in order to develop new anti- HCV compounds based on natural products., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)