Tuberculosis (TB) is an infection caused by Mycobacterium tuberculosis, responsible for 1.5 million documented deaths in 2016. The increase in reported cases of M. tuberculosis resistance to the main drugs show the need for the development of new and efficient drugs for better TB control. Based on these facts, this work aimed to use combined in silico techniques for the discovery of potential inhibitors to β-ketoacyl-ACP synthase (MtKasA). Initially compounds from natural sources present in the ZINC database were selected, then filters were sequentially applied by virtual screening, initially with pharmacophoric modeling, and later the selected compounds (based on QFIT scores) were submitted to the DOCK 6.5 program. After recategorization of the variables (QFIT score and GRID score), compounds ZINC35465970 and ZINC31170017 were selected. These compounds showed great hydrophobic contributions and for each established system 100 ns of molecular dynamics simulations were performed and the binding free energy was calculated. ZINC35465970 demonstrated a greater capacity for the KasA enzyme inhibition, with a ΔGbind = −30.90 kcal/mol and ZINC31170017 presented a ΔGbind = −27.49 kcal/mol. These data can be used in other studies that aim at the inhibition of the same biological targets through drugs with a dual action.

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Leishmaniasis is caused by several protozoa species belonging to genus Leishmania that are hosted by humans and other mammals. Millions of new cases are recorded every year and the drugs available on the market do not show satisfactory efficacy and safety. A hierarchical virtual screening approach based on the pharmacophore model, molecular docking, and molecular dynamics was conducted to identify possible Leishmania braziliensis N-misristoyltransferase (LbNMT) inhibitors. The adopted pharmacophore model had three main features: four hydrophobic centers, four hydrogen-bond acceptor atoms, and one positive nitrogen center. The molecules (n=15,000) were submitted to alignment with the pharmacophore model and only 27 molecules aligned to model. Six molecules were submitted to molecular docking, using receptor PDB ID 5A27. After docking, the ZINC35426134 was a top-ranked molecule (- 64.61 kcal/mol). The molecule ZINC35426134 shows hydrophobic interactions with Phe82, Tyr209, Val370, and Leu391 and hydrogen bonds with Asn159, Tyr318, and Val370. Molecular dynamics simulations were performed with the protein in its APO and HOLO forms for 37 ns in order to assess the stability of the protein-ligand complex. Results showed that the HOLO form was more stable than the APO one, and it suggests that the ZINC35426134 binding stabilizes the enzyme. Therefore, the selected molecule has the potential to meet the herein proposed target.

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Malaria is the world's most widespread protozoan infection, being responsible for more than 445,000 annual deaths. Among the malaria parasites, Plasmodium falciparum is the most prevalent and lethal. In this context, the search for new antimalarial drugs is urgently needed. P. falciparum superoxide dismutase (PfSOD) is an important enzyme involved in the defense mechanism against oxidative stress. The goal of this study was to identify through hierarchical screening on pharmacophore models and molecular dynamics (MD), promising allosteric PfSOD inhibitors that do not show structural requirements for human inhibition. MD simulations of 1000 ps were performed on PfSOD using GROMACS 5.1.2. For this, the AMBER99SB-ILDN force field was adapted to describe the metal-containing system. The simulations indicated stability in the developed system. Therefore, a covariance matrix was generated, in which it was possible to identify residues with correlated and anticorrelated movements with the active site. These results were associated with the results found in the predictor of allosteric sites, AlloSitePro, which affirmed the ability of these residues to delimit an allosteric site. Then, after successive filtering of the Sigma-Aldrich® compounds database for HsSOD1 and PfSOD pharmacophores, 152 compounds were selected, also obeying Lipinski's rule of 5. Further filtering of those compounds based on molecular docking results, toxicity essays, availability, and price filtering led to the selection of a best compound, which was then submitted to MD simulations of 20,000 ps on the allosteric site. The study concludes that the ZINC00626080 compound could be assayed against SODs. Graphical Abstract Plasmodium falciparum superoxide dismutase.