Virtual screening to identify Leishmania braziliensis N-myristoyltransferase inhibitors: pharmacophore models, docking, and molecular dynamics

• Published in: Journal of molecular modeling 2018-09, Vol.24 (9), p.260-10, Article 260
• Main Authors: de Carvalho Gallo, Juliana Cecília, de Mattos Oliveira, Larissa, Araújo, Janay Stefany Carneiro, Santana, Isis Bugia, dos Santos Junior, Manoelito Coelho
• Format: Article
• Language: English
• Subjects: Acyltransferases - antagonists & inhibitors; Acyltransferases - chemistry; Antiprotozoal Agents - chemistry; Characterization and Evaluation of Materials; Chemical bonds; Chemistry; Chemistry and Materials Science; Computer Appl. in Life Sciences; Computer Applications in Chemistry; Computer simulation; Coordination compounds; Drug Evaluation, Preclinical; Enzyme Inhibitors - chemistry; Hydrogen bonds; Hydrophobicity; Inhibitors; Leishmania braziliensis - enzymology; Molecular docking; Molecular Docking Simulation; Molecular dynamics; Molecular Dynamics Simulation; Molecular Medicine; Nitrogen; Original Paper; Pharmacology; Proteins; Protozoa; Protozoan Proteins - antagonists & inhibitors; Protozoan Proteins - chemistry; Screening; Stability analysis; Theoretical and Computational Chemistry; XIX - Brazilian Symposium of Theoretical Chemistry (SBQT2017)
• ISSN: 1610-2940; 0948-5023
• DOI: 10.1007/s00894-018-3791-8

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 ( Lb NMT) 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.