ArticleJournal of molecular modeling2018
Virtual screening to identify Leishmania braziliensis N-myristoyltransferase inhibitors: pharmacophore models, docking, and molecular dynamics.
Article in Journal of molecular modeling, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Review
- How does aSaudi journal of biological sciences · 2024Article
- Development of Potential Multi-Target Inhibitors for Human Cholinesterases and Beta-Secretase 1: A Computational Approach.Pharmaceuticals (Basel, Switzerland) · 2023Article
- Molecular Multi-Target Approach for Human Acetylcholinesterase, Butyrylcholinesterase andPharmaceuticals (Basel, Switzerland) · 2023Article
- Recent Advances in Chemotherapeutics for Leishmaniasis: Importance of the Cellular Biochemistry of the Parasite and Its Molecular Interaction with the Host.Pathogens (Basel, Switzerland) · 2023Review
- Screening of potential inhibitors targeting the main protease structure of SARS-CoV-2Frontiers in pharmacology · 2022Article
- Discovery of Novel Pyruvate Kinase Inhibitors AgainstTurkish journal of pharmaceutical sciences · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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Registered trials
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