In Silico Study to Identify New Antituberculosis Molecules from Natural Sources by Hierarchical Virtual Screening and Molecular Dynamics Simulations

Pharmaceuticals

JoaquínM. Campos¹  JanayS. C. Araújo²  FrancoH. A. Leite²  ManoelitoC. S. Junior²  Viníciusde S. Pinto²  RaiC. Silva³  GlauberV. da Costa⁴  CleydsonB. R. Santos⁴  MoysésF. De A. Neto⁵  JorddyN. Cruz⁶ 

[1] Department of Pharmaceutical and Organic Chemistry, Faculty of Pharmacy, University of Granada, 18071 Granada, Spain;Graduate Program in Biotechnology, State University of Feira de Santana, 44036-900 Feira de Santana, BA, Brazil;Graduate Program in Chemistry, Faculty of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, 14040-903 Ribeirão Preto, São Paulo, Brazil;Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, 68902-280 Macapá, AP, Brazil;Laboratory of Molecular Modeling, State University of Feira de Santana, 44036-900 Feira de Santana, BA, Brazil;Laboratory of Preparation and Computation of Nanomaterials, Federal University of Pará, 66075-110 Belém, PA, Brazil;

关键词: virtual screening;    pharmacophore model;    molecular docking;    β-ketoacyl-ACP synthase;    tuberculosis;   

DOI  :  10.3390/ph12010036

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown