Pharmacophore based virtual screening & molecular docking approach for identification of mycobacterial membrane protein large 3 (MmpL3) inhibitors

药物数据库 药效团 虚拟筛选 化学 对接(动物) 结核分枝杆菌 计算生物学 立体化学 生物化学 肺结核 组合化学 生物 药品 药理学 医学 病理 护理部
作者
Abhijeet Dhulap,Paromita Banerjee
出处
期刊:Journal of Biomolecular Structure & Dynamics [Taylor & Francis]
卷期号:41 (20): 11062-11077
标识
DOI:10.1080/07391102.2022.2159876
摘要

Tuberculosis (TB) disease continues to remain one of the global threats for mankind. Till date many antibacterial compounds have been identified to target mycobacterium tuberculosis (MTB). However, the mutating nature of the mycobacteria has always posed a challenge for designing newer drugs which can target both the non-mutating and mutating forms of TB. In this process, Mycobacterial membrane protein Large 3 (MmpL3) transporter was identified as one of the key targets for inhibiting tuberculosis. Herein we have made an effort to find potential inhibitors against MmpL3 by using a pharmacophore-based virtual screening workflow, followed by molecular docking studies and molecular dynamic simulations. Based on a set of 220 compounds showing anti-tubercular activity proposed to target MmpL3 transporter with MIC values ranging from 0.003 to 737 μM, a 5-point pharmacophore ADHHR_2 model possessing one hydrogen acceptor, one hydrogen donor, two hydrophobic groups and an aromatic ring system was generated. The model validated by enrichment study was used to screen Asinex and DrugBank database to identify a potential lead compound such as DrugBank_6059 that was found to show better binding affinity (-11.36) and hydrophobic interactions with target protein in comparison to standard drug SQ109.Communicated by Ramaswamy H. Sarma.

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