基于结构的计算机辅助方法在硝基咪唑衍生物支架上设计抗结核药物的见解

IF 4.6 3区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY
RSC Advances Pub Date : 2025-07-03 DOI:10.1039/D5RA01362C
Wei Yang, Hui Zhao, Ziting Zhao, Shaojun Pei, Zheng Zhu, Zhen Huang, Yao Zhao, Shuihua Lu, Fangfang Wang and Yanlin Zhao
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引用次数: 0

摘要

去氮黄素依赖的硝基还原酶(Ddn)是参与霉菌酸生物合成的关键酶,是结核分枝杆菌(MTB)细胞壁的重要组成部分,结核分枝杆菌是导致结核病的细菌病原体。在过去的二十年里,硝基咪唑-恶嗪支架(NOS)衍生物作为靶向Ddn治疗MTB的潜在药物被研究,其重点是提高药物疗效、降低毒性和对抗耐药。在这项研究中,我们结合三维定量构效关系(3D-QSAR)研究、全原子分子对接和原子水平分子动力学(MD)模拟进行了广泛的理论研究。此外,我们还分析了抑制剂与Ddn之间的结合自由能及其分解项,以阐明一系列抑制MTB的NOS衍生物的构效关系(sar)和机制。CoMFA和CoMSIA模型的交叉验证系数(Rcv2)分别为0.591和0.629,预测系数(Rpred2)分别为0.7698和0.6848。这些模型基于NOS支架有效地预测了化合物对MTB的最小抑制浓度(MIC)值。通过分子对接和MD模拟来验证这些衍生物在Ddn活性位点的结合模式,从而详细了解它们的相互作用模式。值得注意的是,我们的分析显示,Tyr65、Ser78、Tyr130、Tyr133和Tyr136残基通过显著影响化合物的结合能,在决定化合物效力方面发挥了关键作用。这些发现为合理设计新型NOS抑制剂提供了有价值的指导,增强了NOS抑制剂作为有效抗结核药物的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Insights into anti-tuberculosis drug design on the scaffold of nitroimidazole derivatives using structure-based computer-aided approaches†

Insights into anti-tuberculosis drug design on the scaffold of nitroimidazole derivatives using structure-based computer-aided approaches†

Deazaflavin-dependent nitroreductase (Ddn) is a crucial enzyme involved in mycolic acid biosynthesis, a vital component of the cell wall in Mycobacterium tuberculosis (MTB)—the bacterial pathogen responsible for tuberculosis. Over the past two decades, nitroimidazole oxazine scaffold (NOS) derivatives have been investigated as potential therapeutic agents targeting Ddn in MTB, with a focus on enhancing drug efficacy, minimizing toxicity, and combating drug resistance. In this study, we performed an extensive theoretical investigation combining three-dimensional quantitative structure–activity relationship (3D-QSAR) studies, all-atom molecular docking, and atomic-level molecular dynamics (MD) simulations. Additionally, we analyzed the binding free energies and their decomposed terms between inhibitors and Ddn to elucidate the structure–activity relationships (SARs) and mechanisms of a series of NOS derivatives developed for MTB inhibition. The CoMFA and CoMSIA models demonstrated strong performance, with cross-validation coefficients (Rcv2) of 0.591 and 0.629, respectively, and prediction coefficients (Rpred2) of 0.7698 and 0.6848 for CoMFA and CoMSIA, respectively. These models effectively predicted the minimum inhibitory concentration (MIC) values of the compounds against MTB based on the NOS scaffold. Molecular docking followed by MD simulations was employed to validate the binding modes of these derivatives at the active site of Ddn, providing detailed insights into their interaction patterns. Notably, our analysis revealed that residues Tyr65, Ser78, Tyr130, Tyr133, and Tyr136 played critical roles in determining the potency of the compounds by contributing significantly to their binding energies. These findings provide valuable guidance for the rational design of novel NOS inhibitors with enhanced potential as effective anti-tuberculosis agents.

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来源期刊
RSC Advances
RSC Advances chemical sciences-
CiteScore
7.50
自引率
2.60%
发文量
3116
审稿时长
1.6 months
期刊介绍: An international, peer-reviewed journal covering all of the chemical sciences, including multidisciplinary and emerging areas. RSC Advances is a gold open access journal allowing researchers free access to research articles, and offering an affordable open access publishing option for authors around the world.
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