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Intrabacterial Metabolism Obscures the Successful Prediction of an InhA Inhibitor of Mycobacterium tuberculosis.
ACS Infectious Diseases ( IF 5.3 ) Pub Date : 2019-11-05 , DOI: 10.1021/acsinfecdis.9b00295
Xin Wang 1 , Alexander L Perryman 1 , Shao-Gang Li 1 , Steve D Paget 1 , Thomas P Stratton 1 , Alex Lemenze 2 , Arthur J Olson 3 , Sean Ekins 4 , Pradeep Kumar 2 , Joel S Freundlich 1, 2
Affiliation  

Tuberculosis, caused by Mycobacterium tuberculosis (M. tuberculosis), kills 1.6 million people annually. To bridge the gap between structure- and cell-based drug discovery strategies, we are pioneering a computer-aided discovery paradigm that merges structure-based virtual screening with ligand-based, machine learning methods trained with cell-based data. This approach successfully identified N-(3-methoxyphenyl)-7-nitrobenzo[c][1,2,5]oxadiazol-4-amine (JSF-2164) as an inhibitor of purified InhA with whole-cell efficacy versus in vitro cultured M. tuberculosis. When the intrabacterial drug metabolism (IBDM) platform was leveraged, mechanistic studies demonstrated that JSF-2164 underwent a rapid F420H2-dependent biotransformation within M. tuberculosis to afford intrabacterial nitric oxide and two amines, identified as JSF-3616 and JSF-3617. Thus, metabolism of JSF-2164 obscured the InhA inhibition phenotype within cultured M. tuberculosis. This study demonstrates a new docking/Bayesian computational strategy to combine cell- and target-based drug screening and the need to probe intrabacterial metabolism when clarifying the antitubercular mechanism of action.

中文翻译:

细菌内代谢掩盖了结核分枝杆菌InhA抑制剂的成功预测。

结核分枝杆菌M. tuberculosis)引起的结核病每年造成160万人死亡。为了弥合基于结构的药物发现策略和基于细胞的药物发现策略之间的鸿沟,我们正在开创一种计算机辅助发现范例,该模型将基于结构的虚拟筛选与基于配体的,经过细胞数据训练的机器学习方法相结合。该方法成功鉴定出N-(3-甲氧基苯基)-7-硝基苯并[ c ] [1,2,5]恶二唑-4-胺(JSF-2164)是纯化的InhA抑制剂,与体外培养相比具有全细胞功效结核分枝杆菌。当利用细菌内药物代谢(IBDM)平台时,机理研究表明JSF-2164在结核分枝杆菌内进行了快速的F 420 H 2依赖性生物转化,从而提供了细菌内一氧化氮和两种胺,分别为JSF-3616和JSF- 3617。因此,JSF-2164的代谢掩盖了培养的结核分枝杆菌中的InhA抑制表型。这项研究证明了一种新的对接/贝叶斯计算策略,可以结合基于细胞和靶标的药物筛选以及在阐明抗结核作用机制时探查细菌内新陈代谢的需求。
更新日期:2019-11-05
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