通过计算生物活性指纹和基于结构的虚拟筛选发现新型 DprE1 抑制剂。
Discovery of novel DprE1 inhibitors via computational bioactivity fingerprints and structure-based virtual screening.
机构信息
Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.
State Key Lab of CAD&CG, Zhejiang University, Hangzhou, 310058, China.
出版信息
Acta Pharmacol Sin. 2022 Jun;43(6):1605-1615. doi: 10.1038/s41401-021-00779-1. Epub 2021 Oct 19.
Abstract
Decaprenylphosphoryl-β-D-ribose oxidase (DprE1) plays important roles in the biosynthesis of mycobacterium cell wall. DprE1 inhibitors have shown great potentials in the development of new regimens for tuberculosis (TB) treatment. In this study, an integrated molecular modeling strategy, which combined computational bioactivity fingerprints and structure-based virtual screening, was employed to identify potential DprE1 inhibitors. Two lead compounds (B2 and H3) that could inhibit DprE1 and thus kill Mycobacterium smegmatis in vitro were identified. Moreover, compound H3 showed potent inhibitory activity against Mycobacterium tuberculosis in vitro (MIC = 1.25 μM) and low cytotoxicity against mouse embryo fibroblast NIH-3T3 cells. Our research provided an effective strategy to discover novel anti-TB lead compounds.
摘要
去氢牛心醇磷酸-β-D-核糖基氧化酶（DprE1）在分枝杆菌细胞壁的生物合成中发挥着重要作用。DprE1 抑制剂在开发新的结核病（TB）治疗方案方面显示出巨大的潜力。在这项研究中，采用了一种综合的分子建模策略，将计算生物活性指纹和基于结构的虚拟筛选相结合，以鉴定潜在的 DprE1 抑制剂。鉴定出两种可抑制 DprE1 并在体外杀死耻垢分枝杆菌的先导化合物（B2 和 H3）。此外，化合物 H3 对体外结核分枝杆菌具有很强的抑制活性（MIC = 1.25 μM），对小鼠胚胎成纤维细胞 NIH-3T3 细胞的细胞毒性较低。我们的研究为发现新型抗结核先导化合物提供了一种有效的策略。
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