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基于结构的虚拟筛选和分子动力学分析从中药中鉴定有效的氯离子细胞内通道蛋白 1 抑制剂。

Identification of Potent Chloride Intracellular Channel Protein 1 Inhibitors from Traditional Chinese Medicine through Structure-Based Virtual Screening and Molecular Dynamics Analysis.

机构信息

Department of Thoracic Surgery, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China.

Guangzhou Institute of Respiratory Diseases and China State Key Laboratory of Respiratory Disease, Guangzhou 510120, China.

出版信息

Biomed Res Int. 2017;2017:4751780. doi: 10.1155/2017/4751780. Epub 2017 Sep 25.

Abstract

Chloride intracellular channel 1 (CLIC1) is involved in the development of most aggressive human tumors, including gastric, colon, lung, liver, and glioblastoma cancers. It has become an attractive new therapeutic target for several types of cancer. In this work, we aim to identify natural products as potent CLIC1 inhibitors from Traditional Chinese Medicine (TCM) database using structure-based virtual screening and molecular dynamics (MD) simulation. First, structure-based docking was employed to screen the refined TCM database and the top 500 TCM compounds were obtained and reranked by -Score. Then, 30 potent hits were achieved from the top 500 TCM compounds using cluster and ligand-protein interaction analysis. Finally, MD simulation was employed to validate the stability of interactions between each hit and CLIC1 protein from docking simulation, and Molecular Mechanics/Generalized Born Surface Area (MM-GBSA) analysis was used to refine the virtual hits. Six TCM compounds with top MM-GBSA scores and ideal-binding models were confirmed as the final hits. Our study provides information about the interaction between TCM compounds and CLIC1 protein, which may be helpful for further experimental investigations. In addition, the top 6 natural products structural scaffolds could serve as building blocks in designing drug-like molecules for CLIC1 inhibition.

摘要

氯离子通道蛋白 1(CLIC1)参与了大多数侵袭性人类肿瘤的发展,包括胃癌、结肠癌、肺癌、肝癌和神经胶质瘤。它已成为几种类型癌症的一个有吸引力的新治疗靶点。在这项工作中,我们旨在使用基于结构的虚拟筛选和分子动力学(MD)模拟,从中药(TCM)数据库中鉴定出作为有效 CLIC1 抑制剂的天然产物。首先,我们采用基于结构的对接方法筛选精制的 TCM 数据库,获得了前 500 个 TCM 化合物,并通过 -Score 重新排序。然后,通过聚类和配体-蛋白相互作用分析,从前 500 个 TCM 化合物中获得了 30 个潜在的命中化合物。最后,我们采用 MD 模拟验证对接模拟中每个命中化合物与 CLIC1 蛋白相互作用的稳定性,并使用分子力学/广义 Born 表面面积(MM-GBSA)分析对虚拟命中化合物进行优化。具有最佳 MM-GBSA 评分和理想结合模型的 6 种 TCM 化合物被确认为最终命中化合物。我们的研究提供了关于 TCM 化合物与 CLIC1 蛋白相互作用的信息,这可能有助于进一步的实验研究。此外,前 6 个天然产物的结构骨架可以作为设计用于 CLIC1 抑制的类药分子的构建模块。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7ec/5632872/fbe7d17e2ccd/BMRI2017-4751780.001.jpg

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