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基于网络药理学和分子对接的葛根芩连汤治疗 COVID-19 合并糖尿病的作用机制研究:综述。

Molecular mechanism of the effect of Gegen Qinlian decoction on COVID-19 comorbid with diabetes mellitus based on network pharmacology and molecular docking: A review.

机构信息

Jingmen Central Hospital, Jingmen, China.

AnKang University, School of Medicine, AnKang, China.

出版信息

Medicine (Baltimore). 2023 Nov 3;102(44):e34683. doi: 10.1097/MD.0000000000034683.

Abstract

To explore the potential mechanism of Gegen Qinlian decoction (GGQL) in the treatment of COVID-19 comorbid with diabetes mellitus (DM) through network pharmacology and molecular docking, and to provide theoretical guidance for clinical transformation research. Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform was used to screen the active compounds and targets of GGQL, the targets of COVID-19 comorbid with DM were searched based on Genecards database. Protein-protein interaction network was constructed using String data platform for the intersection of compounds and disease targets, the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis of the intersection targets was performed using DAVID database. Cytoscape software was used to construct the "compound target-pathway (C-T-P)" of GGQL in the treatment of COVID-19 comorbid with DM, the molecular docking platform was used to complete the simulated docking of key compounds and targets. We obtained 141 compounds from GGQL, revealed 127 bioactive compounds and 283 potential targets of GGQL. Quercetin, kaempferol and formononetin in GGQL play a role by modulating the targets (including AR, GSK3B, DPP4, F2, and NOS3). GGQL might affect diverse signaling pathways related to the pathogenesis of coronavirus disease - COVID-19, AGE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, human cytomegalovirus infection and Th17 cell differentiation. Meanwhile, molecular docking showed that the selected GGQL core active components had strong binding activity with the key targets. This study revealed that GGQL play a role in the treatment of COVID-19 comorbid with DM through multi-component, multi-target and multi-pathway mode of action, which provided good theoretical basis for further verification research.

摘要

为了通过网络药理学和分子对接探索葛根芩连汤(GGQL)治疗 COVID-19 合并糖尿病(DM)的潜在机制,并为临床转化研究提供理论指导。使用中药系统药理学数据库和分析平台筛选 GGQL 的活性化合物和靶点,基于 Genecards 数据库搜索 COVID-19 合并 DM 的靶点。使用 String 数据平台构建化合物和疾病靶点的交集蛋白-蛋白相互作用网络,使用 DAVID 数据库对交集靶点进行基因本体论和京都基因与基因组百科全书分析。使用 Cytoscape 软件构建 GGQL 治疗 COVID-19 合并 DM 的“化合物-靶点-通路(C-T-P)”,使用分子对接平台完成关键化合物和靶点的模拟对接。我们从 GGQL 中获得 141 种化合物,揭示了 GGQL 的 127 种生物活性化合物和 283 个潜在靶点。GGQL 中的槲皮素、山奈酚和芒柄花素通过调节靶点(包括 AR、GSK3B、DPP4、F2 和 NOS3)发挥作用。GGQL 可能影响与冠状病毒病 COVID-19 发病机制相关的多种信号通路、糖尿病并发症的 AGE-RAGE 信号通路、IL-17 信号通路、人巨细胞病毒感染和 Th17 细胞分化。同时,分子对接表明,所选 GGQL 核心活性成分与关键靶点具有很强的结合活性。本研究表明,GGQL 通过多成分、多靶点和多途径的作用方式在治疗 COVID-19 合并 DM 中发挥作用,为进一步验证研究提供了良好的理论基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5720/10627614/c4f34cb773f5/medi-102-e34683-g001.jpg

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