基于网络药理学探究小青龙汤治疗新型冠状病毒肺炎的作用机制

doi:10.3976/j.issn.1002-4026.2023.03.002

摘要/Abstract

摘要：

基于网络药理学探究小青龙汤治疗新型冠状病毒感染(COVID-19)的作用机制。应用中药系统药理学数据库与分析平台(traditional Chinese medicine systems pharmacology database and analysis platform,TCMSP)筛选小青龙汤8味中药的活性成分,运用PubChem、SwissTargetPrediction和TCMSP数据库获取中药的潜在作用靶点;运用OMIM、DisGeNET和GeneCards 数据库筛选COVID-19和Delta variant of COVID-19相关靶点;利用Venny 2.1在线工具筛选出小青龙汤靶点和COVID-19靶点的交集并作维恩图;应用Cytoscape 3.7.2 软件构建小青龙汤-成分-(COVID-19)-靶点网络;利用STRING数据库收集数据,并在线构建蛋白质-蛋白质相互作用网络;应用Metascape数据库进行基因本体(gene ontology, GO)和基于京都基因与基因组百科全书 ( Kyoto encyclopedia of genes and genomes, KEGG)富集分析,借助微生信在线绘图工具绘制GO和KEGG富集分析图。利用AutoDockTools 1.5.6软件进行分子对接。筛选得到小青龙汤有效活性成分共169个及靶点1 363个,药物与疾病相交靶点292个, 得到GO富集分析中生物过程共2 393条,细胞成分共168条,分子功能共264条,KGGG通路共225条。分子对接结果显示筛选出的小青龙汤核心成分与COVID-19相关靶点结合良好。该研究揭示了小青龙汤可能通过作用于TNF、AKT1、GAPDH、IL-6、ALB、TP53、IL-1β、VEGFA、STAT3、EGFR等靶点,参与MAPK信号通路、PI3K-Akt信号通路、糖尿病并发症中的AGE-RAGE信号通路等通路治疗COVID-19。

关键词: 小青龙汤, 新型冠状病毒感染, 网络药理学, 作用机制

Abstract:

This research aims to study the mechanism of Xiaoqinglong Decoction in the treatment of coronavirus disease 2019 (COVID-19) based on network pharmacology. The traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) online tool was used to screen the active ingredients of Xiaoqinglong Decoction. PubChem, SwissTargetPrediction, and TCMSP databases were used to obtain the potential targets of eight traditional Chinese medicines. OMIM, DisGeNET, and GeneCards databases were used to obtain COVID-19 and delta variant of COVID-19 related targets. The intersecting targets of eight traditional Chinese medicines and Xiaoqinglong decoction and COVID-19 were screened using online tool Venny 2.1, and a Venn diagram was prepared. The Cytoscape 3.7.2 software was used to construct Xiaoqinglong Decoction-components-(COVID-19)-target network. After using STRING database to collect data, protein-protein interaction network was built online. Metascape database was used for gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis, and the GO and KEGG enrichment analysis maps were plotted using Weishengxin online plotting tool. Molecular docking was performed using the AutoDockTools 1.5.6 software. A total of 169 active ingredients, 1 363 targets of Xiaoqinglong Decoction, and 292 intersecting targets of drugs and diseases were screened. A total of 2 393 biological process, 168 cell components, 264 molecular functions were obtained via GO enrichment analysis. A total of 225 pathways were obtained via KEGG. Molecular docking showed that the core components of Xiaoqinglong Decoction screened in this study combined well with the COVID-19 related targets. Xiaoqinglong Decoction could treat COVID-19 through TNF, AKT1, GAPDH, IL-6, ALB, TP53, IL-1β, VEGFA, STAT3, EGFR, and other targets and participate in MAPK signaling pathway, PI3K-Akt signaling pathway, AGE-RAGE signaling pathway in diabetes complications, and other pathways.

Key words: Xiaoqinglong Decoction, COVID-19, network pharmacology, action mechanism

中图分类号:

R285

朱洁, 王征, 梁艳妮. 基于网络药理学探究小青龙汤治疗新型冠状病毒肺炎的作用机制[J]. 山东科学, 2023, 36(3): 10-17.

ZHU Jie, WANG Zheng, LIANG Yanni. The mechanism of Xiaoqinglong Decoction in treatment of COVID-19 based on network pharmacology[J]. Shandong Science, 2023, 36(3): 10-17.

图/表 3

参考文献 43

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活性成分	核心靶点		活性成分	核心靶点
活性成分	ACE2	PLP	活性成分	ACE2	PLP
槲皮素	-7.9	-8.9	甘草黄酮	-6.6	-8.0
山柰酚	-8.1	-9.1	光甘草宁	-6.1	-7.7
β-谷甾醇	-9.2	-8.3	半甘草异黄酮B	-6.4	-6.5
儿茶素	-7.8	-9.1	丁子香萜	-9.4	-7.0
黄芩苷	-9.8	-9.4	豆甾醇	-7.9	-6.5
芍药苷	-8.5	-7.9	紫杉醇	-4.7	-5.7
甘草酚	-6.8	-7.7	柚皮素	-5.9	-5.8
松柏素	-6.3	-5.1