江汉大学学报(自然科学版) ›› 2020, Vol. 48 ›› Issue (6): 23-32.doi: 10.16389/j.cnki.cn42-1737/n.2020.06.003

• COVID-19药理与临床 • 上一篇    下一篇

基于网络药理学的“金叶败毒颗粒”防治COVID-19作用机制探索

袁发浒,刘丽,巴瑞琪,陈江源,黄丽霞,朱书秀*   

  1. 江汉大学 医学院,湖北 武汉 430056
  • 出版日期:2020-12-28 发布日期:2020-12-18
  • 作者简介:袁发浒(1988— ),男,实验师,博士生,研究方向:病原生物学与免疫学。
  • 基金资助:
    ZHU Shuxiu

Mechanism Exploration of Jinyebaidu Particles Against COVID- 19 Based on Network Pharmacology

YUAN Fahu,LIU Li,BA Ruiqi,CHEN Jiangyuan,HUANG Lixia,ZHU Shuxiu*   

  1. School of Medicine,Jianghan University,Wuhan 430056,Hubei,China
  • Online:2020-12-28 Published:2020-12-18
  • Contact: 朱书秀
  • Supported by:
    国家自然科学基金资助项目(81674060)

摘要: 目 的 探寻金叶败毒颗粒治疗新型冠状病毒肺炎(coronavirus disease 2019,COVID-19)的药理作用机制。方 法 通过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)、中药分子机制的生物信息学分析工具(Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine,BATMAN-TCM)检索筛选金叶败毒颗粒中金银花、蒲公英、鱼腥草、大青叶的化学成分和作用靶点。查询OMIM(Online Mendelian Inheritance in Man)、GeneCards 数据库获得疾病相关靶点基因,进而运用Cytoscape 软件构建药物活性分子- 靶点基因作用网络,通过R 语言包clusterProfiler 进行基因本体(gene ontology,GO)功能注释和基于京都基因与基因组百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)通路富集分析,预测金叶败毒颗粒对COVID-19 的作用机制。结 果 共筛选获得药物活性分子31个。靶点基因110 个,主要包含PTGS2、AR、ESR1、PPARG 、PRSS1、NOS2、NR3C2 等核心靶点。富集分析得到GO 条目2 138 项(P < 0. 05),KEGG 信号通路134 条(P < 0. 05),主要富集的通路有AGE-RAGE 信号通路、动脉粥样硬化、TNF- α 信号通路、甲型流感等。结 论 金叶败毒颗粒的活性化合物能作用于TNF 信号等核心炎症通路,从而对COVID-19 起到抗氧化损伤、抗炎作用。

关键词: 金叶败毒, 颗粒剂, 新型冠状病毒, 肺炎, 网络药理学

Abstract: Objective To explore the pharmacological mechanism of Jinyebaidu Particles in the treatment of coronavirus disease 2019 (COVID-19). Methods Through searching Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP)and Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM) to select the chemical constituents and action targets of Lonicerae Japonicae Flos,Houttuyniae Herba,Isatidis Folium,Taraxacum mongolicum Hand.-Mazz in Jinyebaidu Particles. The disease-related target genes were obtained by consulting Online Mendelian Inheritance in Man (OMIM) and GeneCards database,and then the drug-active molecules-target gene action network was constructed using Cytoscape software. Gene ontology (GO) functional annotation and enrichment analysis based on Kyoto Encyclopedia of Genes and Genomes(KEGG) pathways were conducted by the R package cluster Profiler to predict the mechanism of action of Jinyebaidu Particles on COVID-19. Results A total of 31 active molecules and 110 target genes were screened,mainly including PTGS2,AR,ESR1,PPARG,PRSS1,NOS2,NR3C2 and other core targets. Enrichment analysis revealed 2 138 GO items(P < 0. 05)and 134 KEGG signaling pathways (P < 0. 05). The main enrichment pathways included AGE-RAGE signaling pathway,atherosclerosis,TNF-α signaling pathway,Influenza A pathway. Conclusion The active compounds of Jinyebaidu Particles can act on core inflammatory pathways such as TNF signaling,thus exerting antioxidant damage and anti-inflammatory effects on COVID-19.

Key words: Jinyebaidu, particles, coronavirus disease 2019 (COVID-19), pneumonia, network pharmacology

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