基于网络药理学和分子对接的荆防败毒散预防新型冠状病毒肺炎的活性成分研究
投稿时间:2020-05-26  修订日期:2020-10-16  点此下载全文
引用本文:冯群,关永霞,黄志艳,叶士莉,程国良,姚景春,张贵民.基于网络药理学和分子对接的荆防败毒散预防新型冠状病毒肺炎的活性成分研究[J].药学实践杂志,2020,38(6):485~491,538
摘要点击次数: 1190
全文下载次数: 1289
作者单位E-mail
冯群 鲁南厚普制药有限公司山东 临沂 276006
鲁南制药集团股份有限公司中药制药共性技术国家重点实验室山东 临沂 276006 
 
关永霞 鲁南厚普制药有限公司山东 临沂 276006
鲁南制药集团股份有限公司中药制药共性技术国家重点实验室山东 临沂 276006 
 
黄志艳 鲁南制药集团股份有限公司中药制药共性技术国家重点实验室山东 临沂 276006  
叶士莉 鲁南制药集团股份有限公司中药制药共性技术国家重点实验室山东 临沂 276006  
程国良 鲁南制药集团股份有限公司中药制药共性技术国家重点实验室山东 临沂 276006  
姚景春 鲁南制药集团股份有限公司中药制药共性技术国家重点实验室山东 临沂 276006
山东新时代药业有限公司山东 临沂 273400 
 
张贵民 鲁南厚普制药有限公司山东 临沂 276006
鲁南制药集团股份有限公司中药制药共性技术国家重点实验室山东 临沂 276006
山东新时代药业有限公司山东 临沂 273400 
gmzhanglunan@163.com 
基金项目:山东省重点研发计划(重大科技创新工程)项目(2017CXGC1308)
中文摘要:目的 运用网络药理学和分子对接方法,预测荆防败毒散预防新型冠状病毒肺炎(COVID-19)的活性成分,为临床用药提供参考。方法 通过中药系统药理学分析平台,检索荆防败毒散组方中所有药材的化学成分和作用靶点。通过Uniprot数据库校正靶点对应的基因,利用Cytoscape软件构建药材-成分-靶点网络并进行可视化处理,利用疾病数据库检索COVID-19相关的靶点,筛选出重合的靶点,通过String数据库构建蛋白-蛋白相互作用网络。通过Metascape进行GO富集分析和KEGG通路富集分析,预测其作用机制,通过分子对接,计算核心成分在预防新型冠状病毒肺炎的作用强度。结果 限定筛选条件为口服生物利用度(OB)≥30%、类药性(DL)≥0.18,共得到荆防败毒散的159个活性成分和277个靶点,与获得的273个COVID-19相关的靶点取交集,得到55个核心靶点;对核心靶点进行GO富集分析和KEGG通路富集分析,得到GO条目1376个和136条信号通路,涉及感染性疾病、癌症、细胞进程、免疫系统、信号等通路。分子对接结果显示荆防败毒散核心成分与SARS-CoV-2 3CL水解酶、血管紧张素转化酶II(ACE2)具有较强的结合能力,结合形式有氢键、疏水作用。结论 荆防败毒散中的活性成分能通过抑制新型冠状病毒(SARS-CoV-2)蛋白,ACE2结合,通过对多靶点、多通路的作用发挥对COVID-19的防治作用。
中文关键词:荆防败毒散  新型冠状病毒  新型冠状病毒肺炎  网络药理学  分子对接
 
Study on active ingredients of Jingfang Baidu San for preventing COVID-19 based on network pharmacology and molecular docking
Abstract:Objective To investigate the active ingredients of Jingfang Baidu San for the prevention and treatment of COVID-19 by using network pharmacology and molecular docking, and to provide references for clinical applications.Methods The chemical constituents and action targets of all medicinal materials in Jingfang Baidu San were retrieved from TCMSP. Uniprot database was used to search the corresponding genes of targets. Cytoscape software was used to construct the network of medicinal materials-compounds-targets for visualization. The target proteins of COVID-19 were searched by disease databases. The intersection of both was considered to be analyzed to establish the protein-protein interaction (PPI) network by STRING database. GO function enrichment analysis and KEGG pathway enrichment analysis were performed through Metascape database to predict its mechanism. The effective strength of core constituents on preventing COVID-19 was calculated by molecular docking method.Results A total of 159 effective ingredients and 277 potential targets were obtained in Jingfang Baidu San within the given screening conditions [oral bioavailability (OB) ≥30%; drug-like (DL) ≥ 0.18], including 55 core targets with the intersection of 273 targets of COVID-19. According to the results of GO and KEGG enrichment analysis performed on the core targets, 1376 GO items and 136 KEGG pathways were obtained, involving infectious diseases, cancer, cell progress, immune system, signaling pathways etc. The results of molecular docking indicated strong binding capacity between the core ingredients and SARS-CoV-2 3CL hydrolase or angiotensin-converting enzyme II (ACE2). The hydrogen binding and hydrophobic effect were the main forms of the interaction.Conclusion The active ingredients in Jingfang Baidu San can inhibit the binding between SARS-CoV-2 protein and ACE2, thus regulating multiple targets and signal pathways, which plays a role in the prevention and the treatment of COVID-19.
keywords:Jingfang Baidu San  SARS-CoV-2  COVID-19  network pharmacology  molecular docking
查看全文  查看/发表评论  下载PDF阅读器
关闭

分享按钮