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基于网络药理学的雷公藤干预IgAN潜在靶点预测及作用机制分析
引用本文:熊冲,方桂玉,龚彩弟,陈虹彤,赵辉,王梓霞,陈萍,钟建.基于网络药理学的雷公藤干预IgAN潜在靶点预测及作用机制分析[J].世界科学技术-中医药现代化,2019,21(11):2373-2383.
作者姓名:熊冲  方桂玉  龚彩弟  陈虹彤  赵辉  王梓霞  陈萍  钟建
作者单位:广西中医药大学研究生学院 广西 530000,广西中医药大学研究生学院 广西 530000,广西中医药大学研究生学院 广西 530000,广西中医药大学研究生学院 广西 530000,安徽中医药大学研究生学院 安徽 230038,广西中医药大学研究生学院 广西 530000,广西中医药大学研究生学院 广西 530000,广西中医药大学第一附属医院 广西 530001
摘    要:目的 基于网络药理学的理念,运用网络分析的技术,拟探讨雷公藤干预IgAN(immunoglobulin Anephropathy)的潜在靶点预测及其作用机制。方法 利用TCMSP平台收集雷公藤的重要活性成分及潜在相关靶点信息,分别从 GeneCards数据库、OMIM数据库中获取与IgAN相关联的靶点;采用STRING平台构建PPI作用网络,使用Cytoscape 3.7.0对药物-活性成分-潜在靶点-疾病网络进行构建;通过DAVID数据库对相关疾病-药物靶点基因进行GO生物功能富集分析和KEGG代谢通路分析。结果 检索出雷公藤成分共144个,筛选获得重要活性成分共29个;收集到潜在作用靶点基因122个。检索出IgAN相关靶点333个,基因功能GO富集分析及KEGG代谢通路富集结果显示,雷公藤中的9个有效成分干预26个疾病靶点,通过对20个生物过程、12个分子功能、13个细胞成分产生作用。得到通路共50条,通过可视化分析,取靠前的30条通路,其中6条通路可能与IgAN发生及发展密切相关。结论 该研究基于网络药理学方法,表明了雷公藤中药多成分、多靶点、多功能、多通路干预IgAN的作用,为后续临床及研究开展相应工作提供了较为可观的信息和理论依据。

关 键 词:雷公藤  IgAN  网络药理学  生物信息学  活性成分  靶点基因
收稿时间:2019/6/12 0:00:00
修稿时间:2019/12/20 0:00:00

Prediction of Potential Target of IgAN Intervention by Tripterygium Wilfordii Based on Network Pharmacology and its Mechanism
Xiong Chong,Fang Guiyu,Gong Caidi,Chen Hongtong,Zhao Hui,Wang Zixi,Chen Ping and Zhong Jian.Prediction of Potential Target of IgAN Intervention by Tripterygium Wilfordii Based on Network Pharmacology and its Mechanism[J].World Science and Technology-Modernization of Traditional Chinese Medicine,2019,21(11):2373-2383.
Authors:Xiong Chong  Fang Guiyu  Gong Caidi  Chen Hongtong  Zhao Hui  Wang Zixi  Chen Ping and Zhong Jian
Institution:Graduate School of Guangxi University of Traditional Chinese Medicine, Guangxi 530000, China,Graduate School of Guangxi University of Traditional Chinese Medicine, Guangxi 530000, China,Graduate School of Guangxi University of Traditional Chinese Medicine, Guangxi 530000, China,Graduate School of Guangxi University of Traditional Chinese Medicine, Guangxi 530000, China,Graduate School of Anhui University of Traditional Chinese Medicine, Anhui 230038, China,Graduate School of Guangxi University of Traditional Chinese Medicine, Guangxi 530000, China,Graduate School of Guangxi University of Traditional Chinese Medicine, Guangxi 530000, China,The First Affiliated Hospital of Guangxi University of Traditional Chinese Medicine, Guangxi 530001, China
Abstract:Objective Based on the concept of network pharmacology, using network analysis techniques, it is proposed to explore the potential target prediction of Tripterygium wilfordii IgAN and its mechanism of action.METHODS The important active components and potential related target information of Tripterygium wilfordii were collected by TCMSP platform. The targets associated with IgAN were obtained from GeneCards database and OMIM database respectively. The PPI network was constructed by STRING platform, using Cytoscape 3.7.0. The drug-active ingredient-potential target-disease network was constructed, and the GO-function enrichment analysis and KEGG metabolic pathway analysis were performed on the relevant disease-drug target genes by the DAVID database.RESULTS A total of 144 components of Tripterygium wilfordii were retrieved, and 29 important active ingredients were screened. 122 potential target genes were collected. 333 IgAN-related targets were retrieved, and gene function GO enrichment analysis and KEGG metabolic pathway enrichment showed that 9 active components in Tripterygium wilfordii interfered with 26 disease targets through 20 biological processes and 12 molecular functions. 13 cellular components work. A total of 50 pathways were obtained. Through visual analysis, the top 30 pathways were taken, and 6 of them may be closely related to the occurrence and development of IgAN.Conclusion This study based on the network pharmacology method, clarified the role of multi-component, multi-target, multi-functional and multi-channel intervention of IgAN in Tripterygium wilfordii Hook. It provided a considerable information and theoretical basis for the subsequent clinical and research work.
Keywords:Tripterygium wilfordii  IgAN  network pharmacology  active ingredient  target gene
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