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中国防痨杂志 ›› 2022, Vol. 44 ›› Issue (2): 131-140.doi: 10.19982/j.issn.1000-6621.20210433

• 论著 • 上一篇    下一篇

中药治疗肺结核的用药规律及其核心药物作用机制的探讨

刘媛1, 陈洁1, 孙辉1, 刘幸1, 刘梦醒1, 李池川1, 杨柏荣2(), 杨敏1()   

  1. 1昆明市第三人民医院药学部,昆明 650000
    2昆明市中医医院药剂科,昆明 650000
  • 收稿日期:2021-08-02 出版日期:2022-02-10 发布日期:2022-02-14
  • 通信作者: 杨柏荣,杨敏 E-mail:18314534982@163.com;1330542876@qq.com
  • 基金资助:
    云南省教育厅科学研究基金(2022J0726);昆明市卫生科技人才培养项目“千”工程(2020-SW[Backup]-60);昆明市卫生健康委员会卫生科研课题(2021-16-01-0010);昆明市卫生健康委员会卫生科研课题(2020-0201-011)

Exploration of the drug use pattern of traditional Chinese medicine in the treatment of pulmonary tuberculosis and its core drug action mechanism

LIU Yuan1, CHEN Jie1, SUN Hui1, LIU Xing1, LIU Meng-xing1, LI Chi-chuan1, YANG Bai-rong2(), YANG Min1()   

  1. 1Department of Pharmacy, Kunming Third People’s Hospital, Kunming 650000, China
    2Department of Pharmacy, Kunming Municipal Hospital Traditional Chinese Medicine, Kunming 650000, China
  • Received:2021-08-02 Online:2022-02-10 Published:2022-02-14
  • Contact: YANG Bai-rong,YANG Min E-mail:18314534982@163.com;1330542876@qq.com
  • Supported by:
    Scientific Research Fund Project of the Education Department of Yunnan Province(2022J0726);Kunming Health Science and Technology Talent Training Project “Thousands” Project(2020-SW[Backup]-60);Health Research Project of the Kunming Health Commission(2021-16-01-0010);Health Research Project of the Kunming Health Commission(2020-0201-011)

摘要:

目的: 基于数据挖掘,探讨中药治疗肺结核的用药规律,挖掘出其常用药对,并借助网络药理学探讨其核心药物对肺结核的作用机制。方法: 对符合纳入标准的中药复方建立数据库,运用Apriori算法建立起关联模型,通过中药系统药理分析平台数据库筛选核心药对的活性成分和靶点,应用Gene Cards数据库检索肺结核疾病靶点,分析得到药物-疾病共同靶点,将靶点输入String数据库获得蛋白相互作用网络,通过DAVID数据库进行GO和KEGG通路富集分析,并利用Cytoscape软件对成分-靶点-信号通路进行可视化。结果: 筛选出符合要求的文献156篇,涉及272味中药,频次排名前5位的中药为百部(113次)、麦冬(104次)、黄芪(89次)、白及(86次)、地黄(83次)。关联分析后显示,白及、百部关联性最高(支持度:71.81%,置信度:80.99%,提升比:1.28)。对白及-百部药对进行网络药理学分析,白及-百部发挥的主要作用可能与癌症、乙型肝炎、结核病、凋亡、MAPK、TNF等相关信号通路有关(P值均<0.01)。结论: 通过数据挖掘,白及-百部为治疗肺结核的核心药对。网络药理学初步阐明核心药对白及-百部治疗肺结核的作用机制,可为临床新方组合和新药研发提供思路。

关键词: 结核,肺, 中草药, 数据挖掘, 药理作用分子作用机制

Abstract:

Objective: Based on data mining, we explored the drug use pattern of traditional Chinese medicine for pulmonary tuberculosis (PTB), mined out its common drug pairs, and explored the mechanism of action of core drugs on PTB using network pharmacology. Methods: A database was established for the Chinese herbal compounds meeting the inclusion criteria; association model was established using the Apriori algorithm; the active ingredients and targets of the core drug pairs were screened within the TCMSP database, while the PTB disease targets were retrieved by searching the Gene Cards database to analyze the drug-disease common targets, then the targets were entered into the String database to obtain the protein interaction network. DAVID database was used for GO and KEGG pathway enrichment analysis, and Cytoscape software was used to visualize the component-target-signaling pathway. Results: One hundred and fifty-six documents were screened, involving 272 Chinese herbal medicines. The top 5 herbs were Stemonae Radix (n=113), Ophiopogonis Radix (n=104), Astragali Radix (n=89), Bletillae Rhizoma (n=86) and Rehmanniae Radix (n=83). Association analysis showed that Bletillae Rhizoma and Stemonae Radix had the highest association (support=71.81%, confidence=80.99%, lifting ratio=1.28). With network pharmacological analysis for Bletillae Rhizoma and Stemonae Radix, the major effects exerted by them might be related with cancer, hepatitis B, tuberculosis, apoptosis, MAPK, TNF (all Ps<0.01). Conclusion: Data mining showed that Bletillae Rhizoma and Stemonae Radix were the core therapeutic drug pair for treating PTB. Network pharmacological analysis revealed primary mechanism of action for those core drugs on PTB, and provided ideas for new clinical drug combinations and new drug development.

Key words: Tuberculosis,pulmonary, Drugs,Chinese herbal, Data mining, Molecular mechanisms of pharmacological action

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