主 办:北 京 中 医 药 大 学
ISSN 1006-2157 CN 11-3574/R

北京中医药大学学报 ›› 2019, Vol. 42 ›› Issue (1): 44-51.doi: 10.3969/j.issn.1006-2157.2019.01.008

• 中药药理 • 上一篇    下一篇

基于网络药理学的四逆散与酸枣仁汤治疗失眠分子机制的比较研究

刘梦, 吴凤芝, 张蔚, 王曦廷, 马捷, 戴宁, 张炜悦, 于姣姣, 谭丽博, 李杰, 李峰#   

  1. 北京中医药大学中医学院 北京 100029
  • 收稿日期:2018-06-06 出版日期:2019-01-30 发布日期:2019-03-01
  • 通讯作者: 李峰,男,博士,教授,博士生导师,研究方向:中医的病证结合,E-mail:lifeng95@vip.sina.com
  • 作者简介:刘梦,女,在读硕士生
  • 基金资助:
    北京市自然科学基金资助项目(No.7162124),北京中医药大学自主课题(No.2018-JYB-XS)

Molecular mechanism of Sini San and Suanzaoren Tang in treatment of insomnia based on network pharmacology: a comparative study

Liu Meng, Wu Fengzhi, Zhang Wei, Wang Xiting, Ma Jie, Dai Ning, Zhang Weiyue, Yu Jiaojiao, Tan Libo, Li Jie, Li Feng#   

  1. School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing 100029, China
  • Received:2018-06-06 Online:2019-01-30 Published:2019-03-01
  • Contact: Li Feng, male, PhD., Professor, Doctoral Supervisor. Research direction: combination of disease and pattern in Chinese medicine. E-mail: lifeng95@vip.sina.com
  • Supported by:
    Natural Science Foundation of Beijing (No. 7162124)

摘要: 目的 基于网络药理学方法探究四逆散与酸枣仁汤治疗失眠的分子机制并进行比较分析。方法 通过检索中药系统药理学分析平台(TCMSP)等中药化合物数据库构建四逆散与酸枣仁汤的活性化合物数据库,结合机器学习算法进行化合物靶标预测分析,并基于KEGG通路分析、基因本体(GO)富集分析、治疗靶点数据库(TTD)疾病关联性分析,运用Cytoscape软件构建四逆散及酸枣仁汤的“活性成分—靶标—疾病”复杂网络与拓扑分析。结果 从四逆散中得到活性成分145个,其中柴胡皂苷与槲皮素具有较高的结合活性,靶标1 306个,22个显著关联疾病,49个显著性KEGG通路,74个显著性GO富集通路;从酸枣仁汤中得到活性成分139个,其中酸枣仁皂苷与知母皂苷具有较高的结合活性,靶标1 386个,27个显著关联疾病,52个显著性KEGG通路,84个显著性GO富集通路。结论 通过复杂网络图计算与生物信息学分析,在分子生物学层面探讨四逆散与酸枣仁汤治疗失眠的潜在网络药理机制及活性成分,为中医方剂相似性及差异性比较提供新的方法学参考,为进一步揭示中医治疗失眠同病异治的机理提供新的研究思路。

关键词: 网络药理学, 四逆散, 酸枣仁汤, 失眠, 分子机制

Abstract: Objective To study and compare the molecular mechanism of Sini San (Cold-Limbs Powder) and Suanzaoren Tang (Spine Date Seed Decoction) in treatment of insomnia based on network pharmacology method. Methods A database of active compounds of Sini San and Suanzaoren Tang was established through searching the databases of Chinese medicinal compounds including traditional Chinese medicinal system pharmacology platform (TCMSP), and the predictive analysis of the compounds was conducted by using machine learning algorithm. Based on the analyses of KEGG pathway, gene ontology (GO) enrichment and disease association of therapeutic target database (TTD), Cytoscape software was used to construct complex network of active constituent-target-disease and topological analysis of the pharmacological mechanisms of Sini San and Suanzaoren Tang. Results There were 145 active constituents obtained from Sini San and among them saikoside and kaempferol had higher binding activities. There were 1 306 target proteins obtained and among them 22 were significantly correlated to diseases, and 49 significant KEGG pathways and 72 significant GO enrichment pathways obtained from Sini San. There were 139 active constituents obtained from Suanzaoren Tang and among them jujuboside and timosaponin had higher binding activities. There were 1 386 target proteins, 52 significant KEGG pathways and 84 significant GO enrichment pathways obtained from Suanzaoren Tang. Conclusion The potential network pharmacological mechanisms and active constituents of Sini San and Suanzaoren Tang in insomnia treatment are studied at the molecular biology level through complex network graph calculation and bioinformatics analysis. The purpose is to provide new ideas for further revealing the mechanism of treating insomnia with Chinese medicinal based on principle of different treatments for the same disease.

Key words: network pharmacology, Sini San (Cold-Limbs Powder), Suanzaoren Tang (Spine Date Seed Decoction), insomnia, molecular mechanism

中图分类号: 

  • R285.5