文章摘要
兰济乐,阮叶萍,蒋东晓.基于数据挖掘和网络药理学的失眠中药配方规律及作用机制研究[J].浙江中医药大学学报,2020,44(12):1230-1238, 1241.
基于数据挖掘和网络药理学的失眠中药配方规律及作用机制研究
Study on the Regularity and Mechanism of the Compatibility of Traditional Chinese Medicine for Treating Insomnia Based on Data Mining and Network Pharmacology
投稿时间:2020-07-06  
DOI:10.16466/j.issn1005-5509.2020.12.018
中文关键词: 失眠  中药  配方规律  数据挖掘  网络药理学  作用机制  关联规则  远志-酸枣仁-当归
英文关键词: insomnia  traditional Chinese medicine  medication rules of herbal prescriptions  data mining  network pharmacology  mechanisms of action  association rule  Polygala tenuifolia-Semen Zizyphi spinosae-Angelica sinensis
基金项目:国家自然科学基金项目(81641139);浙江省自然科学基金项目(LY20H280004)
作者单位E-mail
兰济乐 浙江中医药大学药学院 杭州 310053  
阮叶萍 浙江中医药大学药学院 杭州 310053 ruanyp@zjtcm.net 
蒋东晓 浙江中医药大学药学院 杭州 310053  
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中文摘要:
      [目的]基于数据挖掘和网络药理学方法,研究《中国知网中药方剂知识库》《中国方剂数据库》《方剂现代应用数据库》中治疗失眠的中药配伍用药规律,并探讨所得高频药组的作用机制。[方法]通过Microsoft Excel 2019软件统计中药频次,SPSS Modeler 18.0软件中的Apriori算法进行关联分析,SPSS Statistics 25.0软件进行聚类分析,运用中药分子作用机制生物信息学分析工具(bioinformatics analysis tool for molecular mechanism of TCM, BATMAN-TCM)构建“高频中药成分-靶点-疾病”网络,并对其作用靶点进行基因本体(gene ontology,GO)和京都基因与基因组百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)功能富集分析。[结果]筛选有效方剂共853首,含469味中药,核心药物有人参、茯苓、酸枣仁、当归、甘草,常用中药类型为补虚药、安神药、清热药、化痰止咳平喘药、解表药。关联规则分析得到6个药对、13个药组,聚类分析得到8个药对、7个药组,发掘得到远志、酸枣仁、当归等高频药组,其主要通过影响神经活动配体-受体相互作用,调控多巴胺能突触和γ-氨基丁酸(γ-aminobutyric acid,GABA)能突触,并通过调节氨基酸等基础代谢以及免疫功能起到抗失眠作用。[结论]关联规则与聚类分析以及网络分析结果表明,中药治疗失眠以安神益智、交通心肾、补脾益气等为主要治则,远志、酸枣仁、当归可能通过调控多巴胺能突触和GABA能突触,调节机体基础代谢和神经活动配体-受体相互作用、钙信号通路、磷酸肌醇-3-激酶-蛋白激酶β(phosphatidylinositol-3-kinase-protein kinase B,PI3K-Akt)信号通路等多条信号通路发挥治疗失眠的作用。
英文摘要:
      [Objective] Based on data mining and network pharmacology, anti-insomnia prescriptions were collected from "China Knowledge Network Chinese Medicine Formula Knowledge Base" "Chinese Prescription Database" and "Modern Application Database of Square Agents", to explore regularity of the compatibility of traditional Chinese medicines for treating insomnia, and to explore the mechanism of the core drug pair targets. [Methods] The frequency of traditional Chinese medicine(TCM) was counted by Microsoft Excel 2019 software. The association rules were analyzed by Apriori algorithm using SPSS Modeler 18.0. Cluster analysis was determined by SPSS Statistics 25.0. Use bioinformatics analysis tool for molecular mechanism of TCM(BATMAN-TCM) online analysis system to construct a “high-frequency use of TCM ingredients-targets-diseases” network and perform gene ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment analysis on the target. [Results] Finally, 853 effective prescriptions were included, involving 469 Chinese herbs. The core drugs were Panax ginseng, Poria cocos, Semen Zizyphi spinosae, Angelica sinensis and Glycyrrhiza. The commonly used types of TCM were tonic medicinals, Chinese medicine sedatives, heat-clearing medicinals, medicinals for dissolving phlegm, relieving cough, calming panting, and relieving exterior syndrome. six drug pairs and 13 drug groups were obtained by association rule analysis, and 8 drug pairs and 7 drug groups were obtained by cluster analysis. The Chinese medicines with high-frequency use for treating insomnia had Polygala tenuifolia, Semen Zizyphi spinosae and Angelica sinensis. The study found that neuroactive ligand-receptor interaction among others were the main molecular pathways for treatment of insomnia. They regulate dopaminergic synapses and γ-aminobutyric acidergic(GABAergic) synapses, and exert anti-insomnia effects by regulating basic metabolism such as amino acids and immune function. [Conclusion] The results of association rules and cluster analysis and network analysis showed that TCM treatment of insomnia had the main rule of calming the mind and promoting the mind, transporting the heart and kidney, and supplementing Qi and strengthening the spleen. Polygala tenuifolia, Semen Zizyphi spinosae and Angelica sinensis may play a role in treating insomnia by regulating dopaminergic synapses and GABAergic synapses, regulating the body's basic metabolism and neuroactive ligand-receptor interaction, calcium signaling pathway, phosphatidylinositol-3-kinase-protein kinase B(PI3K-Akt) signaling pathway and many other signaling pathways.
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