广州医药 ›› 2024, Vol. 55 ›› Issue (5): 500-512.DOI: 10.3969/j.issn.1000-8535.2024.05.008

• 论著 • 上一篇    下一篇

基于数据挖掘和网络药理学研究中枢性性早熟的用药规律和作用机制

张春红1, 祝静文2   

  1. 1 广州中医药大学第一附属医院(广东广州 510000)
    2 广州中医药大学(广东广州 510000)
  • 收稿日期:2023-11-08 出版日期:2024-05-20 发布日期:2024-06-28

Research on the prescription rules and mechanism of central precocious puberty based on data mining and network pharmacology

ZHANG Chunhong1, ZHU Jingwen2   

  1. 1 The First Affiliated Hospital of Guangzhou University of Chinese Medicine,Guangzhou 510000,China
    2 Guangzhou University of Traditional Chinese Medicine,Guangzhou 510000,China
  • Received:2023-11-08 Online:2024-05-20 Published:2024-06-28

摘要: 目的 运用数据挖掘、网络药理学和分子对接的方法,探讨中药复方治疗中枢性性早熟(CPP)的用药规律和作用机制,为其临床治疗提供更多依据。方法 在中国知网(CNKI)、万方数据(Wanfang)、维普中文期刊(VIP)等数据库中检索从建库至2022年10月发表的中药复方治疗CPP的文献,用Excel 2021 收集整理临床治疗CPP的常用中药复方,并通过Excel 2021、SPSS Modeler 18.0、SPSS Statistics 25.0等软件对其进行频次、关联规律等分析,研究CPP治疗的用药规律。在上述基础上采用网络药理学的研究方法,筛选出高频药对的活性成分、作用靶点以及疾病的相关靶点,构建蛋白互作网络,并通过基因本体和京都基因 基因组百科全书通路富集分析来阐明药物的作用机制。最后运用 Autodock Vina 软件进行分子对接对结果验证。结果 共筛选出224篇文献,包含方剂133首,中药188味。发现18味使用超过25次的高频药物;清热类、补虚类的药物应用较多;药物性味以寒及苦为主;归经之中以肝经占比最高;进一步关联分析得到高频药对14个;核心处方4个。网络药理学结果显示,共得到44个活性成分、200个药物靶点、1 287个疾病靶点、70个共有靶点、573条GO富集条目及136条KEGG通路,药物主要成分槲皮素、山奈酚、β-谷甾醇作用于雌激素受体、黄体酮受体等核心靶点,通过内分泌抵抗、雌激素等信号通路发挥治疗作用。分子对接结果显示药物主要活性成分与相应核心靶点具有较好的结合能力。结论 中药复方治疗CPP多为滋阴清热、补虚类药物,与药性寒,药味苦、甘,归肝、肾经的药物配伍使用。其中高频药对“知母-黄柏”通过多成分、多靶点调控内分泌抵抗、雌激素信号通路发挥治疗作用。

关键词: 中枢性性早熟, 数据挖掘, 网络药理学, 高频药对, 活性成分, 靶点

Abstract: Objective To explore the prescription rules and mechanism of traditional Chinese medicine(TCM) in the treatment of central precocious puberty(CPP)by using data mining,network pharmacology and molecular docking,so as to provide more evidence for clinical treatment.Methods Using the literature on the treatment of CPP with TCM compounds,which was retrieved from the databases of CNKI,Wanfang,VIP and other databases from the establishment of the database to October 2022 as the data sources.Excel 2021 was used to collect and summarize the commonly used TCM prescriptions for CPP,and conducted frequency analysis and association rules analysis of CPP by Excel 2021,SPSS Modeler 18.0,SPSS Statistics 25.0 and other software,so as to study the composition rule of prescriptions for CPP.On the basis of these results,network pharmacology method was used to screen out the active ingredients and action targets of high-frequency drugs,and then screen out the disease related targets to construct PPI network.Mechanism of drugs was clarified through GO and KEGG pathway enrichment analysis.Finally,the molecular docking of autodock Vina(Vina)platform was used to verify the results.Results A total of 244 documents met the search criteria,including 133 prescriptions and 188 traditional Chinese medicines.It had been found that 18 high-frequency Chinese medicines were used more than 25 times.The drugs mainly focused on clearing heat and supplementing deficiency.The medicinal flavors were mainly cold and bitter,which belonged to the liver channel.Further correlation analysis yielded 14 high-frequency drug pairs and 4 core prescriptions.The results of network pharmacological analysis showed that 44 active components,200 drug targets,1 287 disease corresponding targets,70 common targets,573 GO enrichment entries and 136 KEGG pathways targets were obtained.It has been found that the main components of the drugs,such as quercetin,kaempferol and β-sitosterol,act on the core targets of ESR1,PGR and play a therapeutic role through endocrine resistance and estrogen signaling pathways.Finally,molecular docking results showed that the main active ingredients of the drug had good binding ability with the corresponding core targets.Conclusions In the treatment of CPP,traditional Chinese medicine is mainly used types of nourish Yin,clear heat and replenish deficiency,which is compatible with the drugs with cold properties,bitter and pliant taste,and the liver and spleen channels.Among them,high-frequency drug pair “ZhiMu-HuangBai” play a therapeutic role in the regulation of endocrine resistance and estrogen signaling pathways through multi-components and multi-targets.

Key words: central precocious puberty, data mining, network pharmacology, high-frequency drug pair, active ingredients, targets