[1]王嘉宁,王健.基于数据挖掘和网络药理学方法探讨惊恐障碍的中药治疗机制[J].西部中医药,2026,39(01):107-114.[doi:10.12174/j.issn.2096-9600.2026.01.18]
　WANG Jia?ning,WANG Jian.Mechanism of TCM Treatment for Panic Disorder Based on Data Mining and Network Pharmacology[J].Western Journal of Traditional Chinese Medicine,2026,39(01):107-114.[doi:10.12174/j.issn.2096-9600.2026.01.18]
点击复制

基于数据挖掘和网络药理学方法探讨惊恐障碍的中药治疗机制()

《西部中医药》[ISSN:2096-9600/CN:62-1204/R]

卷:
39
期数:
2026年01期
页码:
107-114
栏目:
二次研究
出版日期:
2026-01-15

文章信息/Info

Title:
Mechanism of TCM Treatment for Panic Disorder Based on Data Mining and Network Pharmacology
作者:
王嘉宁, 王健
中国中医科学院广安门医院，北京 100053
Author(s):
WANG Jia?ning, WANG Jian
Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
关键词:
惊恐障碍; 奔豚; 数据挖掘; 网络药理学; 药理机制
Keywords:
panic disorder; syndrome; data mining; network pharmacology; pharmacological mechanism
分类号:
R257
DOI:
10.12174/j.issn.2096-9600.2026.01.18
文献标志码:
A
摘要:
目的基于数据挖掘和网络药理学方法探讨中药治疗惊恐障碍（中医病名奔豚）的核心组方及作用机制。 方法使用SPSS 26.0软件，将古籍中治疗奔豚相关处方进行药物频次及关联、聚类、因子分析等，获取用药规律及核心组方，运用中药系统药理学数据库与分析平台、GeneCards等数据库分析核心组方，分别得到相关成分靶点并取交集，利用Cytoscape 3.8.0和STRING数据库分别构建网络，并进行基因本体功能富集分析和京都基因与基因组百科全书通路富集分析，最终选取核心成分和核心靶点；应用autodock vina 1.5.7进行分子对接并绘制热图。 结果数据挖掘共得到方剂65首，涉及中药65味；通过药物关联、聚类和因子分析得到核心组方为桂枝、半夏、小茴香、木香。共获得核心组方有效成分24种，靶点87个，交集基因43个，核心成分包括雌激素受体α1、FOS蛋白、过氧化氢酶、钠依赖性多巴胺转运体、胺氧化酶、血管内皮生长因子A、多巴胺受体、钠依赖性5-羟色胺转运体等；基因本体功能富集分析包括血清素受体信号通路等；京都基因与基因组百科全书通路富集分析包括神经配体-受体相互作用等；分子对接结果显示有较好结合性能。 结论通过数据挖掘得出桂枝、半夏、木香、小茴香等为治疗奔豚最常用的药物，其核心成分β-谷甾醇、儿茶素等，通过作用于雌激素受体α1、FOS蛋白等治疗惊恐障碍。
Abstract:
ObjectiveTo discuss the core prescriptions of treating Bentun syndrome (TCM disease: rushing piglet syndrome) and the mechanism using data mining and network pharmacology. MethodsSPSS 26.0 software was employed to conduct drug frequency, association rules, cluster analysis and factor analysis of the prescriptions related to Bentun syndrome in the ancient books, to obtain medication patterns and core prescriptions, the core prescriptions were analyzed using TCMSP and GeneCards, to obtain the targets of the related ingredients and the intersection respectively, the network was built using Cytoscape 3.8.0 and STRING databases respectively, to conduct GO and KEGG pathway enrichment analysis, consequently, to select the core ingredients and core targets, autodock vina 1.5.7 was applied to perform molecular docking and to draw the heatmap. ResultsA total of 65 prescriptions were gained by data mining, involving 65 herbs; the core prescription were Guizhi (Cinnamomum cassia Presl), Banxia (Pinelliae rhizoma), Xiaohuixiang (Foeniculi fructus) and Muxiang(Aucklandiae radix) through the application of drug association, cluster analysis and factor analysis. The study identified 24 active ingredients of the core prescriptions, 87 targets and 43 intersecting genes, and the core ingredients contained estrogen receptor α1, FOS protein, catalase, and sodium-dependent dopamine transporter, monoamine oxidase, vascular endothelial growth factor A (VEGF-A), dopamine receptor (DR), sodium-dependent serotonin transporter and others; GO enrichment analysis covered seronine receptor signaling pathway; KEGG enrichment analysis contained ligand-receptor interaction; molecular docking results exhibited better binding ability. ConclusionData mining results revealed that Guizhi, Banxia, Muxiang and Xiaohuixiang are commonly used in the treatment of Bentun syndrome, and their core ingredients such as β-Sitosterol, catechin and others, could treat panic disorder by acting on estrogen receptor α1 and FOS protein.

备注/Memo

备注/Memo:
中国中医科学院科技创新工程（CI2021A03102）；首都卫生发展科研专项项目（首发2020-1-2121）。王嘉宁（1995—），女，硕士学位。研究方向：中西医结合防治精神心理疾病。
更新日期/Last Update: 2026-01-15