目的 通过重启随机游走（random walk with restart，RWR）算法解析都梁方成分群对偏头痛生物过程网络的影响，揭示都梁方成分群协同治疗偏头痛的作用机制。方法 结合文献和中药系统药理学数据库与分析平台（TCMSP）、生物信息学分析数据库（BATMAN-TCM）等数据库收集都梁方活性成分及对应靶点，并将成分划分为成分群；从人类基因数据库（Genecards）、功能基因集数据库（GSEA）等6个数据库中收集偏头痛相关基因，分别对都梁方成分群与偏头痛进行生物过程富集分析，通过Cytoscape 3.9.1软件将偏头痛相关生物过程进行聚类，初步分析都梁方成分群治疗偏头痛的协同作用；进一步整合RWR算法、Pearson相关性分析与Z得分显著性分析判断都梁方成分群与偏头痛生物过程之间的相关性与显著性，定量分析都梁方成分群协同治疗偏头痛的关键成分群、关键生物过程；基于定量分析结果构建PPI网络筛选关键成分群发挥协同作用的关键成分、关键靶点，并开展分子对接，以结合能大小为指标筛选核心成分、核心靶点。结果 都梁方中成分归属为6类成分群，偏头痛生物过程聚类为5类，都梁方治疗偏头痛的机制为香豆素类、生物碱类、有机酸类、苯酞类等4类关键成分群协同作用于4类生物过程，其显著性大小依次为对外源性刺激的反应＞炎症与免疫反应＞血液循环＞突触信号，分子对接筛选出6个核心成分（花椒毒酚、别异欧前胡素、川芎哚、绿原酸、欧前胡素、独活素）与7个核心靶点（MMP9、MMP2、SRC、EGFR、TNF、PTGS2、MTOR）。结论 从中医整体观念出发探讨都梁方成分群协同作用偏头痛生物过程的网络关联，有利于揭示都梁方治疗偏头痛的作用机制，为采用网络技术与机器学习解析中药复方药效作用机制提供新思路。

Objective To analyze the effect of Duliang Fang (都梁方) component group on the biological process network of migraine by random walk with restart (RWR) algorithm, reveal the mechanism of Duliang Fang component group in synergistic treatment of migraine. Methods Firstly, the active ingredients in Duliang Fang and the corresponding targets were collected from literature and databases such as Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine (BATMAN-TCM), and the components were grouped. Then, migraine-related genes were collected from six databases including the Human Gene Database (Genecards) and Gene Set Enrichment Analysis (GSEA), and biological process enrichment analysis of Duliang Fang component groups and migraine was conducted. Migraine-related biological processes were clustered using Cytoscape 3.9.1 software to preliminarily analyze the synergistic effect of Duliang Fang component groups in treating migraine. Furthermore, the correlation and significance between Duliang Fang component groups and migraine biological processes were determined using the RWR algorithm, Pearson correlation analysis, and Z-score significance analysis, quantitatively analyzing the key component groups and key biological processes of Duliang Fang synergistic therapy for migraine. Finally, based on the quantitative analysis results, a Protein-Protein Interaction (PPI) network was constructed to select key components and key targets for synergistic action of the component groups, and molecular docking was conducted to select core components and core targets based on the combination energy as the index. Results The components in Duliang Fang belong to six categories of component groups, while migraine biological processes cluster into five categories. The mechanism of Duliang Fang in treatment of migraine involves the synergistic action of four key component groups, namely coumarins, alkaloids, organic acids, and phenanthrenes, in four categories of biological processes. Their significance is ranked as follows: response to exogenous stimuli > inflammation and immune response > blood circulation > synaptic signaling. Molecular docking identified six core components (piperine, isobavachalcone, ligustilide, chlorogenic acid, psoralen, and dehydrocostus lactone) and seven core targets (MMP9, MMP2, SRC, EGFR, TNF, PTGS2 and MTOR). Conclusion Starting from the holistic concept of traditional Chinese medicine, this study explores the network correlations of the synergistic action of Duliang Fang component groups on migraine biological processes. This approach is beneficial for elucidating the mechanism of Duliang Fang in treating migraine, providing new insights for using network technology and machine learning to analyze the efficacy mechanism of traditional Chinese medicine compounds.

Q811.4;R285;TP18

成都中医药大学校院联合创新基金(LH202402042)