【摘要】 目的 基于网络药理学探讨紫苏子—杏仁药对治疗咳嗽变异性哮喘(CVA)的潜在分子作用靶点及机制。方法 采用中药系统药理学数据库和分析平台(TCMSP)数据库对紫苏子—杏仁药对的有效活性成分进行筛选，并采用SwissTargetPrediction网站进行靶点预测。采用GeneCards数据库检索CVA相关靶点，借助Venny 2.1.0获取交集靶点，对交集靶点分别运用Cytoscape 3.9.1软件和STRING数据库构建主要活性成分—潜在治疗靶基因网络图和PPI蛋白互作网络，并筛选出关键有效活性成分和核心靶蛋白，通过DAVID数据库对交集靶点进行GO功能及KEGG通路的富集分析。结果 筛选出紫苏子—杏仁药对有效成分19个，与CVA相关靶点224个，核心靶点为AKT1、IL-6、TP53、SRC、MAPK3、EGFR、JUN、PTGS2、HSP90AA1、ESR1。GO功能富集分析显示分子功能165个、细胞组分79个、生物过程630个。KEGG通路富集分析显示得到信号通路155条，主要涉及cAMP信号通路、PI3K-Akt信号通路、癌症通路、化学致癌—受体激活通路、神经活性配体—受体相互作用等。结论 紫苏子—杏仁药对可通过多成分、多靶点、多通路的协同作用抗CVA。更多还原

【Abstract】 Objective To explore the potential molecular targets and mechanism of the perilla seed-almond pairs for the treatment of cough variant asthma(CVA) based on network pharmacology. Methods The TCMSP database was used to screen the active ingredients of the perilla seed-almond pairs, and the SwissTargetPrediction website was used for target prediction. The GeneCards database was used to retrieve CVA-related targets, and the intersecting targets were obtained with the help of Venny 2.1.0, and Cytoscape 3.9.1 software and STRING database were used to construct the main active ingredient-potential therapeutic target gene network and PPI protein interaction network for the intersecting targets, and the key active ingredients and core target proteins were screened, DAVID database was used to enrich the GO function and KEGG pathway of the intersecting targets. Results A total of 19 active ingredients and 224 CVA-related targets were screened, and the core targets were AKT1, IL-6, TP53, SRC, MAPK3, EGFR, JUN, PTGS2, HSP90AA1, ESR1. There were 165 molecular functions, 79 cellular components and 630 biological processes GO function enrichment analysis. 155 signaling pathways were obtained from KEGG pathway enrichment analysis, mainly involving cAMP signaling pathway, PI3K-Akt signaling pathway, cancer pathway, chemoattractant-receptor activation pathway and neuroactive ligand-receptor interactions. Conclusion Perilla seed-almond pairs can be used against CVA through the synergistic effect of multi-component, multi-target and multi-pathway.更多还原