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基于网络药理学探究玉屏风散增强免疫力的作用机制
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Abstract:
目的：基于网络药理学探讨玉屏风散增强免疫力的活性化合物及作用机制。方法：通过中药系统药理学数据库与分析平台(Traditional Chinese medicine systems pharmacology database and analysis platform, TCMSP)检索玉屏风散组方中黄芪、防风、白术的化学成分，设置筛选条件得到有效活性化合物及对应靶点，通过UniProt数据库对靶点进行标准化处理；通过GeneCards数据库和在线人类孟德尔遗传数据库(OMIM)检索与免疫相关的靶点并进行相应筛选；使用Venny2.1软件将药物靶点和与免疫相关的靶点导入，绘制韦恩图以获得交集靶点，使用Cytoscape3.9.1绘制“药物–疾病–活性化合物–靶点”交互关系网络图；将交集靶点导入String数据库，绘制蛋白相互作用(PPI)网络，并在Cytoscape3.9.1中对PPI网络进行优化处理以筛选出核心靶点；使用Metascape数据库对核心靶点进行GO功能和KEGG通路的富集分析，并在Bioinformatics平台上对分析结果进行可视化处理。结果：得到了44种玉屏风散的活性化合物和215种经统一标准化命名的靶点，免疫相关靶点7220个，交集靶点184个，核心靶点38个；GO分子功能(MF)有63个条目，GO生物学过程(BP)有1059个条目，GO细胞组分(CC)有34个条目。此外，KEGG Pathway富集分析确定了171条通路。结论：玉屏风散可能通过介导氧化应激反应、炎症反应，RNA聚合酶II转录调节，DNA结合转录因子结合等作用于IL-17、AGE-RAGE、PI3K-Akt信号通路，调控AKT1、TNF、IL6等靶点，发挥增强免疫力的作用。
Objective: Based on network pharmacology, this study aims to explore the active compounds and mechanisms of Yu Ping Feng San in enhancing immune function. Methods: The chemical components of Huang Qi, Fang Feng, and Bai Zhu in the formula of Yu Ping Feng San were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Filtering criteria were set to obtain effective active compounds and their corresponding targets. The targets were standardized using the UniProt database. Immune-related targets were retrieved from the Gene Cards database and the Online Mendelian Inheritance in Man database (OMIM), and corresponding screening was performed. The drug targets and immune-related targets were imported into Venny2.1 software to obtain the intersection targets, and the “drug-disease-active compound-target” interaction network was visualized using Cytoscape3.9.1. The intersection targets were imported into the STRING database to construct a protein-protein interaction (PPI) network, and the PPI network was optimized using Cytoscape3.9.1 to screen for core targets. The core targets were subjected to enrichment analysis of Gene Ontology (GO) functions and KEGG pathways using the Metascape database, and the analysis results were visualized using the Bioinformatics platform. Results: A total of 44 active compounds of Yu Ping Feng San and 215 targets with standardized names were obtained. Among them, there were 7220 immune-related targets, 184 intersection targets, and 38 core targets. GO analysis showed 63 entries for molecular function (MF), 1059 entries for
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