基于网络药理学和分子对接技术研究桂枝治疗肾病综合征的机制。

OBJECTIVE: Nephrotic syndrome (NS) is a common glomerular disease caused by a variety of causes and is the second most common kidney disease. Guizhi is the key drug of Wulingsan in the treatment of NS. However, the action mechanism remains unclear. In this study, network pharmacology and molecular docking were used to explore the underlying molecular mechanism of Guizhi in treating NS. METHODS: The active components and targets of Guizhi were screened by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Hitpick, SEA, and Swiss Target Prediction database. The targets related to NS were obtained from the DisGeNET, GeneCards, and OMIM database, and the intersected targets were obtained by Venny2.1.0. Then, active component-target network was constructed using Cytoscape software. And the protein-protein interaction (PPI) network was drawn through the String database and Cytoscape software. Next, Gene Ontology (GO) and pathway enrichment analyses of Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by DAVID database. And overall network was constructed through Cytoscape. Finally, molecular docking was conducted using Autodock Vina. RESULTS: According to the screening criteria, a total of 8 active compounds and 317 potential targets of Guizhi were chosen. Through the online database, 2125 NS-related targets were identified, and 93 overlapping targets were obtained. In active component-target network, beta-sitosterol, sitosterol, cinnamaldehyde, and peroxyergosterol were the important active components. In PPI network, VEGFA, MAPK3, SRC, PTGS2, and MAPK8 were the core targets. GO and KEGG analyses showed that the main pathways of Guizhi in treating NS involved VEGF, Toll-like receptor, and MAPK signaling pathway. In molecular docking, the active compounds of Guizhi had good affinity with the core targets. CONCLUSIONS: In this study, we preliminarily predicted the main active components, targets, and signaling pathways of Guizhi to treat NS, which could provide new ideas for further research on the protective mechanism and clinical application of Guizhi against NS.

目的：肾病综合征（NS）是一种常见的肾小球疾病，由多种原因引起，是第二大常见的肾脏疾病。桂枝是治疗 NS 的五苓散的关键药物。然而，其作用机制尚不清楚。本研究采用网络药理学和分子对接技术探讨桂枝治疗 NS 的潜在分子机制。

方法：通过中药系统药理学数据库和分析平台（TCMSP）、Hitpick、SEA 和 Swiss Target Prediction 数据库筛选桂枝的活性成分和靶点。从 DisGeNET、GeneCards 和 OMIM 数据库中获取与 NS 相关的靶点，并通过 Venny2.1.0 获得交集靶点。然后，使用 Cytoscape 软件构建活性成分-靶点网络。通过 String 数据库和 Cytoscape 软件绘制蛋白质-蛋白质相互作用（PPI）网络。接下来，通过 DAVID 数据库进行基因本体（GO）和京都基因与基因组百科全书（KEGG）富集分析。并通过 Cytoscape 构建整体网络。最后，使用 Autodock Vina 进行分子对接。

结果：根据筛选标准，共选择了 8 种活性化合物和 317 个潜在的桂枝靶点。通过在线数据库，共确定了 2125 个 NS 相关靶点，获得了 93 个重叠靶点。在活性成分-靶点网络中，β-谷甾醇、谷甾醇、肉桂醛和过氧麦角甾醇是重要的活性成分。在 PPI 网络中，VEGFA、MAPK3、SRC、PTGS2 和 MAPK8 是核心靶点。GO 和 KEGG 分析表明，桂枝治疗 NS 的主要途径涉及 VEGF、Toll 样受体和 MAPK 信号通路。在分子对接中，桂枝的活性化合物与核心靶点具有良好的亲和力。

结论：本研究初步预测了桂枝治疗 NS 的主要活性成分、靶点和信号通路，可为进一步研究桂枝对 NS 的保护机制和临床应用提供新的思路。