基于网络药理学与分子对接讨论肾炎方对肾小球肾炎的作用机制

Discussion on the Mechanism of Shenyan Formula in Treating Glomerulonephritis Based on Network Pharmacology and Molecular Docking

摘要: 目的：运用网络药理学与分子对接，研究肾炎方对早期肾小球肾炎(GN)的潜在作用机制。方法：在TCMSP数据库中提取五味药材活性成分，通过uniprot和SwissTargetPrediction数据库预测药物活性成分靶点，DrugBank、GeneCards、OMIM和TTD数据库收集GN疾病靶点，药物与疾病靶点取交集；利用STRING软件构建PPI网络，CytoNCA插件筛选核心靶点，Cytoscape软件进行“药物–活性成分–交集靶点–疾病”网络拓扑分析；R语言对交集靶点做GO和KEGG富集分析；AutoDock Vina软件做分子对接，PyMOL软件将结合模式可视化。结果：筛选到186个活性成分，预测到358个成分靶点，并与1157个疾病靶点取交集得到118个交集靶点；网络拓扑锁定IL6、TNF、STAT3、JUN等9个核心靶点以及排名前十位的核心成分；富集指向AGE-RAGE、TNF、IL-17等炎症信号。对接显示二氢丹参酮I对SRC亲和力最高(−9.9 kcal/mol)，槲皮素、山奈酚、木犀草素均以氢键锚定SRC，而二氢丹参酮I-TP53靠疏水接触稳定。讨论：肾炎方可能通过调控SRC/STAT3等核心靶点干预GN早期炎症反应，为后续实验验证提供方向。

Abstract: Objective: To investigate the potential mechanism of Shenyan Formula in the treatment of early glomerulonephritis (GN) using network pharmacology and molecular docking. Method: Active components of five medicinal materials were extracted from the TCMSP database. The drug active component targets were predicted through the uniprot and SwissTargetPrediction databases. The GN disease targets were collected from the DrugBank, GeneCards, OMIM and TTD databases, and the intersection of drug and disease targets was taken. The STRING software was used to construct the PPI network, and the CytoNCA plugin was used to screen the core targets. The “drug-active component-intersection target-disease” network topology analysis was performed using Cytoscape software. The R language was used to perform GO and KEGG enrichment analysis on the intersection targets. Molecular docking was performed using AutoDock Vina software, and the binding mode was visualized using PyMOL software. Results: 186 active components were screened, and 358 component targets were predicted. The intersection of these with 1157 disease targets yielded 118 intersection targets. Network topology identified 9 core targets including IL6, TNF, STAT3, and JUN, as well as the top ten core components. Enrichment analysis pointed to inflammatory signaling pathways, such as AGE-RAGE, TNF, and IL-17. Docking studies revealed that dihydrotanshinone I exhibited the highest affinity for SRC (−9.9 kcal/mol), while quercetin, kaempferol, and luteolin were anchored to SRC via hydrogen bonds, and dihydrotanshinone I-TP53 was stabilized by hydrophobic interactions. Discussion: The Nephritis Formula may intervene in the early inflammatory response of GN by regulating core targets such as SRC/STAT3, providing direction for subsequent experimental validation.