%0 Journal Article %T 加味当归补血汤干预糖尿病肾病的网络药理学研究
Network Pharmacological Study on the Intervention of Modified Danggui Buxue Decoction in Diabetic Kidney Disease %A 靳锐 %A 周福荣 %A 包芸 %J Traditional Chinese Medicine %P 2191-2199 %@ 2166-6059 %D 2025 %I Hans Publishing %R 10.12677/tcm.2025.145326 %X 目的：通过网络药理学预测加味当归补血汤抗糖尿病肾病(diabetic kidney disease, DKD)的关键靶点与信号通路。方法：从TCMSP数据库筛选出加味当归补血汤(黄芪、当归、丹参、牡丹皮)有效成分及作用靶点，从GeneCards、OMIM、TTD数据库筛选出DKD疾病靶点，二者取交集得到成分–疾病交集靶点，再经过STRING数据库建立PPI网络，Cytoscape 3.10.1软件可视化预测关键靶点及通路，再利用DAVID生物信息数据库进行GO和KEGG通路富集分析，并使用微生信在线网站绘制气泡图展示富集分析结果。结果：筛选出关键靶点28个，有p53、TNF、JUN、IL6、MAPK1、Sirt1等。GO和KEGG预测出加味当归补血汤的关键信号通路有p53与Sirt1相关信号通路等。结论：加味当归补血汤包含多种活性成分及靶点，能够通过p53、Sirt1等多条氧化应激、炎症、凋亡及纤维化通路，协同干预DKD的发生及发展。
Objective: To predict key targets and signaling pathways of Modified Danggui Buxue Decoction against diabetic kidney disease (DKD) through network pharmacology. Methods: Active components and targets of Modified Danggui Buxue Decoction (Astragalus, Angelica, Salvia, Moutan Cortex) were screened from the TCMSP database. Disease targets of DKD were obtained from GeneCards, OMIM, and TTD databases. Intersection targets between components and diseases were identified. A PPI network was constructed using the STRING database and visualized via Cytoscape 3.10.1 to predict key targets and pathways. GO and KEGG pathway enrichment analyses were performed using the DAVID database, with results displayed as bubble plots via the microbioinformatics online platform. Results: Twenty-eight key targets were identified, including p53, TNF, JUN, IL6, MAPK1, and Sirt1. GO and KEGG analyses revealed critical pathways such as p53 and Sirt1-related signaling pathways. Conclusion: Modified Danggui Buxue Decoction contains multiple active components and targets, exerting synergistic effects against DKD progression through oxidative stress, inflammation, apoptosis, and fibrosis pathways involving p53, Sirt1, and others. %K 当归补血汤， %K 糖尿病肾病， %K p53， %K Sirt1， %K 网络药理学
Danggui Buxue Decoction %K Diabetic Kidney Disease %K p53 %K Sirt1 %K Network Pharmacology %U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=115543