[1]田颢颐,田耘.基于网络药理学方法探讨活血药治疗IgA肾病的作用机制[J].西部中医药,2026,39(01):87-95.[doi:10.12174/j.issn.2096-9600.2026.01.16]
　TIAN Haoyi,TIAN Yun.Network Pharmacology-based Exploration into the Mechanism of Blood-activating Drugs in the Treatment of IgA Nephropathy[J].Western Journal of Traditional Chinese Medicine,2026,39(01):87-95.[doi:10.12174/j.issn.2096-9600.2026.01.16]
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基于网络药理学方法探讨活血药治疗IgA肾病的作用机制()

《西部中医药》[ISSN:2096-9600/CN:62-1204/R]

卷:
39
期数:
2026年01期
页码:
87-95
栏目:
二次研究
出版日期:
2026-01-15

文章信息/Info

Title:
Network Pharmacology-based Exploration into the Mechanism of Blood-activating Drugs in the Treatment of IgA Nephropathy
作者:
田颢颐1, 田耘2
1.陕西中医药大学，陕西 西安 712046
2.陕西省中医医院，陕西 西安 710004
Author(s):
TIAN Haoyi1, TIAN Yun2
1.Shaanxi University of Chinese Medicine, Xi’an 712046, China
2.Shaanxi Provincial TCM Hospital, Xi’an 710004, China
关键词:
IgA肾病; 活血药; 网络药理学; 作用机制
Keywords:
IgA nephropathy; blood-activating drugs; network pharmacology; mechanism
分类号:
R289-03
DOI:
10.12174/j.issn.2096-9600.2026.01.16
文献标志码:
A
摘要:
目的基于网络药理学方法探讨活血药治疗IgA肾病的作用机制。 方法利用中药系统药理学数据库与分析平台，筛选并获取活血药的有效成分及其作用靶点。通过人类孟德尔遗传数据库、GeneCards数据库查找筛选IgA肾病相关靶点，运用Venn图，得到药物靶点及疾病靶点的共同靶点。运用STRING平台构建蛋白质-蛋白质互相作用（protein-protein interaction，PPI）网络，利用Metascape平台对其进行基因本体论（gene ontology，GO）、京都基因与基因组百科全书（Kyoto encyclopedia of genes and genomes，KEGG）功能富集分析。而后采用Cytoscape软件构建药物-活性成分-靶点-通路关系网络。 结果共筛选出活血药有效活性成分85个，预测其潜在靶点239个，筛选出IgA肾病疾病靶点667个。其中，活血药有效活性成分参与IgA肾病的靶点共82个。PPI网络模型中共包含82个节点，312条边，其中关键靶点有信号转导与转录激活因子3、肿瘤坏死因子、白细胞介素6、白细胞介素10、丝裂原活化蛋白激酶1、蛋白激酶B抗体和丝裂原活化蛋白激酶14。GO富集分析涉及生长因子受体结合通路、细胞因子受体结合通路、DNA-转录因子结合通路等。KEGG富集分析显示关键信号通路涉及糖尿病并发症中的AGE-RAGE信号通路、TNF信号通路、MAPK信号通路、白细胞介素17信号通路。 结论活血药可能通过多成分、多靶点、多通路对IgA肾病协同发挥作用。
Abstract:
ObjectiveTo discuss the mechanism of blood-activating drugs in the treatment of IgA nephropathy based on network pharmacology. MethodsTCMSP was utilized to screen and obtain the active ingredients of blood-activating drugs and its targets of action. IgA nephropathy related targets were searched and screened from Online Mendelian Inheritance in MaN (OMIM) and the GeneCards database of human genes, Venn diagram was used to obtain the shared targets between medicine and disease. PPI network was constructed using STRING platform, GO and KEGG functional enrichment analysis of the network were conducted using Metascape platform. Cytoscape was adopted to build medicine-active ingredients-targets-pathway network. ResultsThe study has identified 85 active ingredients from the drugs, predicted 239 potential targets of the drugs and 667 IgA nephropathy-related targets. Among which, there were 82 targets of active ingredients from blood-activating drugs involved in IgA nephropathy. PPI network model covered 82 nodes and 312 edges, and the key targets contained signal transduction and transcription activator 3, TNF, IL-6, IL-10, mitogen-activated protein kinase 1, protein kinase B antibody and mitogen-activated protein kinase 14. GO enrichment analysis involved growth factor receptor binding pathway, cytokine receptor binding pathway, DNA-transcription factor binding pathway. KEGG enrichment analysis displayed that the key signaling pathways were AGE-RAGE signaling pathway, TNF signaling pathway, MAPK signaling pathway and interleukin 17 signaling pathway of diabetic complications. ConclusionBlood-activating drugs could exert synergistic effects on IgA nephropathy possibly through multi-ingredient, multi-target and multi-pathway.

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备注/Memo

备注/Memo:
陕西省重点研发计划项目（2018ZDXM-SF-011）。田颢颐（1996—），女，硕士学位，医师。研究方向：肾病的基础与临床研究。
更新日期/Last Update: 2026-01-15