Beijing Key Lab for Immune-Mediated Inflammatory Diseases, Institute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing 100029, China.
Heilongjiang Academy of Chinese Medical Sciences, Harbin 150036, China.
Biomed Res Int. 2021 Feb 1;2021:6642584. doi: 10.1155/2021/6642584. eCollection 2021.
The mechanism of peach kernel-safflower in treating diabetic nephropathy (DN) was investigated using network pharmacology.
Network pharmacology methodology was applied to screen the effective compounds of peach kernel-safflower in the SymMap and TCMSP databases. Potential targets were then screened in the ETCM, SEA, and SymMap databases to construct a compound-target network. This was followed by screening of DN targets in OMIM, Gene, and GeneCards databases. The common targets of drugs and diseases were selected for analysis in the STRING database, and the results were imported into Cytoscape 3.8.0 to construct a protein-protein interaction network. Next, GO and KEGG enrichment analyses were performed. Finally, Schrödinger molecular docking verified the reliability of the results.
A total of 23 effective compounds and 794 potential targets resulted from our screening process. Quercetin and luteolin were identified as the main effective ingredients in peach kernel-safflower. Furthermore, five key targets (VEGFA, IL6, TNF, AKT1, and TP53), AGE-RAGE, fluid shear stress and atherosclerosis, IL-17, and HIF-1 signaling pathways may be involved in the treatment of DN using peach kernel-safflower.
This study embodies the complex network relationship of multicomponents, multitargets, and multipathways of peach kernel-safflower to treat DN and provides a basis for further research on its mechanism.
采用网络药理学方法研究桃仁红花治疗糖尿病肾病（DN）的作用机制。
在 SymMap 和 TCMSP 数据库中运用网络药理学方法筛选桃仁红花的有效化合物，然后在 ETCM、SEA 和 SymMap 数据库中筛选潜在靶点，构建化合物-靶点网络。接着在 OMIM、Gene 和 GeneCards 数据库中筛选 DN 靶点。在 STRING 数据库中对药物和疾病的共同靶点进行分析，并将结果导入 Cytoscape 3.8.0 构建蛋白-蛋白相互作用网络，然后进行 GO 和 KEGG 富集分析。最后，采用 Schrödinger 分子对接验证结果的可靠性。
通过筛选，共得到 23 个有效化合物和 794 个潜在靶点。槲皮素和木樨草素被鉴定为桃仁红花的主要有效成分。此外，VEGFA、IL6、TNF、AKT1 和 TP53 等 5 个关键靶点（VEGFA、IL6、TNF、AKT1 和 TP53）、AGE-RAGE、流体切应力和动脉粥样硬化、IL-17 和 HIF-1 信号通路可能参与了桃仁红花治疗 DN 的作用。
本研究体现了桃仁红花多成分、多靶点、多途径治疗 DN 的复杂网络关系，为进一步研究其作用机制提供了依据。
