AIM: The renal protective mechanisms of Shenyuan particle (SYP) in the treatment of diabetic kidney disease (DKD) were investigated, focusing on the main targets and pathways. MATERIALS AND METHODS: In this study, the potential targets of compounds identified in SYP were predicted by Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and a "herb-compound-target" network was constructed via Cytoscape. Next, the Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were dissected using R language. A protein-protein interaction network was fabricated using STRING to obtain the main target information. In addition, db/db mice were used as the DKD models to explore the renal protective effects of SYP. Transmission electron microscopy, western blot, pathological staining, TUNEL staining, and biochemical methods were used to identify the apoptotic pathways and establish the primary mechanism of SYP. RESULTS: Network pharmacology analysis revealed 67 potential targets based on the analysis of different databases. The targets of SYP were primarily associated with apoptosis. The network hub genes included caspase 3, caspase 7, caspase 8, caspase 9, Bax, and Bcl-2. In vivo, SYP materially improved renal function and inhibited apoptosis in the db/db mouse kidneys by improving the mitochondrial health. In addition, our results showed that SYP significantly decreased the expression of Bax, caspase 3, and Cyto-c and increased the expression of Bcl-2. CONCLUSIONS: Network pharmacology analysis and experimental results suggest that SYP ameliorates DKD mediated via multiple components, targets, and pathways. Our study further demonstrates that SYP inhibits apoptosis in the kidneys of db/db mice by improving the mitochondrial health and thereby alleviating renal damage.
Renal Protective Mechanisms of Shenyuan Particle in Db/Db Mice: A Study Based on Network Pharmacology.
神元颗粒对Db/Db小鼠肾脏的保护机制:基于网络药理学的研究
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作者:Zhu Guoshuang, Wang Lan, Wu Zenan, Qiu Mingliang, Ke Shiwen, Liu Liangji, Wang Xiaoqin
| 期刊: | Evidence-Based Complementary and Alternative Medicine | 影响因子: | 0.000 |
| 时间: | 2022 | 起止号: | 2022 Jun 14; 2022:9579179 |
| doi: | 10.1155/2022/9579179 | ||
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