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Astragalus propinquus Schischkin and Panax notoginseng (A&amp;P) has been widely used in clinical practice to treat chronic kidney disease (CKD) for many years and achieved a remarkable improvement of these outcomes. However, its mechanisms for ameliorating CKD are still poorly obscure. In the current study, integrated network analysis was carried out to analyze the potential active ingredients and molecular mechanism of A&amp;P on CKD, and 39 active ingredients and a total of 570 targets were obtained. Furthermore, the potential disease-related genes were obtained from the NCBI GEO database by integrating 2 microarray datasets, and 24 significant genes were utilized for subsequent analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis displayed that pathways including cell oxidative stress and Akt signaling pathway are medicated by A&amp;P. Of note, Heat Shock Transcription Factor 1 (HSF1) and RELA Proto-Oncogene (RELA) were regarded as hub genes considering their central roles in the gene regulatory network. What’s more, the effect of A&amp;P and potential genes was furthermore verified by using unilateral ureteral ligation (UUO) in rodent model. The results showed that the expression of HSF1 and RELA both at transcript and protein level was significantly upregulated in UUO model, but the expression was markedly reversed after A&amp;P intervention. To further guide the interpretation of active ingredients from A&amp;P on the effect of HSF1 and RELA, we performed a molecular docking assay and the results showed that active ingredients such as coptisine docked well into HSF1 and RELA. In total, these results suggest that A&amp;P may improve RF in CKD by regulating HSF1 and RELA, which provides a basis for further understanding the mechanism of A&amp;P in the treatment of RF and CKD.

evidence-based complementary and alternative medicine

Exploring the Mechanism of Astragalus propinquus Schischkin and Panax Notoginseng (A&amp;P) Compounds in the Treatment of Renal Fibrosis and Chronic Kidney Disease Based on Integrated Network Analysis