Network pharmacology-based strategy to investigate pharmacological mechanisms of wolfberry fruit for the treatment of chronic kidney disease
Description
Figure1. Workflow of network pharmacology analysis. Figure2. The pharmacology networks of fructuslycii (blue rhombus) which connect target genes (green ellipses) and compounds (yellow rectangles). Figure3. Linkage of target compounds and target genes. (A) There were 940 genes related to CKD based on search engine results from gene databases, and 39 overlapping genes were identified by comparing the mentioned genes with disease-associated genes. (B) This network has 60 nodes (39 target genes and 19 chemicals) and 122 edges. Figure4. KEGG pathway and GO analysis by DAVID database. (A) GO analysis of candidate targets. (B) KEGG pathways of target genes. Figure5. Protein-protein interaction (PPI) networks of active ingredients of ELB for the treatment of CKD. (A) Each node represents the relevant gene, the edge means line thickness indicates the strength of data support. (B) Center top 20 genes in the PPI network, the longer the strip, the higher the score. Figure6. Effect of ELB on renal function in 5/6 Nx rats. (A) Hematoxylin and Eosin (HE) staining of renal sections of rats with 5/6 Nx. (B) Changes in the levels of serum creatinine (SCr) and blood urea nitrogen (BUN) in 5/6 Nx rats. Values are mean ± SD (n=6); *P<0.05, comparing 5/6Nx with control. #P<0.05, comparing 5/6 Nx + ELB with 5/6 Nx Figure7. Effects of ELB on the levels of IL6 and VEGF. (∗p < 0.05 and ∗∗ p < 0.01 compared with the sham group; #p < 0.05 and ##p < 0.01 compared with the 5/6Nx group). Table1. A list of the final selected compounds in the fruits of L. barbarum for network analysis Table 2. Potential target genes associated compounds Table 3. Functions of potential target genes based on KEGG pathway analysis