Combining network pharmacology and bioinformatics analysis to identify the molecular mechanisms of UDCA in the treatment of carotid atherosclerosis

Abstract

Ursodeoxycholic acid (UDCA) can be used to prevent atherosclerosis. However, the molecular mechanism of UDCA on carotid atherosclerosis is not known. A combination of bioinformatics, network pharmacology, and molecular docking was used to unravel the potential molecular mechanisms of UDCA in alleviating carotid atherosclerosis. The results of weighted gene co-expression network analysis (WGCNA) combined with differential expression analysis were used to screen for potent targets in carotid atherosclerosis. A typical target for UDCA in the treatment of carotid atherosclerosis was obtained by network pharmacology, and a protein-protein interaction network was constructed. Nine core targets were obtained using four algorithms of the cytoHubba plugin of Cytoscape 3.9.0, and molecular docking was completed using Autodock Vina 1.1.2. GO, and KEGG enrichment pathway analysis was performed based on the Metascape platform. The results showed that CD4, PTPRC, CCL5, MMP9, CD38, CASP1, CCR2, EGFR, and SYK were the targets of action of UDCA in the treatment of carotid atherosclerosis. The enrichment analysis results showed that these targets were significantly enriched in pathways associated with inflammation. In conclusion, this study highlights some of the molecular mechanisms of UDCA in the treatment of carotid atherosclerosis and provides a theoretical basis for future studies.