Abstract
Background: Ermiao San, one of the Chinese medicine formulas, has been widely used to treat rheumatoid arthritis (RA). Our previous study has demonstrated that Ermiao San is effective in treating RA. However, its pharmacological mechanisms remain unclear. Therefore, the purpose of this study was to decipher the potential mechanism of action of Ermiao San in rheumatoid arthritis (RA) by bioinformatics, network pharmacology, molecular docking, and molecular dynamics.
Methods: Gene expression data (GSE77298) were obtained from the GEO database. Differentially expressed genes (DEGs) were analyzed by R. The active ingredients of Huangbai (Phellodendron) and Cangshu (Atractylodes), two main constituents of Ermiao San, and their predicted target genes were retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) platform. Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the overlapping genes between DEGs of the RA dataset and the predicted target genes of Ermiao San. The gene-gene interaction network was analyzed and visualized by Cytoscape. Molecular docking and dynamics simulations were performed to study the interaction between selected target genes (Chemokine ligand 2 (CCL2) and matrix metalloproteinase 1 (MMP1)) and active ingredients (quercetin and wogonin) of Ermiao San.
Results: A total of 16 potential targets for Ermiao San were identified, with significantly enriched GO terms, such as cytokine-mediated signaling pathways, oxidoreductase activity, cell space, etc., and IL-17 signaling pathway, rheumatoid arthritis pathway, and NF-κB signaling pathway were identified as enriched pathways through KEGG analysis. CCL2 and MMP1 were identified and verified to be the targets of both quercetin and wogonin, the two active ingredients of Ermiao San, by molecular docking and molecular dynamics.
Conclusion: Ermiao San may target CCL2 and MMP1 via its active ingredients by exerting therapeutic effects on RA.
Keywords: Rheumatoid arthritis, molecular docking, molecular dynamics, Ermiao San, bioinformatics analysis, network pharmacology.
Graphical Abstract
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