Drug Design, Development and Therapy (Jun 2022)
Network Pharmacology Analysis and Experimental Validation to Investigate the Mechanism of Total Flavonoids of Rhizoma Drynariae in Treating Rheumatoid Arthritis
Abstract
Guang-yao Chen,1,* Jing Luo,2,3,* Yi Liu,4,* Xin-bo Yu,1 Xiao-yu Liu,5 Qing-wen Tao2,3 1Graduate School, Beijing University of Chinese Medicine, Beijing, 100029, People’s Republic of China; 2Department of TCM Rheumatology, China-Japan Friendship Hospital, Beijing, 100029, People’s Republic of China; 3Beijing Key Lab for Immune-Mediated Inflammatory Diseases, China-Japan Friendship Hospital, Beijing, 100029, People’s Republic of China; 4Humanities School, Beijing University of Chinese Medicine, Beijing, 100029, People’s Republic of China; 5School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, 100029, People’s Republic of China*These authors contributed equally to this workCorrespondence: Qing-wen Tao, Department of TCM Rheumatology, China-Japan Friendship Hospital, Beijing, People’s Republic of China, Tel +8613910528490, Email [email protected]: The study aimed to explore the mechanism of total flavonoids of Rhizoma Drynariae (TFRD) in the treatment of rheumatoid arthritis (RA) based on network pharmacology and experimental validation.Methods: The active components of TFRD were identified from TCMSP and TCMID databases. Relevant targets of the active compounds of TFRD and RA-related targets were predicted by public databases online. A component-target (C-T) regulatory network was constructed by Cytoscape. The genes of TFRD regulating RA were imported into STRING database to construct a protein-protein interaction (PPI) network in order to predict the key targets. KEGG enrichment analysis was performed to predict the crucial mechanism of TFRD against RA. The active components of TFRD underwent molecular docking with the key proteins. Collagen-induced arthritis (CIA) model of rats and inflammatory factors-stimulated fibroblast-like synoviocytes were used in vivo and in vitro to validate the efficacy and predicted critical mechanisms of TFRD.Results: Network Pharmacology analysis revealed that TFRD had 14 active compounds, corresponding to 213 targets, and RA related to 2814 genes. There were 137 intersection genes between TFRD and RA. KEGG indicated that therapeutic effects of TFRD on RA involves T cell receptor signaling pathway, Th17 cell differentiation, IL-17 signaling pathway, TNF signaling pathway, MAPK signaling pathway and PI3K/AKT signaling pathway. In vivo experiments suggested TFRD can alleviate the inflammatory response, joint swelling and synovial abnormality of CIA rats. TFRD contributed to the decrease of Th17 cells and the down-regulated secretion of IL-17A and TNF-α of activated lymphocyte in CIA model. In vitro experiments confirmed TFRD can effectively inhibit the inflammatory response of fibroblast-like synoviocytes and suppress the abnormal activation of MAPK, PI3K/AKT and NFκB signaling pathways.Conclusion: The treatment of RA with TFRD is closely related to inhibiting Th17 differentiation and inflammatory response of synoviocytes.Keywords: total flavonoids of Rhizoma Drynariae, Rheumatoid arthritis, network pharmacology, T cell differentiation, inflammatory response
