Network pharmacology uses bioinformatics to broaden our understanding of drug actions and thereby to advance drug discovery. Here we apply network pharmacology to generate testable hypotheses about the multi-target mechanism of celastrol against rheumatoid arthritis. We reconstructed drug-target pathways and networks to predict the likely protein targets of celastrol and the main interactions between those targets and the drug. Then we validated our predictions of four candidate targets (IKK-β, JNK, COX-2, MEK1) by performing docking studies with celastrol. The results suggest that celastrol acts against rheumatoid arthritis by regulating the function of several signaling proteins, including MMP-9, COX-2, c-Myc, TGF-β, c-JUN, JAK-1, JAK-3, IKK-β, SYK, MMP-3, JNK and MEK1, which regulate the functions of Th1 and Th2 cells, macrophages, fibroblasts and endothelial cells in rheumatoid arthritis. Celastrol is predicted to affect networks involved mainly in cancer, connective tissue disorders, organismal injury and abnormalities, tissue development, cell death and survival. This network pharmacology strategy may be useful for discovery of multi-target drugs against complex diseases.
Keywords: Celastrol; Docking; Ingenuity pathway analysis; Network pharmacology; Rheumatoid arthritis.
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