Mechanism of Action of Curcumin for Rheumatoid Arthritis Based on Machine Learning, Molecular Dynamics and Cellular Experiments

Abstract

<i>Objective</i>: Curcumin has been widely used in rheumatoid arthritis (RA) treatment and the previous study also proved its effectiveness. However, the pharmacological mechanism is still not clear. The current study intends to discuss the potential mechanism of action of curcumin in RA treatment through machine learning, network pharmacology, molecular dynamics and cellular experiments.<i>Methods</i>: RA-related microarray data were obtained from three GEO datasets: GSE55235, GSE55457 and GSE77298. Machine learning methods including XGBOOST, LASSO and SVM were adopted to screen out potential targets of RA pathogenesis. Online tools SwissTargetPrediction and Similarity ensemble approach were visited to predict potential targets of action of curcumin. The key target was identified via a Venn diagram and processed for molecular docking and molecular dynamics simulation with curcumin. Fibroblast-like synoviocytes (RA-FLSs) were selected to study the effect of curcumin at different concentrations (20, 40 and 80 μmol/L) on cell proliferation and apoptosis using MTT and flow cytometry assays. In addition, Western blot was used to examine the protein level.<i>Results</i>: Arachidonate 5-Lipoxygenase (ALOX5) was identified as a key target of RA following bioinformatics prediction. Results of molecular docking and molecular dynamics simulation demonstrated the tight binding between curcumin and ALOX5 with stable function. RA-FLSs intervened with different concentrations of curcumin (20, 40 and 80 mol/L) exhibited decreased potential in proliferation while increased apoptosis, which were in a dose-dependent manner. Additionally, with the increase of curcumin concentration, the protein level of ALOX5 gradually decreased. <i>Conclusion</i>: Curcumin may exert its therapeutic effects in RA treatment via down-regulating the expression of ALOX5.