Systems Pharmacology, Molecular Modeling, and Molecular Dynamics Simulation Analyses Provide Insights into the Molecular Mechanism of Trianthema portulacastrum L. for the Treatment of Osteoarthritis

Osteoarthritis (OA), also referred to as degenerative joint disorder, is a common kind of arthritis that affects millions of people worldwide and is characterized by cartilage degradation in joints. Complementary alternative medicine has recently sparked interest due to the potential of bioactive phytochemicals to control molecular pathways with fewer side effects. This study utilized a network pharmacology (NP) approach to investigate the regulatory mechanisms of active constituents of Trianthema portulacastrum L. in treating OA. Active components were obtained from the indian medicinal plants, phytochemistry and therapeutics (IMPPAT) and KNApSAcK databases and the literature, while their related targets were obtained through the Swiss Target Prediction and STITCH databases. Additionally, OA-related targets were obtained from microarray datasets (GSE55235 and GSE55457) using the Gene Expression Omnibus. To annotate target proteins, the DAVID Gene Ontology database was utilized, while KEGG pathways were employed to analyze such signaling pathways in which potential targets are involved. The STRING database along with Cytoscape was utilized to establish protein–protein interaction networks, and CytoHubba’s degree centrality scoring was utilized to identify core genes. Molecular docking analysis was conducted using PyRx. The KEGG pathway and network analyses identified one gene named Jun proto-oncogene (JUN) as mainly involved in OA. Three active ingredients, namely quercetin, stigmasterol, and ecdysterone, were found to influence JUN expression and potentially act as therapeutic targets for OA. The three complexes (JUN_ecdysterone, JUN_quercetin, and JUN_stigmasterol) also revealed stable dynamics and showed no major conformational changes during the simulation time. These observations were validated in the simulation-based binding free energy analysis. The integrated NP and docking study suggested T. portulacastrum’s preventative effect on OA by targeting OA-relevant signaling pathways.