Network pharmacology, molecular docking, molecular dynamics, and ADMET analysis of Curcuma caesia phytoconstituents...

Rheumatoid arthritis (RA) is a chronic, multifactorial autoimmune inflammatory disease that primarily affects joints, leading to stiffness, pain, and disability of joint function. Although therapeutic options like nonsteroidal anti-inflammatory drugs (NSAIDs) for pain management and disease-modifying anti-rheumatoid drugs (DMARDs) are available but are associated with several adverse effects. In this context, research and development efforts are felt necessary to develop safer and effective therapeutics. Herbal drugs employed in traditional medicine are claimed to be beneficial in the management of RA. Curcuma caesia is one such potential medicinal plant used by tribal communities in North-East India for the treatment of arthritis and deserves scientific investigation. Computational biology approaches were employed to unravel the possible modulatory effect of the pathology of RA by phytocompounds of Curcuma caesia using gene set enrichment analysis, network pharmacology, molecular docking, and molecular dynamics studies. STRING, KEGG pathway, PyRx ver. 0.8, DSV2021, and GROMACS were used to perform the study. The phytochemical composition of Curcuma caesia analysed by HPTLC fingerprinting and LC-MS. The findings of the present study predicted anti-inflammatory and antirheumatic arthritis potential of aerugidiol and confertin bioactives from Curcuma caesia by targetting IL6, TNF, and PTGS2, and modulating IL-17, TNF, NF-Kappa B, T cell receptor signaling pathways, Neuroactive ligand interaction, & Arachidonic acid metabolism. LC-MS profiling of Curcuma caesia confirmed the presence of aerugidiol and confertin. Thus, the observations of the present study suggest the potential of C urcuma caesia bioactive compounds as promising antiarthritic candidates, warranting further experimental validation.

The online version contains supplementary material available at 10.1007/s40203-025-00454-x.