Integrating network pharmacology, molecular docking and experimental verification to explore the therapeutic effect of piceatannol on rheumatoid arthritis.

OBJECTIVE

Piceatannol (PIC) exhibits antioxidant and anti-inflammatory activities. This study integrates network pharmacology and experimental validation to investigate its potential role in rheumatoid arthritis (RA).

METHODS

PIC targets were predicted using public databases. RA-related differentially expressed genes (DEGs) were identified from Gene Expression Omnibus (GEO) datasets (|logFC| ≥ 1 and P-value < 0.05). Intersection genes were analyzed via protein-protein interaction (PPI) network (hub gene selection), molecular docking (binding affinity < -5.0 kcal/mol as threshold), ConnectivityMap and molecular dynamics simulation. Experimental validation included CCK8, flow cytometry, real-time quantitative PCR (RT-qPCR), Western blotting, and an adjuvant-induced arthritis (AIA) rat model.

RESULTS

35 intersecting genes were identified, from which 6 hub genes (SYK, CXCL8, TNF, NFKB1, PPARG, and CASP8) were selected. PIC showed stable binding to all hub genes (affinities: -5.6 to -7.8 kcal/mol). ConnectivityMap suggested a regulatory relationship between PIC and SYK. Molecular dynamics simulations demonstrate that the PIC-SYK complex maintains stable structural integrity. Experimental validation showed that PIC reduced MH7A cell viability, induced G2/M arrest and apoptosis, and downregulated mRNA levels of SYK, NFKB1, and CASP8, consistent with predictions. In vivo, PIC alleviated AIA severity.

CONCLUSION

These preliminary findings suggest that PIC exerts therapeutic effects in RA models, potentially via SYK/NFKB1/CASP8. The study provides a theoretical basis for further evaluation of PIC in RA, while acknowledging the exploratory nature of network pharmacology and preclinical models.