Exploring the mechanism of Danggui Niantong Decoction in the treatment of rheumatoid arthritis based on network pharmacology, Mendelian randomization, molecular docking and molecular dynamics simulation

Given the increasing incidence and disability rate of rheumatoid arthritis (RA) year by year, RA has become a common cause of disability. Danggui Niantong Decoction (DGNTD) has been shown to have therapeutic effects on RA. However, to date, its bioactive components and potential targets remain unclear. To systematically explore the potential mechanisms of DGNTD in the treatment of RA, we utilized a combination of network pharmacology, Mendelian randomization, molecular docking, and molecular dynamics simulation. We used the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database to identify DGNTD's active ingredients and potential targets, and GeneCards to screen RA-related targets. Common targets were identified via Venn analysis. We built a protein-protein interaction network and a drug-ingredient-target map with Cytoscape. Based on shared targets, we conducted gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses to reveal key pathways. To validate results, we used R for Mendelian randomization to assess core targets' correlation with RA. We used Autodock for molecular docking and GROMACS for dynamics simulations to verify complex stability. DGNTD contains 316 active ingredients and 276 potential targets. Through protein-protein interaction network analysis and drug-ingredient-target network screening, we identified 215 active ingredients and 200 common targets, with quercetin and naringenin as core active ingredients. The core targets included RAC-alpha serine/threonine-protein kinase, cellular tumor antigen p53, signal transducer and activator of transcription 3, mitogen-activated protein kinase 1, mitogen-activated protein kinase 3, and Myc proto-oncogene protein. The Kyoto encyclopedia of genes and genomes and gene ontology enrichment analyses revealed 186 signaling pathways, with core targets mainly involving the PI3K/AKT pathway, lipid metabolism, and atherosclerosis-related biological processes. After validation through Mendelian randomization, RAC-alpha serine/threonine-protein kinase and mitogen-activated protein kinase 3 may be key targets for the treatment of RA by DGNTD. The molecular docking and dynamics simulations showed that the complexes formed by the core active ingredients and key targets exhibited strong stability. DGNTD exerts its therapeutic effects on RA through the synergistic action of multiple components, targets, and pathways, with its anti-inflammatory effects and potential molecular mechanisms being particularly noteworthy and warranting further investigation.