Combining Network Pharmacology, Machine Learning, Molecular Docking, and Experimental Validation to Explore the...

Danggui-Shaoyao-San (DSS) demonstrates clinical efficacy in rheumatoid arthritis (RA), but its bioactive constituents and molecular mechanisms remain insufficiently characterized.

To elucidate the synergistic mechanisms of DSS in treating RA by integrating network pharmacology, machine learning, molecular docking, and dynamics simulations to identify core bioactive compounds and targets, followed by experimental validation of therapeutic efficacy.

Active compounds and targets of DSS were retrieved from TCMSP and UniProt databases, supplemented by SwissTargetPrediction and TCMIP. In GeneCards, DrugBank, and OMIM, RA-related genes were curated. Cytoscape 3.10. 3 and STRING were used to create compound-target and protein-protein interaction (PPI) networks. The prioritization of core targets was done using topological analysis and tested by molecular docking and molecular dynamics simulations. The in vivo impact of DSS was tested on the CIA model. HE staining measured synovitis, cartilage erosion, and bone erosion. ELISA was used to measure serum levels of TNF-α, IL-1β, IL-6, IL-8, MMP-1, and MMP-3.

We identified 45 bioactive compounds in DSS at work with 913 possible targets. Bioinformatics analysis showed that there were 2,484 targets that are RA-integrated, with 410 overlapping targets. TP53 and SRC came up as regulatory nodes. The results of molecular docking showed high affinity of binding between TP53/SRC and four major DSS compounds: alisol C, myricanone, mandenol, and kaempferol. Complex stability was confirmed by molecular dynamics simulations. DSS in the animal category made a significant reduction in the severity scores of arthritis, as well as reducing the paw swelling, as opposed to their counterparts in the model group. The histopathology proved that there was attenuated inflammation in the synovium and cartilage matrix conservation. The activity of pro-inflammatory mediators in serum was suppressed greatly.

The research has shown that a combination of computational-experimental approach can help to unravel the polypharmacology of a complicated traditional formula. The extension of our discoveries on the synergies of DSS core compounds selects active targets and states that the compounds have roles in common pathways of oncogenesis and metabolism. The paper offers a strong mechanistic background of clinical application of DSS and sets a template to modernize the old medicines.

DSS exerts anti-RA effects through synergistic interactions of alisol C, myricanone, kaempferol, and mandenol with core targets, modulating oncogenic, metabolic, and inflammatory pathways. This integrative strategy deciphers DSS's polypharmacology and provides a mechanistic foundation for clinical application.