Elucidating the Mechanisms of Chrysanthemum Action on Atopic Dermatitis via Network Pharmacology and Machine Learning

Shiying Li, Yongxin Jiang, Chengxiang Hu, Yiyao Ding, Xueqi Fu, Shu Xing, Linlin Zeng

Chrysanthemum (Chrysanthemum morifolium Ramat.) has been recognized as both a food and medicinal substance in China since 2002 and possesses antioxidant, anti-inflammatory, antibacterial, and immunomodulatory activities. Previous studies suggest that Chrysanthemum may alleviate skin lesions resembling atopic dermatitis (AD); however, its underlying mechanisms remain unclear. In this study, we integrated network pharmacology and machine learning to systematically explore the potential mechanisms of Chrysanthemum in AD treatment. Four algorithms—Random Forest (RF), Lasso regression with cross-validation (LassoCV), Elastic Net (EN), and Extreme Gradient Boosting (XGB)—were compared, among which the XGB model achieved the best performance (accuracy = 0.9393). Further analysis identified 15 optimal features, two core targets (PTGS2 and MMP9), and one critical pathway (NF-κB signaling). To experimentally validate these findings, HaCaT keratinocytes were co-stimulated with TNF-α and IFN-γ to establish an in vitro inflammatory model, and co-treatment with three major flavonoids from Chrysanthemum—Acacetin, Diosmetin, and Chryseriol—significantly suppressed cytokine-induced COX-2 overexpression and reduced NF-κB p65 phosphorylation, confirming their inhibitory effects on NF-κB activation. These results were consistent with molecular docking and dynamics simulations, which demonstrated that these flavonoids, along with celecoxib, could stably bind to COX-2, thereby enhancing system stability and reducing residue fluctuations at the binding interface, revealing the molecular basis by which Chrysanthemum alleviates AD and supporting its modernization and therapeutic potential.