Background: Atherosclerosis (AS) is a chronic inflammatory vascular disease, and its progression is closely associated with immune dysregulation and lipid metabolic disorders. Natural active compounds, as multi-target therapeutic agents, have shown promising potential in the prevention and treatment of cardiovascular diseases. Tiliroside (Tle), a natural flavonoid with anti-inflammatory and antioxidant properties, exhibits potential therapeutic effects against AS; however, its molecular mechanisms remain poorly understood. Methods: In this study, we employed an integrated strategy combining animal models, transcriptomic data mining, target prediction, molecular docking, molecular dynamics simulations, single-cell transcriptomic analysis, and multiple machine learning algorithms to systematically identify and validate the key targets of Tle. Both in vivo and in vitro experiments were conducted to explore its underlying mechanisms in AS intervention. Results: Tle significantly attenuated atherosclerotic lesion development in ApoE⁻/⁻ mice, reduced lipid accumulation and inflammatory cytokine expression, and exhibited favorable safety. Multi-omics integration identified spleen tyrosine kinase (SYK) as a potential core target. Molecular simulations revealed that Tle binds stably to SYK, effectively inhibiting its phosphorylation, promoting cholesterol efflux, and suppressing foam cell formation and inflammatory responses. Single-cell analysis further demonstrated that SYK is predominantly expressed in macrophages within AS tissues. Functional experiments confirmed that SYK plays a key mediating role in the atheroprotective effects of Tle. Conclusion: This study systematically elucidates the critical role of SYK in the pathogenesis of AS and, for the first time, proposes and validates the “Tle–SYK–Macrophage” regulatory axis. These findings reveal the dual regulatory role of Tle in modulating immune and metabolic pathways to alleviate AS, providing new insights and potential targets for natural product-based therapeutic strategies.
Li et al. (Thu,) studied this question.