Integrated network pharmacology, metabolomics and molecular docking analysis to reveal the mechanisms of quercetin in the treatment of hyperlipidemia.

Hyperlipidemia (HLP) is a significant contributor to cardiovascular diseases. Quercetin (QUE), a naturally occurring flavonoid with diverse bioactivities, has garnered attention due to its potential therapeutic effects. However, the precise mechanisms underlying the effects of QUE on HLP remain unclear. In this study, an ultra-high-performance liquid chromatography-quadrupole/electrostatic field Orbitrap high-resolution mass spectrometry (UPLC-Q-Exactive-MS) metabolomics strategy was employed to obtain metabolite profiles, and potential biomarkers were identified following data analysis. Network pharmacology and Drug Affinity Responsive Target Stability (DARTS) assays were utilized to explore the potential targets of QUE for HLP treatment. The results of metabolomics and network pharmacology were then integrated to identify the key targets and metabolic pathways involved in the therapeutic action of the QUE against HLP. Molecular docking and experimental validation were performed to confirm these key targets. A comprehensive database search identified 138 QUE-HLP-related targets. A protein-protein interaction (PPI) network was constructed using STRING, and the shared targets were filtered with Cytoscape. Among these, AKT1, TNF, VEGFA, mTOR, SREBP1, and SCD emerged as potential therapeutic targets. These findings were validated using in vitro cell experiments. Additionally, the mechanism of action of QUE against HLP was evaluated by integrating network pharmacology with metabolomics, identifying two metabolomic pathways crucial to HLP treatment. DARTS experiments confirmed the stable binding of QUE to FASN, p-mTOR, SREBP1, and p-AKT. In HepG2 cells treated with palmitic acid (PA), QUE significantly reduced the mRNA expression of ACLY, ACACA, FASN, and SCD (p < 0.05). Western blot analysis revealed that PA significantly increased protein expression of p-mTOR, SREBP1, FASN, and p-AKT (p < 0.05). In summary, our study provides novel insights into the protective mechanisms of QUE against HLP and offers valuable information regarding its potential benefits in clinical treatment.