Abstract
Hyperuricemia (HUA) is a major public health issue with a high prevalence worldwide. Wuling San (WLS) is an effective treatment for HUA. However, the active compounds and the related mechanism are unclear. In this study, we aimed to explore the active compounds and the underlying pharmacological mechanisms of WLS against HUA. First, a network pharmacology approach was used to detect active compounds of WLS, and potential targets and signaling pathways involved in the treatment of HUA were predicted. Then, a molecular docking strategy was used to predict the affinity between active compounds and key targets. Finally, to verify the prediction, the HUA rat model was established. 49 active compounds with 108 common targets were obtained. Besides, cerevisterol, luteolin, ergosterol peroxide, beta-sitosterol, and sitosterol were identified as key active compounds. In PPI analysis, TNF, IL6, CASP3, PPARG, STAT3, and other 12 core targets were obtained. GO enrichment analysis indicated that WLS was likely to interfere with oxidative stress in the treatment of HUA, and KEGG enrichment analysis indicated multiple inflammation-related signaling pathways possibly involved in the treatment of HUA by WLS, including TNF, and NOD-like receptor, HIF-1, PI3K-Akt, and IL-17 signaling pathways. The results of molecular docking indicated that the active compounds had good binding properties to their key targets. In the validation experiments, WLS significantly reduced the levels of serum uric acid (SUA) and serum malondialdehyde (MDA). Moreover, WLS not only significantly increased the levels of total antioxidant capacity (T-AOC) and superoxide dismutase (SOD), but also inhibited the expression of tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6). In the present study, we demonstrate that WLS has multicomponent, multitarget, and multi-pathway properties in the treatment of HUA. Its potential capability to reduce SUA could be ascribed to oxidative stress improvement and inflammation inhibition.
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