Integrating Network Pharmacology and Metabolomics to Elucidate the Mechanism of Allopurinol in Hyperuricemia Treatment

This study integrated network pharmacology and metabolomics to investigate the mechanism of allopurinol in treating hyperuricemia (HUA). Therapeutic targets were identified by screening drug and disease databases. A drug-target-disease network was constructed and validated by molecular docking using Cytoscape. A mouse model of hyperuricemia was established with yeast extract and potassium oxonate. Allopurinol efficacy was evaluated via body weight, renal histopathology, and serum biochemical indices. Enrichment analyses of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed using DAVID platform. Serum metabolite profiles were analyzed by UPLC-Q-TOF/MS-based metabolomics, and metabolic pathways were explored using MetaboAnalyst 6.0. Network pharmacology and molecular docking identified 23 key targets and 43 signaling pathways related to allopurinol treatment. Animal experiments confirmed allopurinol significantly reduced serum levels of uric acid (UA), creatinine (CRE), blood urea nitrogen (BUN), and xanthine oxidase (XOD) activity. Metabolomic analysis revealed 5 differentially regulated metabolites and 13 key metabolic pathways associated with allopurinol intervention. The integrated results indicated that allopurinol treats hyperuricemia not only by modulating purine metabolism but also potentially through influencing oxidative stress and apoptosis-related pathways. This study provided preliminary experimental insights into the potential mechanistic basis of allopurinol in the treatment of hyperuricemia.