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<p>To systematically characterize the chemical constituents and serum metabolites of Qijingmingmu decoction (QJMM) and to explore its potential anti-aging mechanisms using an integrated strategy combining UPLC-Q-TOF-MS and network pharmacology. The chemical components of QJMM were identified using UPLC-Q-TOF-MS. Rats were administered QJMM at different doses, and serum samples were collected for metabolite profiling. The absorbed prototype components and metabolites were analyzed. Potential targets of QJMM were predicted using public databases, and protein–protein interaction (PPI) analysis, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. A total of 66 compounds were identified in QJMM, and 38 metabolites were detected in rat serum, including both prototype compounds and their transformed products. Several representative metabolites, such as dihydroferulic acid 4-O-glucuronide, ferulic acid sulfate, and wedelolactone glucuronide, were identified as key in vivo components. Network pharmacology analysis suggested that QJMM may exert anti-aging effects by regulating multiple targets, including RELA, ESR1, TNF, and HSP90AB1, and modulating signaling pathways such as the NF-κB, TNF, and HIF-1 pathways. This study provides a preliminary characterization of the chemical and metabolic profiles of QJMM and offers insights into its potential multi-target mechanisms underlying anti-aging effects.</p>

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Integrated analysis of chemical components, serum metabolites, and anti-aging mechanisms of Qijingmingmu decoction for conjunctivochalasis based on UPLC-Q-TOF-MS and network pharmacology

  • 期刊论文

  • 发表日期：

    2026年5月22日

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  • KaiYu Yang,
  • QingSong Li

摘要

To systematically characterize the chemical constituents and serum metabolites of Qijingmingmu decoction (QJMM) and to explore its potential anti-aging mechanisms using an integrated strategy combining UPLC-Q-TOF-MS and network pharmacology. The chemical components of QJMM were identified using UPLC-Q-TOF-MS. Rats were administered QJMM at different doses, and serum samples were collected for metabolite profiling. The absorbed prototype components and metabolites were analyzed. Potential targets of QJMM were predicted using public databases, and protein–protein interaction (PPI) analysis, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. A total of 66 compounds were identified in QJMM, and 38 metabolites were detected in rat serum, including both prototype compounds and their transformed products. Several representative metabolites, such as dihydroferulic acid 4-O-glucuronide, ferulic acid sulfate, and wedelolactone glucuronide, were identified as key in vivo components. Network pharmacology analysis suggested that QJMM may exert anti-aging effects by regulating multiple targets, including RELA, ESR1, TNF, and HSP90AB1, and modulating signaling pathways such as the NF-κB, TNF, and HIF-1 pathways. This study provides a preliminary characterization of the chemical and metabolic profiles of QJMM and offers insights into its potential multi-target mechanisms underlying anti-aging effects.