AI-driven determination of active compounds and investigation of multi-pharmacological effects of Chrysanthemi Flos

Background Chrysanthemi Flos as a medicine food homology species is widely used in the prevention and treatment of diseases, whereas comprehensive research of its active compounds related to multi-pharmacological effects remains limited. This study aimed to systematically explore the active compounds through artificial intelligence-based target prediction and activity evaluation. Methods The information on compounds in Chrysanthemi Flos was obtained from six cultivars containing Gongju, Chuju, Huaiju, Boju, Hangbaiju, and Fubaiju, using UPLC-Q-TOF/MS. The main differential metabolites in six cultivars were also screened through the PLS-DA model. Then the potential targets of differential compounds were predicted via the DrugBAN model. Enrichment and topological analysis of compound-target networks were performed to identify key pharmaceutical compounds. Subsequently, the pharmacological effects of predictively active compounds were confirmed in vitro . Based on the active compounds, the pharmacological activities of Chrysanthemi Flos from the six origins were also investigated and compared for the further evaluation of medicinal quality. Results A total of 155 secondary metabolites were obtained from Chrysanthemi Flos . Among them, 26 differential components were screened, and 9 key pharmacological compounds with 1141 targets were identified. Enrichment analysis indicated the main pharmacological effects of Chrysanthemi Flos related to inflammation, oxidative stress, and lipid metabolism. In addition, 9 key pharmaceutical compounds were evaluated in vitro experiments, indicating the significant therapeutic effect in regulating inflammation, oxidative stress, and lipid metabolism. Conclusion This study successfully identified 9 key pharmaceutical compounds in Chrysanthemi Flos and predicted the pharmacodynamic advantages of six origins. The findings would provide improved guidance for the discovery of active constituents and the assessment of pharmacodynamic advantages of different geographical origins.