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Herbal medicines usually contain a large group of chemical components, which may be transformed into more complex metabolites  in vivo . In this study, we proposed a knowledge-transmitting strategy for metabolites identification of compound formulas. Gegen-Qinlian Decoction (GQD) is a classical formula in traditional Chinese medicine (TCM). It is widely used to treat diarrhea and diabetes in clinical practice. However, only tens of metabolites could be detected using conventional approaches. To comprehensively identify the metabolites of GQD, a “compound to extract to formulation” strategy was established in this study. The metabolic pathways of single representative constituents in GQD were studied, and the metabolic rules were transmitted to chemically similar compounds in herbal extracts. After screening diversified metabolites from herb extracts, the knowledge was summarized to identify the metabolites of GQD. Tandem mass spectrometry (MS n ), fragment-based scan (NL, PRE), and selected reaction monitoring (SRM) were employed to identify, screen, and monitor the metabolites, respectively. Using this strategy, we detected 131 GQD metabolites (85 were newly generated) in rats biofluids. Among them, 112 metabolites could be detected when GQD was orally administered at a clinical dosage (12.5 g/kg). This strategy could be used for systematic metabolites identification of complex Chinese medicine formulas.

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Compound to Extract to Formulation: a knowledge-transmitting approach for metabolites identification of Gegen-Qinlian Decoction, a traditional Chinese medicine formula