A funnel-type stepwise filtering strategy for identification of potential Q-markers of traditional Chinese medicine formulas

Quality marker (Q-marker) serves as an important driver for the standardization of quality control in traditional Chinese medicine (TCM) formulas. However, it is still challenging to discover comprehensive and representative Q-markers. This study aimed to identify Q-markers of Hugan tablet (HGT), a famous TCM formula with ideal clinical effects in liver diseases. Here, we proposed a funnel-type stepwise filtering strategy that integrated secondary metabolites characterization, characteristic chromatogram, quantitative analysis, literature mining, biotransformation rules and network analysis. Firstly, the strategy of "secondary metabolites-botanical drugs-TCM formula" was applied to comprehensively identify the secondary metabolites of HGT. Then, the secondary metabolites with specificity and measurability in each botanical drug were identified by HPLC characteristic chromatogram, biosynthesis pathway and quantitative analysis. Based on literature mining, the effectiveness of botanical metabolites that met the above conditions was evaluated. Furthermore, the metabolism of the above metabolites in vivo was studied to reveal their biotransformation forms, which were used for network analysis. At last, according to biotransformation rules of the prototype drugs in vivo, the secondary metabolites were traced and preliminarily chosen as Q-markers. As a result, 128 plant secondary metabolites were identified in HGT, and 11 specific plant secondary metabolites were screened out. Then, the content of specific plant secondary metabolites in 15 batches of HGT was determined, which confirmed their measurability. And the results of literature mining showed that eight secondary metabolites had therapeutic effects in treating liver disease at the in vivo level, and three secondary metabolites inhibited liver disease-related indicators at the in vitro level. After that, 26 compounds absorbed into the blood (11 specific plant metabolites and their 15 metabolites in vivo) were detected in rats. Moreover, 14 compounds, including prototype components and their metabolites, were selected as Q-marker candidates by the "TCM formula-botanical drugs-compounds-targets-pathways" network. Finally, 9 plant secondary metabolites were defined as comprehensive and representative Q-markers. Our study not only provides a scientific basis for the improvement and secondary development of the quality standard of HGT, but also proposes a reference method for discovering and identifying Q-markers of TCM preparations.