Abstract
In this study, we aim to establish an integrated research strategy for the rapid chemical profiling of Compound Huanggen Granules (CHG) and absorbed prototypes in plasma by integrating the UHPLC-Q-TOF-MSE method and data post-processing strategy, to provide some valuable research basis for the further studies on the quality control, pharmacokinetics and pharmacodynamics of CHG. Compound Huanggen Granules (CHG), a traditional Chinese medicine (TCM) hospital preparation, has long been used in clinical practice for the prevention and treatment of liver fibrosis. However, due to the lack of in vitro chemical and in vivo metabolism studies, its pharmacodynamic material basis is still unrevealed. To simplify the mass data post-processing process and enhance the structural identification efficiency by reducing the possibility of false positive, and rapidly identify the absorbed prototypes in plasma after oral administration of CHG. An analytical strategy integrating ultra high-performance liquid chromatography coupled with quadrupletime- of-flight mass spectrometry (UHPLC-Q-TOF-MSE, E represents collision energy) method and data postprocessing strategy based on a self-built in-house components database was established and utilized for the rapid characterization of the multi-constituents of CHG and prototypes in cynomolgus monkey plasma after oral administration. As a result, a total of 81 compounds, including 14 phenolic acids, 6 coumarins, 25 flavonoids, 5 anthraquinones, 5 phenylpropanoids, 15 triterpenoid saponins, and 11 others, were plausibly or unambiguously identified based on their accurate masses, and MS/MS fragment pathways analysis, and also by comparison of retention time and MS data with reference standards. In the in vivo study, according to the extracted ion chromatograms (EICs) of identified components, 34 absorbed prototypical components were rapidly identified in cynomolgus monkey plasma after oral administration. It was demonstrated that the data post-processing strategy applied in this study could greatly simplify the data post-processing process and enhance the structural identification efficiency by reducing the possibility of false positives, and the results obtained might be helpful for further studies on the quality control, pharmacokinetics and pharmacodynamics of CHG.
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