Screening and identification of characteristic components in big traditional Chinese medicine prescriptions using HPLC-ESI-Q/TOF-MS

In the present study, a powerful and rational strategy was proposed to offer higher quality structural information of components for the characterization of the complex big traditional Chinese medicine prescriptions (TCMPs). The self-built compounds database was established on the basis of the in-house screening and identification of each comprising herbal medicines using the same analytical method as the determined big TCMPs, including the same chromatographic and MS analysis, and also the same sample pretreatment methods. The herbs used for the self-built compounds database should be the raw materials using in the manufacture of big TCMPs whenever possible to avoid other interference factors, including the botanical origin, producing area, collecting seasons, concocted processing of medicinal materials. The retention times, ultraviolet absorption spectrums obtained by diode-array detector, accurate mass within 5 ppm error and mainly characteristic MS fragmentation ions of components identified in each comprising herbal medicines were listed in the self-built compounds library. Then the extraction ion chromatography (EIC) of the corresponding components from each herbs and equivalent dose of formula were compared one by one on the condition of guaranteeing the stability of instruments based on HPLC-ESI-Q/TOF-MS. Then the components in big TCMPs would be identified by comparing the characteristic product ions, fragmentation patterns with corresponding components in the comprising single medicinal materials. A total of 152 components deriving from the all 16 comprising medicinal herbs of NDQG were identified with the proposed components identification strategy here. The complementary multi-level structural information provided by LC/ion trap MSn as well as reference standard comparison analyses were also accompanied in this analysis. Moreover, the analytical approach developed herein is expected to provide an effective and reliable pattern for comprehensive and systemic characterization of TCM systems and other complicated mixtures.