Characterization and identification of alkaloids in Phellodendri Chinensis Cortex and Phellodendri Amurensis Cortex based on UHPLC-IM-Q-TOF-MS

Abstract

A strategy combining collision cross section(CCS) prediction and quantitative structure-retention relationship(QSRR) model for quinoline and isoquinoline alkaloids was established based on UHPLC-IM-Q-TOF-MS and applied to Phellodendri Chinensis Cortex and Phellodendri Amurensis Cortex. The strategy included the following three steps.(1) The molecular features were extracted by the "find features" algorithm.(2) The potential quinoline and isoquinoline alkaloids were screened by filtering the original characteristic ions extracted from Phellodendri Chinensis Cortex and Phellodendri Amurensis Cortex by the established CCS vs m/z prediction interval.(3) According to the retention time of candidate compounds predicted by QSRR model, the chemical constituents were identified in combination with the characteristic fragment ions and pyrolysis law of secondary mass spectrometry. With the strategy, a total of 80 compounds were predicted, and 15 were identified accurately. The strategy is effective for the identification of small analogs of traditional Chinese medicine.