Advanced data post‐processing method for rapid identification and classification of the major triterpenoids of Alismatis rhizoma by ultra‐performance liquid chromatography coupled with quadrupole time‐of‐flight tandem mass spectrometry

Abstract

AbstractIntroductionAlismatis rhizoma (AR), a distinguished diuretic traditional Chinese herbal medicine, is widely used for the treatment of diarrhea, edema, nephropathy, hyperlipidemia, and tumors in clinical settings. Most beneficial effects of AR are attributed to the major triterpenoids, whose contents are relatively high in AR. To date, only 25 triterpenoids in AR have been characterized by LC‐MS because the low‐mass diagnostic ions are hardly triggered in MS, impeding structural identification. Herein, we developed an advanced data post‐processing method with abundant characteristic fragments (CFs) and neutral losses (NLs) for rapid identification and classification of the major triterpenoids in AR by UPLC‐Q‐TOF‐MSE.ObjectiveWe aimed to establish a systematic method for rapid identification and classification of the major triterpenoids of AR.MethodsUPLC‐Q‐TOF‐MSE coupled with an advanced data post‐processing method was established to characterize the major triterpenoids of AR. The abundant CFs and NLs of different types of triterpenoids were discovered and systematically summarized. The rapid identification and classification of the major triterpenoids of AR were realized by processing the data and comparing with information described in the literature.ResultsIn this study, a total of 44 triterpenoids were identified from AR, including three potentially new compounds and 41 known ones, which were classified into six types.ConclusionThe newly established approach is suitable for the chemical profiling of the major triterpenoids in AR, which could provide useful information about chemical constituents and a basis for further exploration of its active ingredients in vivo.