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Ultra-high performance liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry and database-driven automatic peak annotation for the rapid profiling and characterization of the multicomponents from Stephaniae Tetrandrae radix (Fang-Ji)

1 State Key Laboratory of Component-based Chinese Medicine; Tianjin Key Laboratory of TCM Chemistry and Analysis, Tianjin University of Traditional Chinese Medicine, Tianjin, China
2 State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China

Correspondence Address:
Wen-Zhi Yang,
Tianjin State Key Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/wjtcm.wjtcm_56_20

Quality control of traditional Chinese medicine (TCM) begins with elucidation of its chemical basis. The root of Stephania tetrandra, Stephaniae Tetrandrae radix (STR; Fang-Ji), has long been utilized as an antirheumatic, analgesic, and diuretic TCM. Powerful analytical strategies that would enable a multicomponent characterization of STR are still lacking. In the present study, we established a rapid, reliable, and enhanced profiling approach, using ultra-high performance liquid chromatography coupled with ion mobility/quadrupole time-of-flight mass spectrometry (MS) and automatic peak annotation facilitated by computational matching of an in-house library. This approach was used to characterize the multicomponents of STR. Good chromatographic separation was achieved within 17 min on a reversed-phase BEH C18 column eluted with acetonitrile/0.1% ammonium hydroxide in water, whereas data-independent high-definition MSE in the positive mode was applied to acquire the MS2 data using a Vion™ IM-QTOF instrument, which, in theory, could cover all the profiled precursor ions. To overcome the interference of three predominant peaks, a knockout strategy was utilized by automated valve switching. An in-house library of 163 compounds was established and incorporated into the UNIFI™ platform. By applying this method, we could identify or tentatively characterize 76 alkaloids from the methanolic extract of STR, including 14 aporphine-type, four morphine-type, 48 bisbenzylisoquinoline-type, seven tetrahydroprotoberberine-type, one protopine-type, one benzylisoquinoline-type, and one other. For each component, four-dimensional information, such as retention time, collision cross-section, high-accuracy MS1, and high-accuracy MS2 data, was utilized to achieve the systematic multicomponent characterization of STR.

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