Method development and application of offline two-dimensional liquid chromatography/quadrupole time-of-flight mass spectrometry-fast data directed analysis for comprehensive characterization of the saponins from Xueshuantong Injection

摘要

Xueshuantong Injection (XSTI), derived from Notoginseng total saponins, is a popular traditional Chinese medicine injection for the treatment of thrombus-resultant diseases. Current knowledge on its therapeutic basis is limited to five major saponins, whereas those minor ones are rarely investigated. We herein develop an offline two-dimensional liquid chromatography/quadrupole time-of-flight mass spectrometry-fast data directed analysis (offline 2D LC/QTOF-Fast DDA) approach to systematically characterize the saponins contained in XSTI. Key parameters affecting chromatographic separation in 2D LC (including stationary phase, mobile phase, column temperature, and gradient elution program) and the detection by QTOF MS (involving spray voltage, cone voltage, and ramp collision energy) were optimized in sequence. The configured offline 2D LC system showed an orthogonality of 0.84 and a theoretical peak capacity of 8976. Total saponins in XSTI were fractionated into eleven samples by the first-dimensional hydrophilic interaction chromatography, which were further analyzed by reversed phase UHPLC/QTOF-Fast DDA in negative ion mode. The fragmentation features evidenced from 36 saponin reference standards, high-accuracy MS and Fast-DDA-MS2 data, elemental composition (C < 80, H < 120, O < 50), double-bond equivalent (DBE 5-15), and searching an in-house library of Panax notoginseng, were simultaneously utilized for structural elucidation. Ultimately, 148 saponins were separated and characterized, and 80 have not been isolated from P. notoginseng. An in-depth depiction of the chemical composition of XSTI was achieved. The results obtained would benefit better understanding of the therapeutic basis and significant promotion on the quality standard of XSTI as well as other homologous products. (C) 2016 Published by Elsevier B.V.