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Enhanced Identification of Ginsenosides Simultaneously from Seven Panax Herbal Extracts by Data-Dependent Acquisition
Meiyu Liu1,2, Xiaoyan Xu1,2, Xiaoyan Wang1,2
1State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, China.
Abstract:
Data-dependent acquisition (DDA) is widely utilized for metabolite identification in natural product research and food science, which, however, can suffer from low coverage. A potential solution to improve DDA coverage is to include the precursor ions list (PIL). Here, we aimed to construct a PIL-containing DDA strategy based on an in-house library of ginsenosides (VLG) and identify ginsenosides simultaneously from seven Panax herbal extracts. VLG, combined with mass defect filtering, could efficiently screen the ginsenoside precursors and elaborate the separate PIL involved in DDA for each ginseng extract. Consequently, we could characterize 500 ginsenosides, including 176 ones with unknown masses. Using the Panax ginseng extract, the superiority of this strategy was embodied in targeting more known ginsenoside masses and newly acquiring the MS2 spectra of 13 components. Conclusively, knowledge-based large-scale molecular prediction and PIL-DDA can represent a powerful targeted/untargeted strategy beneficial to novel natural compound discovery.
