Application of Large-Scale Molecular Prediction for Creating the Preferred Precursor Ions List to Enhance the Identification of Ginsenosides from the Flower Buds of Panax ginseng,Journal of Agricultural and Food Chemistry

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Application of Large-Scale Molecular Prediction for Creating the Preferred Precursor Ions List to Enhance the Identification of Ginsenosides from the Flower Buds of Panax ginseng
Journal of Agricultural and Food Chemistry ( IF 5.7 ) Pub Date : 2022-05-03 , DOI: 10.1021/acs.jafc.2c01435
Chunxia Zhang ₁ , Meiyu Liu ₁ , Xiaoyan Xu ₁ , Jia Wu ₂ , Xue Li ₁ , Hongda Wang ₁ , Xiumei Gao _{1,

3} , Dean Guo ₄ , Xiaoxuan Tian ₁ , Wenzhi Yang ₁

Affiliation

This work was designed to evaluate the coverage of data-dependent acquisition (DDA) extensively utilized in the untargeted metabolite/component identification in the food sciences and pharmaceutical analysis. Using saponins from the flower buds of Panax ginseng (PGF) as an example, precursor ions list (PIL)-including DDA on a Q-Orbitrap mass spectrometer could enable higher coverage than the other four MS² acquisition approaches in characterizing PGF ginsenosides. A “Virtual Library of Ginsenoside” containing 13,536 ginsenoside molecules was established by C-language-programmed large-scale molecular prediction, which in combination with mass defect filtering could create a new PIL involving 1859 PGF saponin precursors. We could newly obtain the MS² spectra of at least 17 components and characterize 36 ginsenosides with unknown masses, among the 164 compounds identified from PGF. Conclusively, a molecular-prediction-oriented PIL in DDA can assist to discover more potentially novel molecules benefiting to the development of functional foods and new drugs.

中文翻译：

应用大规模分子预测创建优选前体离子列表以增强人参花芽中人参皂苷的鉴定

这项工作旨在评估在食品科学和药物分析中广泛用于非靶向代谢物/成分鉴定的数据依赖采集 (DDA) 的覆盖范围。以人参(PGF)花蕾中的皂苷为例，Q-Orbitrap 质谱仪上的前体离子列表 (PIL)（包括 DDA）在表征 PGF 人参皂苷方面比其他四种 MS ^{2采集方法具有更高的覆盖率。}通过C语言编程的大规模分子预测，建立了包含13,536个人参皂苷分子的“人参皂苷虚拟库” ，结合质量缺陷过滤，可以创建一个包含1859个PGF皂苷前体的新PIL。我们可以新获得MS从 PGF 中鉴定出的 164 种化合物中，至少有 17 种成分的^{2谱图和 36 种质量未知的人参皂苷的特征。}总之，DDA 中以分子预测为导向的 PIL 可以帮助发现更多有利于功能性食品和新药开发的潜在新分子。

更新日期：2022-05-03

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