4.6 Article

Dose-dependent targeted knockout methodology combined with deep structure elucidation strategies for Chinese licorice chemical profiling

期刊

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.jpba.2015.06.020

关键词

Licorice; Dose-dependent targeted knockout technique; UPLC-Q/TOF MS; MS-NMR combination spectroscopy; Flavonoid glycoside alkaloids; Organic acid alkaloids

资金

  1. National Science and Technology Major Projects for Major New Drugs Innovation and Development [2015ZX09J15102-004-004, 2014ZX09304307-001-005]
  2. National Natural Science Foundation of China [81202877]

向作者/读者索取更多资源

One of the limitations with regards to the chemical profiling of Chinese herbs is that low-level compounds are masked by high-level structures. Here, we established a novel methodology based on a dose-dependent targeted knockout (DDTK) technique combined with deep structure elucidation strategies to allow the chemical profiling of Chinese licorice. We employed ultra-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (UPLC-Q/TOF MS) incorporated with the DDTK technique to identify the compounds in different concentration samples and found that the compounds at the high- or medium-level were detected readily in the sample at a low concentration; subsequently, minor or trace-level constituents were identified in the sample at a high concentration by rejecting high-level constituents detected in the sample at a low concentration based on a heart-cutting technique during analysis. In this study, among the 232 compounds detected, 27 compounds were unequivocally identified and 165 compounds, including 29 new compounds and two new natural products, were tentatively characterized. The novel methodology established in this work paves the way the further identification of compounds from complicated mixtures, especially traditional Chinese medicines. (C) 2015 Elsevier B.V. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据