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ComMSDB—一种从 MS 数据集(以鉴定绞股蓝皂苷为例)中自动识别化合物的策略。

ComMSDB-An Automatable Strategy to Identify Compounds from MS Data Sets (Identification of Gypenosides as an Example).

机构信息

School of Pharmacy, Fudan University, Shanghai 200135, P. R. China.

Center for Pharmacological Evaluation and Research of SIPI, Shanghai Institute of Pharmaceutical Industry, Shanghai 200082, P. R. China.

出版信息

J Agric Food Chem. 2020 Oct 14;68(41):11368-11388. doi: 10.1021/acs.jafc.0c03693. Epub 2020 Oct 1.

Abstract

(Thunb.) Makino is a popular functional food and is also used as an important medicinal plant in China. Gypenoside, the main active constituent in (Thunb.) Makino, belongs to dammarane-type triterpenoid saponins. Due to its high molecular weight and high polarity, it is difficult to obtain complete compound information for gypenoside extracts via mass spectrometry experiments. In this study, an automated targeted data postprocessing strategy called Compound MS Database (ComMSDB) was designed and established to elucidate compounds in gypenoside extracts based on ultrahigh-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight tandem mass spectrometry (UHPLC-ESI-Q-TOF-MS/MS). As a result, 18 types of and 199 main saponin constituents, including 47 potential novel compounds, were tentatively identified from different habitats. At the same time, 15 gypenoside standard compounds were used to verify the feasibility of the ComMSDB strategy. These results demonstrated that ComMSDB offers practical value for quick, automated, and effective compound identification.

摘要

绞股蓝是一种受欢迎的功能性食品,也是中国重要的药用植物。绞股蓝中的主要活性成分绞股蓝皂苷属于达玛烷型三萜皂苷。由于其分子量高、极性强,通过质谱实验很难获得绞股蓝提取物中化合物的完整信息。本研究设计并建立了一种自动化靶向数据后处理策略,称为化合物 MS 数据库(ComMSDB),用于基于超高效液相色谱-电喷雾电离四极杆飞行时间串联质谱(UHPLC-ESI-Q-TOF-MS/MS)阐明绞股蓝提取物中的化合物。结果,从不同生境中初步鉴定出 18 种和 199 种主要皂苷成分,包括 47 种潜在的新化合物。同时,使用 15 种绞股蓝标准化合物验证了 ComMSDB 策略的可行性。这些结果表明,ComMSDB 为快速、自动和有效鉴定化合物提供了实用价值。

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