A mass spectrometry database for identification of saponins in plants
A mass spectrometry database for identification of saponins in plants
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用于鉴定植物中皂苷的质谱数据库
DOI：
10.1016/j.chroma.2020.461296
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发表时间：
2020-08-16
影响因子：
4.1
通讯作者：
Zhou, Wei
中科院分区：
文献类型：
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作者：
Huang, Feng-Qing;Dong, Xuesi;Zhou, Wei
皂苷是植物界一类重要的次生代谢物。在这里，我们提出了一个基于质谱学的数据库，用于快速、方便地鉴定皂苷，以下简称皂苷质谱库(SMSd)。总皂苷4196个，其中214个来自商业来源。通过负离子模式下的液相色谱-串联高分辨/质谱仪(HR/MS)分析，所有母体碎片离子的裂解行为几乎符合高能碰撞诱导解离过程中糖基的连续损失、α-解离和麦氏重排。糖基产生从m/z(单糖)到m/z(多糖)的糖碎片离子。用上述碎裂模式预测了其他皂苷的母体离子和糖类碎片离子。SMSD可以在http://47.92.73.208:8082/or http://cpu-smsd.com上免费获取(最好使用谷歌)。它提供了三种搜索模式(分类、搜索和代谢物)。在“分类”功能下，通过建立Logistic回归模型，以CSV文件的形式从HR/MS输入的海量数据中对所有代谢物中的皂苷进行分类，其中第一列为ID，第二列为MASS。对于“搜索”功能，在“MS离子搜索”中，以具有一定质量容差的母体离子为对照来搜索皂苷。然后，将具有一定质量容差的子离子输入到MS/MS离子搜索中。根据匹配次数和匹配率值与数据库中的片段数据进行比较，筛选出最优候选。此外，另一个Logistic回归模型完全区分了亲本离子和糖片段离子。该功能设计在网站前台，有利于搜索和复查。利用“代谢物”功能，可以使用皂苷的常用名称进行搜索，支持全名搜索和部分名称搜索。利用这些模式，可以对不同化学成分的皂苷进行探索、分组和鉴定，并具有高度的预测准确性。这个专门的数据库将有助于鉴定复杂基质中的皂苷，特别是在中药或植物代谢组学的研究中。(C)2020爱思唯尔B.V.保留所有权利。
Saponins constitute an important class of secondary metabolites of the plant kingdom. Here, we present a mass spectrometry-based database for rapid and easy identification of saponins henceforth referred to as saponin mass spectrometry database (SMSD). With a total of 4196 saponins, 214 of which were obtained from commercial sources. Through liquid chromatography-tandem high-resolution/mass spectrometry (HR/MS) analysis under negative ion mode, the fragmentation behavior for all parent fragment ions almost conformed to successive losses of sugar moieties, alpha-dissociation and McLafferty rearrangement of aglycones in high-energy collision induced dissociation. The saccharide moieties produced sugar fragment ions from m/z (monosaccharide) to m/z (polysaccharides). The parent and sugar fragment ions of other saponins were predicted using the above mentioned fragmentation pattern. The SMSD is freely accessible at http://47.92.73.208:8082/or http://cpu-smsd.com (preferrably using google). It provides three search modes ("CLASSIFY", "SEARCH" and "METABOLITE"). Under the "CLASSIFY" function, saponins are classified with high predictive accuracies from all metabolites by establishment of logistic regression model through their mass data from HR/MS input as a csv file, where the first column is ID and the second column is mass. For the "SEARCH" function, saponins are searched against parent ions with certain mass tolerance in "MS Ion Search". Then, daughter ions with certain mass tolerance are input into "MS/MS Ion Search". The optimal candidates were screened out according to the match count and match rate values in comparison with fragment data in database. Additionally, another logistic regression model completely differentiated between parent and sugar fragment ions. This function designed in front web is conducive to search and recheck. With the "METABOLITE" function, saponins are searched using their common names, where both full and partial name searches are supported. With these modes, saponins of diverse chemical composition can be explored, grouped and identified with a high degree of predictive accuracy. This specialized database would aid in the identification of saponins in complex matrices particular in the study of traditional Chinese medicines or plant metabolomics. (C) 2020 Elsevier B.V. All rights reserved.