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采用液相色谱-高分辨质谱和计算 MS/MS 裂解技术准确识别和鉴定了梁外甘草黄酮提取物的特征。

Accurate recognition and feature qualify for flavonoid extracts from Liang-wai Gan Cao by liquid chromatography-high resolution-mass spectrometry and computational MS/MS fragmentation.

机构信息

Department of Pharmaceutical Engineering, School of Chemical Engineering, Xiangtan University, Xiangtan, 411105, People's Republic of China.

Institute of Forensic Science, Hunan Provincial Public Security Bureau, Changsha, 410001, People's Republic of China.

出版信息

J Pharm Biomed Anal. 2017 Nov 30;146:37-47. doi: 10.1016/j.jpba.2017.07.065. Epub 2017 Aug 19.

Abstract

In this study, Liquid Chromatography (LC) separation combined with quadrupole-Time-Of-Flight Mass Spectrometry (qTOF-MS) detection was used to analyze the characteristic ions of the flavonoids from Liang-wai Gan Cao (Radix Glycyrrhizae uralensis). First, accurate mass measurement and isotope curve optimization could provide reliable molecular prediction after noise deduction, baseline calibration and "ghost peak recognition". Thus, some spectral features in the LC-MS data could be clearly explained. Secondly, the chemical structure of flavonoids was deduced by MS/MS fragment ions, and the in-silico spectra by MS-FINDER program provided strong support for overcoming the bottleneck of phytochemical identification. For a predicted formula and experimental MS/MS spectrum, the MS-FINDER program could sort the candidate compounds in the public database based on a comprehensive weighted score, and we took the first 20 reliable compounds to seek the target compound in an in-house database. Certainly, those fragmentation pathways could also be deduced and described as Retro-Diels-Alder (RDA) fragmentation reaction, losses of CH, CH, CH, CO, CO and others. Accordingly, 63 flavonoids were identified, and their in-silico bioactivity were clearly disclosed by some bioinformatics tools. In this experiment, the flavonoids obtained by the four extraction processes were tested by LC-qTOF-MS. We looked for possible Q-markers from these data matrices and then quantified them; their similarities/differences were also described. The results also indicated that the Macroporous Adsorption Resins (MARs) purification is a low cost, environmentally friendly and effective approach.

摘要

本研究采用液相色谱(LC)分离与四极杆飞行时间质谱(qTOF-MS)联用技术,分析了甘草(甘草)中黄酮类化合物的特征离子。首先,通过降噪、基线校准和“鬼峰识别”后,精确质量测量和同位素曲线优化可提供可靠的分子预测。因此,可以清楚地解释 LC-MS 数据中的一些光谱特征。其次,通过 MS/MS 碎片离子推断黄酮类化合物的化学结构,MS-FINDER 程序的计算光谱为克服植物化学鉴定的瓶颈提供了有力支持。对于预测的分子式和实验 MS/MS 光谱,MS-FINDER 程序可以根据综合加权分数对公共数据库中的候选化合物进行排序,我们选择前 20 个可靠的化合物在内部数据库中寻找目标化合物。当然,也可以推断和描述这些裂解途径,例如逆-Diels-Alder(RDA)裂解反应、CH、CH、CH、CO、CO 等的损失。因此,鉴定出 63 种黄酮类化合物,并通过一些生物信息学工具清楚地揭示了它们的计算生物活性。在本实验中,通过四种提取工艺得到的黄酮类化合物用 LC-qTOF-MS 进行测试。我们从这些数据矩阵中寻找可能的 Q 标志物,然后对其进行定量;还描述了它们的相似性/差异。结果还表明,大孔吸附树脂(MARs)纯化是一种低成本、环保且有效的方法。

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