化学
质谱法
加合物
电喷雾
离解(化学)
碎片(计算)
电喷雾电离
串联质谱法
夏枯草
碰撞诱导离解
色谱法
有机化学
操作系统
病理
医学
中医药
计算机科学
替代医学
作者
Fengwei Ma,Hua-Yong Lou,Yonghui Ge,Jinyu Li,Chao Chen,Su-Yang Xu,Lei Tang,Weidong Pan
标识
DOI:10.1007/s00216-021-03615-x
摘要
Vulgarisins are members of diterpenoids with rare 5/6/4/5 ring skeleton from Prunella vulgaris Linn. (P. vulgaris). Their molecular scaffolds comprise different hydroxylation and degree of esterification. Vulgarisins have attracted many attentions in the fields of food and medicine for their potent bioactivities. Firstly, four reference compounds were analyzed by higher-energy collisional dissociation mass spectrometry (HCD MS/MS) and the fragmentation patterns for molecular scaffold were summarized. And then, a high-performance liquid chromatography/electrospray ionization/high-resolution mass spectrometry (HPLC-ESI-HR-MS) method was adopted to investigate the P. vulgaris extracts. Finally, the proposed analysis results were successfully applied to facilitate the discovery of the vulgarisins analogues from P. vulgaris. For the four reference compounds, the sodium adduct was the predominate ion in full scan. A specific fragmentation pathway of [M+Na]+ ions leads to produce diagnostic ions of vulgarisins at m/z 325 under HCD, which was formed through consecutive-side chains lost. Twenty-three diterpenoids, including 18 vulgarisins analogues, were identified or tentatively characterized in the botanical extracts of P. vulgaris based on their elemental constituents and characteristic fragment ion profiles. Two new vulgarisins analogues in the plant were isolated and their structures were illustrated based on extensive spectroscopic analysis using 1D and 2D nuclear magnetic resonance (NMR) spectroscopy. The HCD MS/MS method, including the profiles of the diagnostic ions induced by characteristic fragmentation, is an effective technique for the discovery of vulgarisins analogues in P. vulgaris. The expected fragmentation pattern knowledge will also facilitate the analysis of other natural products.
科研通智能强力驱动
Strongly Powered by AbleSci AI