A dereplication strategy for identifying triterpene acid analogues in Poria cocos by comparing predicted and acquired UPLC-ESI-QTOF-MS/MS data.

Published on May 1, 2019in Phytochemical Analysis2.772
· DOI :10.1002/PCA.2813
Ye-Ting Zou3
Estimated H-index: 3
(Nanjing University of Chinese Medicine),
Fang Long3
Estimated H-index: 3
(Nanjing University of Chinese Medicine)
+ 5 AuthorsSong-Lin Li26
Estimated H-index: 26
(Nanjing University of Chinese Medicine)
Source
Abstract
INTRODUCTION: Triterpene acids from the dried sclerotia of Poria cocos (Schw.) Wolf (poria) were recently found to possess anti-cancer activities. Identification of more triterpene acid analogues in poria is worthwhile for high throughput screening in anti-cancer drug discovery. OBJECTIVE: To establish an efficient dereplication strategy for identifying triterpene acid analogues in poria based on ultra-performance liquid chromatography with electrospray ionisation quadrupole time-of-flight tandem mass spectrometry (UPLC-ESI-QTOF-MS/MS). METHODOLOGY: The structural characteristics and mass spectrometric data profiles of known triterpene acids previously reported in poria were used to establish a predicted-analogue database. Then, the quasi-molecular ions of components in a poria extract were automatically compared with those in the predicted-analogue database to highlight compounds of potential interest. Tentative structural identification of the compounds of potential interest and discrimination of isomers were achieved by assessing ion fragmentation patterns and chromatographic behaviour prediction based on structure-retention relationship. RESULTS: A total of 62 triterpene acids were unequivocally or tentatively characterised from poria, among which 17 triterpene acids were tentatively identified for the first time in poria. CONCLUSION: This study provided more structure information of triterpene acids in poria for future high throughput screening of anti-cancer candidates. It is suggested that this semi-automated approach in which MS data are automatically compared to a predictive database may also be applicable for efficient screening of other herbal medicines for structural analogues of proven bioactives.
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