期刊
JOURNAL OF SEPARATION SCIENCE
卷 44, 期 7, 页码 1537-1551出版社
WILEY-V C H VERLAG GMBH
DOI: 10.1002/jssc.202001068
关键词
flavonoid glycosides; molecular networking; Robinia hispida L.; Robinia pseudoacacia L.; rohispidascopolin
资金
- Natural Science Foundation of Ningxia Province [2019AAC03113]
- Science Research Project of Ningxia Higher Education Institutions [NGY2017165]
- Scientific Research Projects at North Minzu University [ZDZX201803, 2020000116]
- National Natural Science Foundation of China [81603006]
- Scientific Research Start-up project for Recruitment Talents of North Minzu University in 2019 [113159150]
This study successfully identified the chemical compositions of fresh flowers from two ornamental plant species using advanced analytical methods, including glycosylated structures and flavonoid glycosides, as well as discovering a new compound. Pharmacological targets of these compounds were predicted.
Developing methods for the systematic and rapid identification of the chemical compositions of fresh plant tissues has long attracted the attention of phytochemists and pharmacologists. In the present study, based on highly efficient sample pretreatment and high-throughput analysis of high-performance liquid chromatography coupled with quadrupole time of flight tandem mass spectrometry data using molecular networks, a method was developed for systematically analyzing the chemical constituents of the fresh flowers of Robinia hispida L. and Robina pseudoacacia L., two congeneric ornamental species that lack prior consideration. A total of 44 glycosylated structures were characterized. And on the basis of establishing of the fragmentation pathways of 11 known flavonoid glycosides, together with the molecular networking analysis, 18 other ions of flavonoid glycosides in five classes were clustered. Moreover, 15 soyasaponins/triterpenoid glycosides were tentatively identified by comparison of their tandem mass spectrometry characteristic ions with those reported in the literature or the online Global Natural Product Social Molecular Networking database. The water extracts were separated by flash chromatography, which resulted in the discovery of one new compound, named rohispidascopolin, along with five known entities. The pharmacological targets were predicted by Swis-sTargetPrediction.
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