An integrated strategy for characterization of chemical constituents in Stephania tetrandra using LC-QTOF-MS/MS and the target isolation of two new biflavonoids.
Biflavonoid
Diagnostic fragment ion filtering
LC–QTOF–MS
Mass defect filtering
Molecular networking
Stephania tetrandra
Journal
Journal of pharmaceutical and biomedical analysis
ISSN: 1873-264X
Titre abrégé: J Pharm Biomed Anal
Pays: England
ID NLM: 8309336
Informations de publication
Date de publication:
20 Mar 2023
20 Mar 2023
Historique:
received:
16
10
2022
revised:
08
01
2023
accepted:
10
01
2023
pubmed:
20
1
2023
medline:
25
2
2023
entrez:
19
1
2023
Statut:
ppublish
Résumé
LC-MS has been a widely used analytical technique for identification of natural compounds. However, sophisticated and laborious data analysis is required to identify chemical components, especially new compounds, from a large LC-MS dataset. The aim of this study is to develop an integrated data-mining strategy that combines molecular networking (MN), in-house polygonal mass defect filtering (MDF), and diagnostic fragment ion filtering (DFIF) to identify phytochemicals in Stephania tetrandra based on LC-MS data. S. tetrandra samples were prepared by matrix solid-phase dispersion extraction methods and then raw MS spectra were acquired using LC-QTOF-MS/MS. MN and in-house polygonal MDF classified the compounds roughly. Modified DFIF were then used in succession to place each spectrum into a specific class. Finally, the exact structures were deduced by fragmentation pathways and related botanical biogenesis, with the help of the narrowed classification from MN and MDF. The total workflow was a combination of data filtering and identification methods for rapid characterization of known compounds (dereplication) and discovery of new compounds. Consequently, 144 compounds were identified or tentatively identified in the aerial parts and roots of S. tetrandra, including 11 potentially new compounds and 63 compounds first identified in this species. Among 144 compounds, 61 were from the aerial parts exclusively, 8 were from the roots exclusively, and 75 were found in both parts. Furthermore, two new biflavonoids were isolated with the guide of LC-MS analysis and structurally elucidated by spectroscopic methods. In conclusion, the proposed data-mining strategy based on LC-MS can be used to profile chemical constituents with high efficiency and guide the isolation of new compounds from medicinal plants. The comparison of the components of the aerial parts and roots of S. tetrandra would be helpful for the rational utilization of the medicinal plant.
Identifiants
pubmed: 36657347
pii: S0731-7085(23)00016-X
doi: 10.1016/j.jpba.2023.115247
pii:
doi:
Substances chimiques
Biflavonoids
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
115247Informations de copyright
Copyright © 2023 Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.