An integrated strategy for characterization of chemical constituents in Stephania tetrandra using LC–QTOF–MS/MS and the target isolation of two new biflavonoids

• Published in: Journal of pharmaceutical and biomedical analysis Vol. 226; p. 115247
• Main Authors: Xue, Jiayun, Liu, Shun, Kang, Yun, Wang, Yaqin, Weng, Weiyu, Yang, Ping, Huang, Jianming
• Format: Journal Article
• Language: English
• Published: England Elsevier B.V 20.03.2023
• Subjects: Biflavonoid; Biflavonoids; Chromatography, High Pressure Liquid; Chromatography, Liquid - methods; Diagnostic fragment ion filtering; LC–QTOF–MS; Mass defect filtering; Molecular networking; Plants, Medicinal - chemistry; Stephania tetrandra; Tandem Mass Spectrometry - methods; Stephania tetrandra; Mass defect filtering; Molecular networking; Biflavonoid; LC–QTOF–MS; Diagnostic fragment ion filtering
• ISSN: 0731-7085; 1873-264X
• DOI: 10.1016/j.jpba.2023.115247

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. [Display omitted] •An integrated strategy based on LC–MS was developed to identify the phytochemicals.•The integrated strategy was used to profile the chemicals in Stephania tetrandra.•A total of 144 compounds were identified or tentatively identified in S. tetrandra.•Eleven potentially new compounds were tentatively identified in this species.•Two new biflavonoids were isolated and structurally elucidated by NMR analyses.