Structural characterization and discrimination of Paris polyphylla var. yunnanensis by a molecular networking strategy coupled with ultra-high-performance liquid chromatography with quadrupole time-of-flight mass spectrometry
机构:[1]School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, China[2]Pharmacy Department, Second Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, China广东省中医院
Rationale Paris polyphylla var. yunnanensis (Franch) Hand Mazz (PPY) is a traditional Chinese medicine with antitumor, antibacterial, hemostatic, and anthelmintic activities. Identification of the chemical composition in PPY is helpful to discover its active ingredients and can be used to establish its quality control protocols. Methods The composition of PPY was identified using ultra-high-performance liquid chromatography combined with quadrupole time-of-flight mass spectrometry (UHPLC/QTOF-MS/MS) coupled with a molecular networking strategy. First, the UHPLC/QTOF-MS/MS approach was optimized for chemical compound profiling. Then, the MS data were processed using PeakView (TM) combined with an in-house database to quickly characterize the secondary metabolites. Finally, molecular networking excavated new molecular weights to discover unknown or trace natural products based on the characteristics of each cluster. Results A total of 222 compounds, including 77 isospirostanols, 2 spirostanols, 19 furostanols, 10 pseudospirostanols, 6 cholesterols, 10 C-21 steroids, 5 insect metamorphosis hormones, 3 plant sterols, 6 five-ring triterpenoids, 4 flavonoids, 8 fatty acids, 2 phenylpropanoids, and 8 other compounds, were characterized in PPY by comparing their main fragmentation characteristics and pathways with the literature data, and 62 of them, 54 steroidals and 8 phenylpropanoids, were discovered or tentatively identified for the first time. Conclusions This study extended the application of a molecular networking strategy to traditional herbal medicines and developed a molecular networking based screening approach with a significant increase in efficiency for the discovery and identification of trace novel natural products.
基金:
National Natural Science Foundation of ChinaNational Natural Science Foundation of China [81603269, 81741160]; Fire Plan Project of the Guangzhou University of Chinese Medicine [XH20170110]; Project on Construction of High Level University of Guangzhou University of Chinese Medicine [81]; Medical Research Foundation of Guangdong Province [A2016334]; Science and Technology Planning Project of Guangdong Province [2017A020217008]; NSFCNational Natural Science Foundation of China [81603269, 81741160]
第一作者机构:[1]School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, China
共同第一作者:
通讯作者:
通讯机构:[1]School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, China[*1]School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou 510006, China[*2]School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, China.
推荐引用方式(GB/T 7714):
Wang Yumei,Fan Qian,Xiang Jun,et al.Structural characterization and discrimination of Paris polyphylla var. yunnanensis by a molecular networking strategy coupled with ultra-high-performance liquid chromatography with quadrupole time-of-flight mass spectrometry[J].RAPID COMMUNICATIONS IN MASS SPECTROMETRY.2020,34(11):doi:10.1002/rcm.8760.
APA:
Wang, Yumei,Fan, Qian,Xiang, Jun,Huang, Haibo,Chen, Sheng...&Rong, Li.(2020).Structural characterization and discrimination of Paris polyphylla var. yunnanensis by a molecular networking strategy coupled with ultra-high-performance liquid chromatography with quadrupole time-of-flight mass spectrometry.RAPID COMMUNICATIONS IN MASS SPECTROMETRY,34,(11)
MLA:
Wang, Yumei,et al."Structural characterization and discrimination of Paris polyphylla var. yunnanensis by a molecular networking strategy coupled with ultra-high-performance liquid chromatography with quadrupole time-of-flight mass spectrometry".RAPID COMMUNICATIONS IN MASS SPECTROMETRY 34..11(2020)