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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

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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
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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.

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基金编号: 81603269 81741160 XH20170110 81 A2016334 2017A020217008 81603269 81741160

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出版当年[2019]版:
大类 | 4 区 化学
小类 | 3 区 光谱学 4 区 生化研究方法 4 区 分析化学
最新[2025]版:
大类 | 4 区 化学
小类 | 4 区 生化研究方法 4 区 分析化学 4 区 光谱学
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出版当年[2018]版:
Q2 SPECTROSCOPY Q3 BIOCHEMICAL RESEARCH METHODS Q3 CHEMISTRY, ANALYTICAL
最新[2023]版:
Q2 SPECTROSCOPY Q3 CHEMISTRY, ANALYTICAL Q4 BIOCHEMICAL RESEARCH METHODS

影响因子: 最新[2023版] 最新五年平均 出版当年[2018版] 出版当年五年平均 出版前一年[2017版] 出版后一年[2019版]

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第一作者机构: [1]School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, China
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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.
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