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      Rapid discovery and identification of the anti-inflammatory constituents in Zhi-Shi-Zhi-Zi-Chi-Tang

      , , , ,
      Chinese Journal of Natural Medicines
      Elsevier BV

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          Abstract

          The anti-inflammatory active ingredients of Zhi-Shi-Zhi-Zi-Chi-Tang (ZSZZCT), a traditional Chinese medicine formula, were predicted and identified using an approach based on activity index, LC-MS, semi-preparative LC and NMR. Firstly, the whole extract of ZSZZCT was analyzed using liquid chromatography-quadrupole time of flight-mass spectrometry (LC-Q-TOF-MS) and liquid chromatography - ion trap mass spectrometry (LC-IT-MS), 79 constituents were detected and 39 constituents were identified unambiguously or tentatively. Subsequently, the whole extract of the formula was separated into multiple components and the activity index method was used to calculate index values of the 79 constituents by integrating the chemical and pharmacological information of multiple components. Four polymethoxyl flavones were predicted as the major active constituents according to the activity index values. Furthermore, three polymethoxyl flavones were prepared using the strategy with semi-preparative LC guided by LC-MS, and their anti-inflammatory activities were validated. The results show that three polymethoxyl flavones with higher positive index values, i.e., 3, 5, 6, 7, 8, 3', 4'-heptamethoxyflavone, 3-hydroxynobiletein and tangeretin had significant anti-inflammatory effects. In conclusion, the predicted results indicated that the activity index method is feasible for the accurate prediction of active constituents in TCM formulae.

          Author and article information

          Journal
          Chinese Journal of Natural Medicines
          Chinese Journal of Natural Medicines
          Elsevier BV
          18755364
          April 2019
          April 2019
          : 17
          : 4
          : 308-320
          Article
          10.1016/S1875-5364(19)30035-4
          28d1aaf7-633a-4e8e-b3ff-78f4b8fc5ae4
          © 2019

          https://www.elsevier.com/tdm/userlicense/1.0/

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