AUTHOR=Ma Fang , Cui Qingxin , Bai Gang TITLE=Combining UPLC/Q-TOF-MS/MS With Biological Evaluation for NF-κB Inhibitors in Uyghur Medicine Althaea rosea Flowers JOURNAL=Frontiers in Plant Science VOLUME=9 YEAR=2019 URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2018.01975 DOI=10.3389/fpls.2018.01975 ISSN=1664-462X ABSTRACT=

The Althaea rosea (Linn.) flower is a common plant that is often used to control inflammation in Uyghur ethnic medicine. However, its active ingredients remain uncertain and difficult to identify, severely limiting its use as a valuable crop. This paper aims to establish a rapid assay strategy for the integration of ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF-MS/MS) and a biologically active (NF-κB inhibitor) luciferase reporter detection system to explore various anti-inflammatory compounds of A. rosea (Linn.) flowers. Potential anti-inflammatory components were screened using the NF-κB activity assay system and simultaneously identified based on mass spectrometry data. Four structural types of NF-κB inhibitors (phenolic acid, hydroxycinnamic acid, flavonoid, and dihydroflavone) were identified. Further cytokine assays confirmed their potential anti-inflammatory effects as NF-κB inhibitors. Compared with traditional chromatographic separation, integrated UPLC/Q-TOF-MS/MS identification compounds, and biological activity verification are more convenient and more reliable. This strategy clearly demonstrates that fingerprinting based on MS data not only can identify unknown components but also is a powerful and useful tool for screening trace active ingredients directly from complex matrices. A. rosea (Linn.) exhibits great health and pharmaceutical value and may contribute to the development of new anti-inflammatory drugs.