Characterization of chemical constituents in Huangqi Guizhi Wuwu decoction using ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry.
Zhuoyu FanJiao GuanLele LiYue CuiXinmiao TangXiaoying LinGuanghai ShenBo FengHeyun ZhuPublished in: Journal of separation science (2023)
Huangqi Guizhi Wuwu decoction (HGWWD) is a classic traditional Chinese medicine prescription for the treatment of ischemic stroke, etc. However, the material basis of its efficacy remains unclear, seriously affecting drug development and clinical applications. In the present study, an ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry method was developed to separate and identify the chemical components of HGWWD. A total of 81 compounds were identified and tentatively characterized. Eight compounds were accurately identified by comparing the retention time and mass spectrometry data with those of reference substances, the remaining compounds were characterized by comparing the mass spectrometry data and reference information. Based on the results of compound attribution, 35 compounds were from Astragali Radix, six compounds were from Cinnamomi Ramulus, 23 compounds were from Paeoniae Radix Alba, eight compounds were from Zingiberis Rhizoma Recens and nine compounds were from Jujubae Fructus. The results showed that monoterpenoids, flavonoids, organic acids, triterpenes, amino acids, gingerols, alkaloids, and glycosides were the main chemical components of HGWWD. This analytical method is suitable for characterizing the chemical constituents of HGWWD, and the results provide important information for elucidating its pharmacodynamic material basis and mechanism of action.
Keyphrases
- mass spectrometry
- tandem mass spectrometry
- liquid chromatography
- ultra high performance liquid chromatography
- high performance liquid chromatography
- high resolution mass spectrometry
- simultaneous determination
- gas chromatography
- healthcare
- solid phase extraction
- amino acid
- capillary electrophoresis
- big data
- drinking water
- social media
- data analysis
- smoking cessation