Non-targeted characteristic filter analysis combined with in silico prediction strategies to identify the chemical components and in vivo metabolites of Dalitong Granules by UPLC-Q-TOF/MS/MS

Yan Su, Lin Tao, Xiaoli Zhang,Xianjie Sheng,Qin Li, Wenying Fei, Tao Yin,An Kang,Jiye Aa,Guangji Wang

Journal of Pharmaceutical and Biomedical Analysis(2023)

引用 3|浏览15
暂无评分
摘要
Dalitong Granules, a potent gastrointestinal motility promoting traditional Chinese medicine, is used to treat functional dyspepsia clinically. It shows good effect on alleviating gastrointestinal motility disorders and has a broad prospect of clinical application. However, there is no comprehensive study on its in vivo and in vitro chemical analysis. UPLC-Q-TOF-MS combined with the non-targeted characteristic filter analysis and in silico prediction strategies (NCFS) were used to deduce and identify the chemical components and in vivo metabolites in the bio-samples of rats following oral administration of Dalitong Granules. In this study, 108 chemical components were identified in Dalitong granules, including 50 flavonoids, 22 alkaloids, 13 terpenes, 11 organic acids, 10 coumarins and 2 volatile oils. In the plasma, tissue, urine and fecal samples of rats after administration of Dalitong granules, a total of 147 compounds were speculated (60 prototype compounds and 87 metabolites). The main metabolic pathways in vivo include methylation, demethylation, deglycosylation, hydrogenation, hydroxylation, sulfonation and glucuronidation as there are many flavonoids existing in Dalitong Granules. In conclusion, the chemical components and metabolites of Dalitong Granules were comprehensively identified by using a rapid and accurate analysis method, which laid a foundation for dissecting its bioactive substances. In addition, it provides a scientific basis for the in-depth study of the material basis of Dalitong Granules efficacy and its further comprehensive development and utilization.
更多
查看译文
关键词
Dalitong Granules,Chemical constituents,Metabolites,High resolution mass spectrometry
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要