Exploring the Antihyperglycemic Chemical Composition and Mechanisms of Tea Using Molecular Docking
Exploring the Antihyperglycemic Chemical Composition and Mechanisms of Tea Using Molecular Docking
Tea, a widely consumed beverage, has long been utilized for promoting human health with a close correlation to hyperglycemia. The Tea Metabolome Database (TMDB), the most complete and comprehensive curated collection of tea compounds data containing 1271 identified small molecule compounds from the tea plant (Camellia sinensis), was established previously by our research team. More recently, our studies have found that various tea types possess an antihyperglycemic effect in mice. However, the bioactive ingredients from tea have potential antihyperglycemic activity and their underlying molecular mechanisms remain unclear. In this study, we used a molecular docking approach to investigate the potential interactions between a selected 747 constituents contained in tea and 11 key protein targets of clinical antihyperglycemic drugs. According to our results, the main antihyperglycemic targets of tea composition were consistent with those of the drug rosiglitazone. The screening results showed that GCG, ECG3’Me, TMDB‐01443, and CG had great target binding capacity. The results indicated that these chemicals of tea might affect hyperglycemia by acting on protein targets of rosiglitazone.
- University of Massachusetts System United States
- Fudan University China (People's Republic of)
- UNIVERSITY OF MASSACHUSETTS United States
- University of Massachusetts Amherst United States
- Anhui Agricultural University China (People's Republic of)
Research Article
Research Article
14 Research products, page 1 of 2
- 2013IsAmongTopNSimilarDocuments
- 2010IsRelatedTo
- 2020IsRelatedTo
- 2020IsRelatedTo
- 2017IsRelatedTo
- 2015IsRelatedTo
- 2016IsRelatedTo
- 2020IsRelatedTo
chevron_left - 1
- 2
chevron_right
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).3 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
