品味
化学
食品科学
计算生物学
计算机科学
生物
作者
Zhiyong Cui,Tianxing Zhou,Shengnan Wang,Imre Blank,Jiaming Gu,Danni Zhang,Yanyang Yu,Zhiwei Zhang,Wenli Wang,Yuan Liu
标识
DOI:10.1021/acs.jafc.4c12922
摘要
Taste peptides have nutritional and sensory properties, and their structural derivatives show unique taste modulation effects. The increasing number of taste peptide candidates requires a fast and accurate screening methodology using advanced detection tools. Notably, existing platforms lack integrated bioinformatics solutions to provide accurate retrieval and prediction capabilities. In response to this need, TastePeptides-Meta is proposed, comprising 2,926 peptides entries, 975 peptide structural derivatives, and 954 synergistic (enhancing) data from 282, 109, and 103 peer-reviewed studies, respectively. It was equipped with corresponding machine learning-driven prediction modules and domain-specific analytical toolkits. As an online interactive platform, TastePeptides-Meta provides multiple interfaces that allow searching, downloading and predicting taste peptides. We believe that the public availability of TastePeptides-Meta and its implementation of standardized data schemas will accelerate mechanistic investigations in the field of taste peptides and the development of data-driven, interpretable models for predicting and exploring taste mechanisms. The TastePeptides-Meta platform can be accessed online at http://www.tastepeptides-meta.com/.
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