期刊
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
卷 71, 期 14, 页码 5630-5645出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jafc.3c00591
关键词
Umami and bitter prediction; TPDM; key residues; molecular descriptors and fingerprints
In this study, 489 taste peptides with umami/bitter taste were analyzed and used to train a classification model based on docking analysis, molecular descriptors, and molecular fingerprints. The model, called taste peptide docking machine (TPDM), showed that certain molecular descriptors and fingerprints had the greatest impact on the umami/bitter prediction of peptides. Key recognition modes of umami/bitter receptors were also identified based on the docking results.
Taste peptides, as an important component of protein-rich foodstuffs, potentiate the nutrition and taste of food. Thereinto, umami-and bitter-taste peptides have been ex tensively reported, while their taste mechanisms remain unclear. Meanwhile, the identification of taste peptides is still a time-consuming and costly task. In this study, 489 peptides with umami/ bitter taste from TPDB (http://tastepeptides-meta.com/) were collected and used to train the classification models based on docking analysis, molecular descriptors (MDs), and molecular fingerprints (FPs). A consensus model, taste peptide docking machine (TPDM), was generated based on five learning algorithms (linear regression, random forest, gaussian naive bayes, gradient boosting tree, and stochastic gradient descent) and four molecular representation schemes. Model interpretive analysis showed that MDs (VSA_EState, MinEstateIndex, MolLogP) and FPs (598, 322, 952) had the greatest impact on the umami/bitter prediction of peptides. Based on the consensus docking results, we obtained the key recognition modes of umami/bitter receptors (T1Rs/T2Rs): (1) residues 107S-109S, 148S-154T, 247F-249A mainly form hydrogen bonding contacts and (2) residues 153A-158L, 163L, 181Q, 218D, 247F-249A in T1R1 and 56D, 106P, 107V, 152V-156F, 173K-180F in T2R14 constituted their hydrogen bond pockets. The model is available at http://www.tastepeptides-meta.com/yyds.
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