{"title":"探索小肽与 T1R1/T1R3 味觉受体在味肽预测中的关系:综合方法。","authors":"Wenyuan Zhang, Hui Guan, Miaomiao Wang, Wenyu Wang, Jianyu Pu, Hui Zou* and Dapeng Li*, ","doi":"10.1021/acs.jafc.4c00187","DOIUrl":null,"url":null,"abstract":"<p >Umami peptides are known for enhancing the taste experience by binding to oral umami T1R1 and T1R3 receptors. Among them, small peptides (composed of 2–4 amino acids) constitute nearly 40% of reported umami peptides. Given the diversity in amino acids and peptide sequences, umami small peptides possess tremendous untapped potential. By investigating 168,400 small peptides, we screened candidates binding to T1R1/T1R3 through molecular docking and molecular dynamics simulations, explored bonding types, amino acid characteristics, preferred binding sites, etc. Utilizing three-dimensional molecular descriptors, bonding information, and a back-propagation neural network, we developed a predictive model with 90.3% accuracy, identifying 24,539 potential umami peptides. Clustering revealed three classes with distinct logP (−2.66 ± 1.02, −3.52 ± 0.93, −2.44 ± 1.23) and asphericity (0.28 ± 0.12, 0.26 ± 0.11, 0.25 ± 0.11), indicating significant differences in shape and hydrophobicity (<i>P</i> < 0.05) among potential umami peptides binding to T1R1/T1R3. Following clustering, nine representative peptides (CQ, DP, NN, CSQ, DMC, TGS, DATE, HANR, and STAN) were synthesized and confirmed to possess umami taste through sensory evaluations and electronic tongue analyses. In summary, this study provides insights into exploring small peptide interactions with umami receptors, advancing umami peptide prediction models.</p>","PeriodicalId":41,"journal":{"name":"Journal of Agricultural and Food Chemistry","volume":"72 23","pages":"13262–13272"},"PeriodicalIF":6.2000,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Exploring the Relationship between Small Peptides and the T1R1/T1R3 Umami Taste Receptor for Umami Peptide Prediction: A Combined Approach\",\"authors\":\"Wenyuan Zhang, Hui Guan, Miaomiao Wang, Wenyu Wang, Jianyu Pu, Hui Zou* and Dapeng Li*, \",\"doi\":\"10.1021/acs.jafc.4c00187\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >Umami peptides are known for enhancing the taste experience by binding to oral umami T1R1 and T1R3 receptors. Among them, small peptides (composed of 2–4 amino acids) constitute nearly 40% of reported umami peptides. Given the diversity in amino acids and peptide sequences, umami small peptides possess tremendous untapped potential. By investigating 168,400 small peptides, we screened candidates binding to T1R1/T1R3 through molecular docking and molecular dynamics simulations, explored bonding types, amino acid characteristics, preferred binding sites, etc. Utilizing three-dimensional molecular descriptors, bonding information, and a back-propagation neural network, we developed a predictive model with 90.3% accuracy, identifying 24,539 potential umami peptides. Clustering revealed three classes with distinct logP (−2.66 ± 1.02, −3.52 ± 0.93, −2.44 ± 1.23) and asphericity (0.28 ± 0.12, 0.26 ± 0.11, 0.25 ± 0.11), indicating significant differences in shape and hydrophobicity (<i>P</i> < 0.05) among potential umami peptides binding to T1R1/T1R3. Following clustering, nine representative peptides (CQ, DP, NN, CSQ, DMC, TGS, DATE, HANR, and STAN) were synthesized and confirmed to possess umami taste through sensory evaluations and electronic tongue analyses. In summary, this study provides insights into exploring small peptide interactions with umami receptors, advancing umami peptide prediction models.</p>\",\"PeriodicalId\":41,\"journal\":{\"name\":\"Journal of Agricultural and Food Chemistry\",\"volume\":\"72 23\",\"pages\":\"13262–13272\"},\"PeriodicalIF\":6.2000,\"publicationDate\":\"2024-05-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Agricultural and Food Chemistry\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://pubs.acs.org/doi/10.1021/acs.jafc.4c00187\",\"RegionNum\":1,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRICULTURE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Agricultural and Food Chemistry","FirstCategoryId":"97","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acs.jafc.4c00187","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
Exploring the Relationship between Small Peptides and the T1R1/T1R3 Umami Taste Receptor for Umami Peptide Prediction: A Combined Approach
Umami peptides are known for enhancing the taste experience by binding to oral umami T1R1 and T1R3 receptors. Among them, small peptides (composed of 2–4 amino acids) constitute nearly 40% of reported umami peptides. Given the diversity in amino acids and peptide sequences, umami small peptides possess tremendous untapped potential. By investigating 168,400 small peptides, we screened candidates binding to T1R1/T1R3 through molecular docking and molecular dynamics simulations, explored bonding types, amino acid characteristics, preferred binding sites, etc. Utilizing three-dimensional molecular descriptors, bonding information, and a back-propagation neural network, we developed a predictive model with 90.3% accuracy, identifying 24,539 potential umami peptides. Clustering revealed three classes with distinct logP (−2.66 ± 1.02, −3.52 ± 0.93, −2.44 ± 1.23) and asphericity (0.28 ± 0.12, 0.26 ± 0.11, 0.25 ± 0.11), indicating significant differences in shape and hydrophobicity (P < 0.05) among potential umami peptides binding to T1R1/T1R3. Following clustering, nine representative peptides (CQ, DP, NN, CSQ, DMC, TGS, DATE, HANR, and STAN) were synthesized and confirmed to possess umami taste through sensory evaluations and electronic tongue analyses. In summary, this study provides insights into exploring small peptide interactions with umami receptors, advancing umami peptide prediction models.
期刊介绍:
The Journal of Agricultural and Food Chemistry publishes high-quality, cutting edge original research representing complete studies and research advances dealing with the chemistry and biochemistry of agriculture and food. The Journal also encourages papers with chemistry and/or biochemistry as a major component combined with biological/sensory/nutritional/toxicological evaluation related to agriculture and/or food.