{"title":"通过结构分析揭开 T 细胞受体表位的神秘面纱","authors":"Miaozhe Huo, Yuepeng Jiang, Shuai Cheng Li","doi":"10.1038/s43588-024-00654-z","DOIUrl":null,"url":null,"abstract":"A method leverages protein structural data to predict T-cell receptor–peptide interactions for unseen peptide epitopes, which can be particularly useful for applications in cancer immunotherapy, autoimmunity studies, and vaccine design.","PeriodicalId":74246,"journal":{"name":"Nature computational science","volume":null,"pages":null},"PeriodicalIF":12.0000,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Unlocking T-cell receptor–epitope insights with structural analysis\",\"authors\":\"Miaozhe Huo, Yuepeng Jiang, Shuai Cheng Li\",\"doi\":\"10.1038/s43588-024-00654-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A method leverages protein structural data to predict T-cell receptor–peptide interactions for unseen peptide epitopes, which can be particularly useful for applications in cancer immunotherapy, autoimmunity studies, and vaccine design.\",\"PeriodicalId\":74246,\"journal\":{\"name\":\"Nature computational science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":12.0000,\"publicationDate\":\"2024-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature computational science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.nature.com/articles/s43588-024-00654-z\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature computational science","FirstCategoryId":"1085","ListUrlMain":"https://www.nature.com/articles/s43588-024-00654-z","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
摘要
有一种方法利用蛋白质结构数据来预测未见肽表位的 T 细胞受体与肽的相互作用，这对癌症免疫疗法、自身免疫研究和疫苗设计中的应用特别有用。
Unlocking T-cell receptor–epitope insights with structural analysis
A method leverages protein structural data to predict T-cell receptor–peptide interactions for unseen peptide epitopes, which can be particularly useful for applications in cancer immunotherapy, autoimmunity studies, and vaccine design.
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