{"title":"A structure-guided approach to predict MHC-I restriction of T cell receptors for public antigens","authors":"Sagar Gupta, Nikolaos G. Sgourakis","doi":"10.1016/j.str.2025.06.011","DOIUrl":null,"url":null,"abstract":"Peptides presented by major histocompatibility complex class I (MHC-I) proteins provide biomarkers for therapeutic targeting using T cell receptors (TCRs), TCR-mimicking antibodies (TMAs), or other engineered protein binders. Despite the extreme sequence diversity of the human leukocyte antigen (HLA, the human MHC), a given TCR or TMA is restricted to recognize epitopic peptides in the context of a limited set of different HLA alleles. Here, guided by our analysis of 98 TCR:pHLA complex structures, we identify TCR contact residues and classify 148 common HLA alleles into T cell cross-reactivity groups (T-CREGs) on the basis of their presented surface features. Insights from our work have actionable value for predicting MHC-I restriction of TCRs, guiding therapeutic expansion of existing TCR-based approaches and informing the selection of peptide targets for the development of new therapeutics.","PeriodicalId":22168,"journal":{"name":"Structure","volume":"23 2 1","pages":""},"PeriodicalIF":4.3000,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Structure","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.str.2025.06.011","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Peptides presented by major histocompatibility complex class I (MHC-I) proteins provide biomarkers for therapeutic targeting using T cell receptors (TCRs), TCR-mimicking antibodies (TMAs), or other engineered protein binders. Despite the extreme sequence diversity of the human leukocyte antigen (HLA, the human MHC), a given TCR or TMA is restricted to recognize epitopic peptides in the context of a limited set of different HLA alleles. Here, guided by our analysis of 98 TCR:pHLA complex structures, we identify TCR contact residues and classify 148 common HLA alleles into T cell cross-reactivity groups (T-CREGs) on the basis of their presented surface features. Insights from our work have actionable value for predicting MHC-I restriction of TCRs, guiding therapeutic expansion of existing TCR-based approaches and informing the selection of peptide targets for the development of new therapeutics.
期刊介绍:
Structure aims to publish papers of exceptional interest in the field of structural biology. The journal strives to be essential reading for structural biologists, as well as biologists and biochemists that are interested in macromolecular structure and function. Structure strongly encourages the submission of manuscripts that present structural and molecular insights into biological function and mechanism. Other reports that address fundamental questions in structural biology, such as structure-based examinations of protein evolution, folding, and/or design, will also be considered. We will consider the application of any method, experimental or computational, at high or low resolution, to conduct structural investigations, as long as the method is appropriate for the biological, functional, and mechanistic question(s) being addressed. Likewise, reports describing single-molecule analysis of biological mechanisms are welcome.
In general, the editors encourage submission of experimental structural studies that are enriched by an analysis of structure-activity relationships and will not consider studies that solely report structural information unless the structure or analysis is of exceptional and broad interest. Studies reporting only homology models, de novo models, or molecular dynamics simulations are also discouraged unless the models are informed by or validated by novel experimental data; rationalization of a large body of existing experimental evidence and making testable predictions based on a model or simulation is often not considered sufficient.