T cell receptor specificity landscape revealed through de novo peptide design.

ABSTRACT: T cells play a key role in adaptive immunity by mounting specific responses against diverse pathogens. Effective bindings between T cell receptors (TCRs) and pathogen derived peptides presented on major histocompatibility complexes (MHCs) mediate immune responses. However, predicting these interactions remains challenging due to limited functional data on T cell reactivities. Here, we introduce a computational approach to predict TCR interactions with peptides presented on MHC-I alleles, and to design immunogenic peptides for specified TCR-MHC complexes. Our method leverages HERMES, a structure-based machine learning model trained on the protein universe to predict amino acid preferences based on local structural environments. Despite no direct training on TCR-pMHC data, HERMES's implicit

SUBMITTER: Visani GM 

PROVIDER: S-EPMC12557503 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature