T‐cell receptor insights: Determinants of Major Histocompatibility Complex class I versus class <scp>II</scp> recognition

In this study, we analyzed large-scale T-cell receptor (TCR) sequence data to determine whether TCRs preferentially bind to major histocompatibility complex (MHC) class I (CD8+) or class II (CD4+) epitopes. Using the International ImMunoGeneTics information system numbering scheme, we identified specific positions with distinct amino acid enrichment for each MHC class and developed machine learning models for classification. While our frequency-based approach effectively differentiated MHC-I from MHC-II TCRs in cross-validation, performance declined when only beta chain data were used from real-world peripheral blood mononuclear cell samples. However, incorporating the TCR alpha chain significantly improved accuracy, emphasizing its importance for MHC recognition. Overall, we found that V-region loops can signal MHC class bias, aiding in immunotherapy design and TCR repertoire analysis, while highlighting the need for larger, more diverse datasets for reliable predictions.

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Publication Details

Journal
Protein Science
Published
2025-08-15
DOI
https://doi.org/10.1002/pro.70262
Citations
2
Primary Topic
vaccines and immunoinformatics approaches
Type
article
Field-Weighted Citation Impact
1.61

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article

T‐cell receptor insights: Determinants of Major Histocompatibility Complex class I versus class II recognition

Leila Y. Chihab, Jonas Birkelund Nilsson, Morten Nielsen, Lonneke Scheffer et al.
2 citations
Protein Science
vaccines and immunoinformatics approaches
1.61
article

T‐cell receptor insights: Determinants of Major Histocompatibility Complex class I versus class II recognition

Leila Y. Chihab, Jonas Birkelund Nilsson, Morten Nielsen, Lonneke Scheffer, Bjoern Peters, Marcus Fabiano de Almeida Mendes
article en
2 citations

Abstract

In this study, we analyzed large-scale T-cell receptor (TCR) sequence data to determine whether TCRs preferentially bind to major histocompatibility complex (MHC) class I (CD8+) or class II (CD4+) epitopes. Using the International ImMunoGeneTics information system numbering scheme, we identified specific positions with distinct amino acid enrichment for each MHC class and developed machine learning models for classification. While our frequency-based approach effectively differentiated MHC-I from MHC-II TCRs in cross-validation, performance declined when only beta chain data were used from real-world peripheral blood mononuclear cell samples. However, incorporating the TCR alpha chain significantly improved accuracy, emphasizing its importance for MHC recognition. Overall, we found that V-region loops can signal MHC class bias, aiding in immunotherapy design and TCR repertoire analysis, while highlighting the need for larger, more diverse datasets for reliable predictions.

Protein ScienceVol. 34(9)
La Jolla Institute for Immunology (US), University of Oslo (NO), University of California San Diego (US), Unge aksjonærer (NO), Technical University of Denmark (DK)
National Institutes of Health
Openalex Percentile: Top 15%
vaccines and immunoinformatics approaches
1.61
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T‐cell receptor insights: Determinants of Major Histocompatibility Complex class I versus class <scp>II</scp> recognition — Leila Y. Chihab, Jonas Birkelund Nilsson, et al. · Protein Science (2025) | TGRS Research Map | TGRS