IMMREP25: Unseen Peptides

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Authors: Eve Richardson, Yannick Jurriaan Maria Aarts, John A. Altin, Coos A. B. Baakman, Philip Bradley, Binbin Chen, Joakim Nøddeskov Clifford, Manjima Dhar, Danielle Diepenbroek, Ethan Fast, Ragul Gowthaman, Jieling He
+26 more Vadim K Karnaukhov, Dario F. Marzella, Pieter Meysman, Morten Nielsen, Jonas Birkelund Nilsson, Sebastian Nymann Deleuran, Farzaneh M. Parizi, Aurélien Pélissier, Brian G. Pierce, María Rodríguez Martínez, Dona Roran A R, Shayana Saravanakumar, Yanjun Shao, Nils Smit, Max Van Houcke, Gian Marco Visani, Yat-tsai Richie Wan, Xiaowo Wang, Lawson J. Woods, Sander Wuyts, Chengkai Xiao, Li C. Xue, Justin Barton, Matthew T. Noakes, Damon May, Bjoern Peters
Cited by: 11
References: 54

Abstract

Abstract T cell receptors (TCRs) can bind to peptides presented by MHC molecules (pMHC) as a first step to trigger a T cell response. Reliable approaches to predict TCR:pMHC binding would have broad applications in clinical diagnostics, therapeutics, and the fundamental understanding of molecular interactions. IMMREP is a community organized series of prediction contests that asks participants to predict TCR:pMHC binding on unpublished datasets. Previous iterations in 2022 and 2023 showed multiple approaches can predict TCR-pMHC binding with significant accuracy (median AUC_0.1≥0.7) for peptides where experimental data is available (“seen” peptides). In contrast, models did not outperform random guessing for peptides that have no such data available (“unseen” peptides). Here we report on the results of IMMREP25, which focused solely on unseen peptides in order to evaluate the cutting edge of the field. We received 126 named submissions predicting the specificity of 1,000 TCRs against twenty unseen peptides restricted by one of two MHC molecules (HLA-A*02:01 and HLA-B*40:01). The best performing methods showed a macro-AUC_0.1 of 0.60, significantly better than random, demonstrating significant advances in the field. The top performing methods incorporated structural modeling into their approach, indicating that especially for ‘unseen’ peptides, a structural understanding aids in the prediction of TCR:pMHC interactions. The results from this benchmark highlight the significant challenges remaining for TCR:pMHC predictions and will inform future method development.

Fields of Study & Subjects

vaccines and immunoinformatics approaches T-cell and B-cell Immunology Immunotherapy and Immune Responses

Publication details

Journal / source
bioRxiv (Cold Spring Harbor Laboratory)
Publisher
openRxiv
Publication date
1 April 2026
Document type
Preprint