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bioRxiv · 10.1101/2022.02.15.480516

Predicting TCR-peptide recognition based on residue-level pairwise statistical potential

Karnaukhov, V. K.·Shcherbinin, D. S.·Chugunov, A. O.·Chudakov, D. M.·Efremov, R. G.·Zvyagin, I. V.·Shugay, M.
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Abstract

Prediction of TCR-peptide interactions has great importance for therapy of cancer, infectious and autoimmune diseases, but remains a major challenge, particularly for unseen epitopes. We present a structure-based method that enables scoring of TCR-peptide interactions using an energy potential (TCRen) derived from statistics of TCR-peptide contacts in existing crystal structures. We show that TCRen has high performance in discriminating cognate/unrelated peptides and can facilitate the identification of cancer neoepitopes recognized by tumor-infiltrating lymphocytes.

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Karnaukhov, V. K., Shcherbinin, D. S., Chugunov, A. O., Chudakov, D. M., Efremov, R. G., Zvyagin, I. V., Shugay, M.. 2022-02-19. Predicting TCR-peptide recognition based on residue-level pairwise statistical potential. https://doi.org/10.1101/2022.02.15.480516

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