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== Publication Abstract from PubMed ==

Major histocompatibility complex (MHC) proteins present peptides on the cell surface for T cell surveillance. Reliable in silico prediction of which peptides would be presented and which T cell receptors would recognize them is an important problem in structural immunology. Here, we introduce an AlphaFold-based pipeline for predicting the three-dimensional structures of peptide-MHC complexes for class I and class II MHC molecules. Our method demonstrates high accuracy, outperforming existing tools in class I modeling accuracy and class II peptide register prediction. We validate its performance and utility with new experimental data on a recently described cancer neoantigen/wild-type peptide pair and explore applications toward improving peptide-MHC binding prediction.

Accurate modeling of peptide-MHC structures with AlphaFold.,Mikhaylov V, Brambley CA, Keller GLJ, Arbuiso AG, Weiss LI, Baker BM, Levine AJ Structure. 2023 Dec 14:S0969-2126(23)00413-6. doi: 10.1016/j.str.2023.11.011. PMID:38113889<ref>PMID:38113889</ref>

From MEDLINE&reg;/PubMed&reg;, a database of the U.S. National Library of Medicine.<br>

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== References ==

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