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| == Function == | | == Function == |
| [https://www.uniprot.org/uniprot/Q53Z42_HUMAN Q53Z42_HUMAN] Involved in the presentation of foreign antigens to the immune system (By similarity).[SAAS:SAAS003006_004_004364] | | [https://www.uniprot.org/uniprot/Q53Z42_HUMAN Q53Z42_HUMAN] Involved in the presentation of foreign antigens to the immune system (By similarity).[SAAS:SAAS003006_004_004364] |
| <div style="background-color:#fffaf0;">
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| == Publication Abstract from PubMed ==
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| 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.
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| 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>
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| From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.<br>
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| </div>
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| <div class="pdbe-citations 8tbw" style="background-color:#fffaf0;"></div>
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| == References ==
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| <references/>
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| __TOC__ | | __TOC__ |
| </StructureSection> | | </StructureSection> |
