ArticleMolecular immunology2013
Accurate structure prediction of peptide-MHC complexes for identifying highly immunogenic antigens.
Article in Molecular immunology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed.
- Peptide-binding specificity prediction using fine-tuned protein structure prediction networks.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Physicochemical Heuristics for Identifying High Fidelity, Near-Native Structural Models of Peptide/MHC Complexes.Frontiers in immunology · 2022Article
- Structural Prediction of Peptide-MHC Binding Modes.Methods in molecular biology (Clifton, N.J.) · 2022Review
- Combining Three-Dimensional Modeling with Artificial Intelligence to Increase Specificity and Precision in Peptide-MHC Binding Predictions.Journal of immunology (Baltimore, Md. : 1950) · 2020Article
- Predicting Cross-Reactivity and Antigen Specificity of T Cell Receptors.Frontiers in immunology · 2020Review
- Structure Based Prediction of Neoantigen Immunogenicity.Frontiers in immunology · 2019Article
- Machine Learning for Cancer Immunotherapies Based on Epitope Recognition by T Cell Receptors.Frontiers in genetics · 2019Review
- Article
- Platform technologies for modern vaccine manufacturing.Vaccine · 2017Review
- Enhancement of viral escape in HIV-1 Nef by STEP vaccination.AIDS (London, England) · 2016Article
- Article
- Genomic and bioinformatic profiling of mutational neoepitopes reveals new rules to predict anticancer immunogenicity.The Journal of experimental medicine · 2014Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Designing an optimal HIV-1 vaccine faces the challenge of identifying antigens that induce a broad immune capacity. One factor to control the breadth of T cell responses is the surface morphology of a peptide-MHC complex. Here, we present an in silico protocol for predicting peptide-MHC structure. A robust signature of a conformational transition was identified during all-atom molecular dynamics, which results in a model with high accuracy. A large test set was used in constructing our protocol and we went another step further using a blind test with a wild-type peptide and two highly immunogenic mutants, which predicted substantial conformational changes in both mutants. The center residues at position five of the analogs were configured to be accessible to solvent, forming a prominent surface, while the residue of the wild-type peptide was to point laterally toward the side of the binding cleft. We then experimentally determined the structures of the blind test set, using high resolution of X-ray crystallography, which verified predicted conformational changes. Our observation strongly supports a positive association of the surface morphology of a peptide-MHC complex to its immunogenicity. Our study offers the prospect of enhancing immunogenicity of vaccines by identifying MHC binding immunogens.
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Registered trials
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