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PLoS One. 2012;7(8):e41710. doi: 10.1371/journal.pone.0041710. Epub 2012 Aug 8.

Predicting HLA class I non-permissive amino acid residues substitutions.

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Biosciences Division, Argonne National Laboratory, Midwest Center for Structural Genomics, Argonne, Illinois, United States of America.


Prediction of peptide binding to human leukocyte antigen (HLA) molecules is essential to a wide range of clinical entities from vaccine design to stem cell transplant compatibility. Here we present a new structure-based methodology that applies robust computational tools to model peptide-HLA (p-HLA) binding interactions. The method leverages the structural conservation observed in p-HLA complexes to significantly reduce the search space and calculate the system's binding free energy. This approach is benchmarked against existing p-HLA complexes and the prediction performance is measured against a library of experimentally validated peptides. The effect on binding activity across a large set of high-affinity peptides is used to investigate amino acid mismatches reported as high-risk factors in hematopoietic stem cell transplantation.

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