Title |
Predicting HLA Class I Non-Permissive Amino Acid Residues Substitutions
|
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Published in |
PLOS ONE, August 2012
|
DOI | 10.1371/journal.pone.0041710 |
Pubmed ID | |
Authors |
T. Andrew Binkowski, Susana R. Marino, Andrzej Joachimiak |
Abstract |
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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Geographical breakdown
Country | Count | As % |
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Australia | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
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Scientists | 1 | 50% |
Members of the public | 1 | 50% |
Mendeley readers
Geographical breakdown
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United States | 3 | 8% |
Unknown | 36 | 92% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 11 | 28% |
Student > Ph. D. Student | 10 | 26% |
Student > Master | 8 | 21% |
Other | 3 | 8% |
Professor > Associate Professor | 3 | 8% |
Other | 5 | 13% |
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Computer Science | 5 | 13% |
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Immunology and Microbiology | 3 | 8% |
Other | 6 | 15% |