Amino Acid Biophysical Properties in the Statistical Prediction of Peptide-MHC Class I Binding


Show simple item record Ray, Surajit en_US Kepler, Thomas B en_US 2012-01-11T17:18:24Z 2012-01-11T17:18:24Z 2007 en_US 2007-10-29 en_US
dc.identifier.citation Ray, Surajit, Thomas B Kepler. "Amino acid biophysical properties in the statistical prediction of peptide-MHC class I binding" Immunome Research 3:9. (2007) en_US
dc.identifier.issn 1745-7580 en_US
dc.description.abstract BACKGROUND. A key step in the development of an adaptive immune response to pathogens or vaccines is the binding of short peptides to molecules of the Major Histocompatibility Complex (MHC) for presentation to T lymphocytes, which are thereby activated and differentiate into effector and memory cells. The rational design of vaccines consists in part in the identification of appropriate peptides to effect this process. There are several algorithms currently in use for making such predictions, but these are limited to a small number of MHC molecules and have good but imperfect prediction power. RESULTS. We have undertaken an exploration of the power gained by taking advantage of a natural representation of the amino acids in terms of their biophysical properties. We used several well-known statistical classifiers using either a naive encoding of amino acids by name or an encoding by biophysical properties. In all cases, the encoding by biophysical properties leads to substantially lower misclassification error. CONCLUSION. Representation of amino acids using a few important bio-physio-chemical property provide a natural basis for representing peptides and greatly improves peptide-MHC class I binding prediction. en_US
dc.description.sponsorship Duke University Center for Translational Research (5 P30 AI051445-03); Duke Epitope Discovery program (N01-A1-40082); Statistical and Mathematical Sciences Institute en_US
dc.language.iso en en_US
dc.publisher BioMed Central en_US
dc.rights Copyright 2007 Ray and Kepler; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. en_US
dc.rights.uri en_US
dc.title Amino Acid Biophysical Properties in the Statistical Prediction of Peptide-MHC Class I Binding en_US
dc.type article en_US
dc.identifier.doi 10.1186/1745-7580-3-9 en_US
dc.identifier.pubmedid 17967170 en_US
dc.identifier.pmcid 2186325 en_US

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