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Evaluation of different generic in silico methods for predicting HLA class I binding peptide vaccine candidates using a reverse approach.

DIR@IMTECH: CSIR-Institute of Microbial Technology

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Title Evaluation of different generic in silico methods for predicting HLA class I binding peptide vaccine candidates using a reverse approach.
 
Creator Gowthaman, Uthaman
Chodisetti, Sathi Babu
Parihar, Pankaj
Agrewala, J N
 
Subject QR180 Immunology
 
Description Since CD8+ T cell response is crucial to combat intracellular infections and cancer, identification of class I HLA binding peptides is of immense clinical value. The experimental identification of such peptides is protracted and laborious. Exploiting in silico tools to discover such peptides is an attractive alternative. However, this approach needs a thorough assessment before its elaborate application. We have adopted a reverse approach to evaluate the reliability of eight different servers (inclusive of 55 predictors) by exploiting experimentally proven data. A comprehensive data set of more than 960 peptides was employed to test the efficacy of the programs. We have validated commonly used strategies to predict peptides that bind to seven most prevalent HLA class I alleles. We conclude that four of the eight servers are more adept in predictions. Although the overall predictions for class I MHC binders were superior to class II MHC binders, individual predictors for different alleles belonging to the same program were highly variable in their efficiencies. We have also addressed whether a consensus approach can yield better prediction efficiency. We observed that combining the results from different in silico programs could not increase the efficiency significantly.
 
Publisher Springer Science
 
Date 2010-11
 
Type Article
PeerReviewed
 
Format application/pdf
 
Identifier http://crdd.osdd.net/open/524/1/agrewala10.pdf
Gowthaman, Uthaman and Chodisetti, Sathi Babu and Parihar, Pankaj and Agrewala, J N (2010) Evaluation of different generic in silico methods for predicting HLA class I binding peptide vaccine candidates using a reverse approach. Amino acids, 39 (5). pp. 1333-42. ISSN 1438-2199
 
Relation http://www.springerlink.com/content/d002832617360288/fulltext.pdf
http://crdd.osdd.net/open/524/