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MULTIPRED: a computational system for prediction of promiscuous HLA binding peptides
Author(s) -
G. L. Zhang,
Asif M. Khan,
K.N. Srinivasan,
J. Thomas August,
Vladimir Brusić
Publication year - 2005
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gki452
Subject(s) - biology , epitope , human leukocyte antigen , computational biology , hidden markov model , genetics , artificial intelligence , antigen , computer science
MULTIPRED is a web-based computational system for the prediction of peptide binding to multiple molecules (proteins) belonging to human leukocyte antigens (HLA) class I A2, A3 and class II DR supertypes. It uses hidden Markov models and artificial neural network methods as predictive engines. A novel data representation method enables MULTIPRED to predict peptides that promiscuously bind multiple HLA alleles within one HLA supertype. Extensive testing was performed for validation of the prediction models. Testing results show that MULTIPRED is both sensitive and specific and it has good predictive ability (area under the receiver operating characteristic curve A(ROC) > 0.80). MULTIPRED can be used for the mapping of promiscuous T-cell epitopes as well as the regions of high concentration of these targets--termed T-cell epitope hotspots. MULTIPRED is available at http://antigen.i2r.a-star.edu.sg/multipred/.

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