Abstract
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/.
MeSH Terms
Computational Biology/methods
Epitopes, T-Lymphocyte/chemistry,immunology,metabolism
HLA-A Antigens/metabolism
HLA-DR Antigens/metabolism
Humans
Internet
Markov Chains
Neural Networks, Computer
Peptides/chemistry,immunology,metabolism
Software
User-Computer Interface
Chemicals
Epitopes, T-Lymphocyte
HLA-A Antigens
HLA-DR Antigens
Peptides
Authors & Affiliations
5 authors, click to expand affiliations / ORCID
Zhang Guang Lan
Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613.
Khan Asif M
Srinivasan Kellathur N
August J Thomas
Brusic Vladimir
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