MULTIPRED: A computational system for prediction of promiscuous HLA binding peptides

Guang Lan Zhang, Asif M. Khan, Kellathur N. Srinivasan, J. Thomas August, Vladimir Brusic

Research output: Contribution to journalArticlepeer-review

122 Scopus citations


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 AROC > 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 multipred/.

Original languageEnglish (US)
Pages (from-to)W172-W179
JournalNucleic acids research
Issue numberSUPPL. 2
StatePublished - Jul 2005
Externally publishedYes

ASJC Scopus subject areas

  • Genetics


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