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MHCPred 2.0: an updated quantitative T-cell epitope prediction server.

Pingping Guan·Channa K Hattotuwagama·Irini A Doytchinova·Darren R Flower
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Abstract

UNLABELLED: The accurate computational prediction of T-cell epitopes can greatly reduce the experimental overhead implicit in candidate epitope identification within genomic sequences. In this article we present MHCPred 2.0, an enhanced version of our online, quantitative T-cell epitope prediction server. The previous version of MHCPred included mostly alleles from the human leukocyte antigen A (HLA-A) locus. In MHCPred 2.0, mouse models are added and computational constraints removed. Currently the server includes 11 human HLA class I, three human HLA class II, and three mouse class I models. Additionally, a binding model for the human transporter associated with antigen processing (TAP) is incorporated into the new MHCPred. A tool for the design of heteroclitic peptides is also included within the server. To refine the veracity of binding affinities prediction, a confidence percentage is also now calculated for each peptide predicted. AVAILABILITY: As previously, MHCPred 2.0 is freely available at the URL http://www.jenner.ac.uk/MHCPred/ CONTACT: Darren R. Flower (darren.flower@jenner.ac.uk).

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AlgorithmsAnimalsAntigen PresentationBinding SitesComputer SimulationEpitopes, T-LymphocyteHistocompatibility AntigensHumansInternetMajor Histocompatibility ComplexMiceModels, ChemicalModels, MolecularOnline SystemsPeptidesProtein BindingSequence Analysis, ProteinSoftwareUser-Computer InterfaceJournal ArticleResearch Support, Non-U.S. Gov't

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Pingping Guan, Channa K Hattotuwagama, Irini A Doytchinova, Darren R Flower. 2006. MHCPred 2.0: an updated quantitative T-cell epitope prediction server.. https://doi.org/10.2165/00822942-200605010-00008

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