EpiJen: a server for multistep T cell epitope prediction.
BACKGROUND
The main processing pathway for MHC class I ligands involves degradation of proteins by the proteasome, followed by transport of products by the transporter associated with antigen processing (TAP) to the endoplasmic reticulum (ER), where peptides are bound by MHC class I molecules, and then presented on the cell surface by MHCs. The whole process is modeled here using an integrated approach, which we call EpiJen. EpiJen is based on quantitative matrices, derived by the additive method, and applied successively to select epitopes. EpiJen is available free online.


RESULTS
To identify epitopes, a source protein is passed through four steps: proteasome cleavage, TAP transport, MHC binding and epitope selection. At each stage, different proportions of non-epitopes are eliminated. The final set of peptides represents no more than 5% of the whole protein sequence and will contain 85% of the true epitopes, as indicated by external validation. Compared to other integrated methods (NetCTL, WAPP and SMM), EpiJen performs best, predicting 61 of the 99 HIV epitopes used in this study.


CONCLUSIONS
EpiJen is a reliable multi-step algorithm for T cell epitope prediction, which belongs to the next generation of in silico T cell epitope identification methods. These methods aim to reduce subsequent experimental work by improving the success rate of epitope prediction.
Doytchinova
Irini A
IA
Edward Jenner Institute for Vaccine Research, Compton, RG20 7NN, UK. irini.doytchinova@jenner.ac.uk
Guan
Pingping
P
Flower
Darren R
DR
D003198:Computer Simulation; D018984:Epitopes, T-Lymphocyte / Q000737:chemistry* / Q000276:immunology*; D015395:Histocompatibility Antigens Class I / Q000737:chemistry* / Q000276:immunology*; D020407:Internet; D018448:Models, Immunological; D009862:Online Systems; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software; D018511:Systems Integration
D018984:Epitopes, T-Lymphocyte; D015395:Histocompatibility Antigens Class I