EpiJen: a server for multistep T cell epitope prediction.
BMC Bioinformatics
; 7: 131, 2006 Mar 13.
Article
em En
| MEDLINE
| ID: mdl-16533401
ABSTRACT
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 foursteps:
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.CONCLUSION:
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.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Software
/
Antígenos de Histocompatibilidade Classe I
/
Modelos Imunológicos
/
Epitopos de Linfócito T
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Análise de Sequência de Proteína
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
BMC Bioinformatics
Assunto da revista:
INFORMATICA MEDICA
Ano de publicação:
2006
Tipo de documento:
Article
País de afiliação:
Reino Unido