Springer Protocols: Abstract: SYFPEITHI: Database for Searching and T-Cell Epitope Prediction

SYFPEITHI: Database for Searching and T-Cell Epitope Prediction

By: Mathias M. Schuler³, Maria-Dorothea Nastke³, Stefan Stevanović³

Abstract

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Reverse immunology has been used for about 12 years in order to identify T-cell epitopes from pathogens or tumor-associated antigens. In this chapter, we discuss the advantages and pitfalls of T-cell epitope prediction compared to classical experimental procedures such as epitope mapping and cloning experiments. We introduce our three established programs, SYFPEITHI, PAProc, and SNEP, which are freely accessible at no cost in the World Wide Web for the prediction of either HLA–peptide binding or proteasomal processing of antigens. We demonstrate the performance of our epitope prediction programs with several examples and in comparison to other epitope prediction programs available. We also reflect the actual possibilities and limitations of such computer-aided work.

Affiliation(s): (3) Department of Immunology, Institute for Cell Biology, University of Tübingen, Tübingen, Germany

Book Title: Immunoinformatics: Predicting Immunogenicity In Silico

Series: Methods in Molecular Biology | Volume: 409 | Pub. Date: Jun-21-2007 | Page Range: 75-93 | DOI: 10.1007/978-1-60327-118-9_5

Subject: Immunology

Key Words: MHC - peptide motif - T-cell epitope - SNP - minor histocompatibility antigen - epitope prediction - CMV - HLA - proteasome - reverse immunology

References

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