SYFPEITHI: database for searching and T-cell epitope prediction

• Published in: Methods in molecular biology (Clifton, N.J.) Vol. 409; p. 75
• Main Authors: Schuler, Mathias M, Nastke, Maria-Dorothea, Stevanovikć, Stefan
• Format: Journal Article
• Language: English
• Published: United States 2007
• Subjects: Algorithms; Amino Acid Sequence; Antigens, Viral - genetics; Cloning, Molecular; Computational Biology; Cytomegalovirus - genetics; Cytomegalovirus - immunology; Databases, Genetic; Epitope Mapping - statistics & numerical data; Epitopes, T-Lymphocyte - genetics; Humans; Immunogenetics - statistics & numerical data; Internet; Minor Histocompatibility Antigens - genetics; Molecular Sequence Data; Phosphoproteins - genetics; Phosphoproteins - immunology; Phosphoproteins - metabolism; Protein Processing, Post-Translational; Software; Viral Matrix Proteins - genetics; Viral Matrix Proteins - immunology; Viral Matrix Proteins - metabolism
• ISSN: 1064-3745
• DOI: 10.1007/978-1-60327-118-9_5

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.