UNIT 18.19 TepiTool: A Pipeline for Computational Prediction of T Cell Epitope Candidates. (1st August 2016)

• Record Type: Journal Article
• Authors: Paul, Sinu; Sidney, John; Sette, Alessandro; Peters, Bjoern
• Is Part Of: Current protocols in immunology. Volume 114(2016)
• Page Start: 18.19.1
• Page End: 18.19.24
• Publication Date: 2016-08-01
• Subjects: binding affinity prediction -- CTL epitope prediction -- MHC class I -- MHC class II -- T cell epitope; Immunology -- Laboratory manuals; Medical protocols; Immunologic Techniques; Medical protocols; Immunology; Laboratory manuals; Reference works; 571.96028
• DOI: 10.1002/cpim.12
• Languages: English
• ISSNs: 1934-3671

Abstract

Abstract : Computational prediction of T cell epitope candidates is currently being used in several applications including vaccine discovery studies, development of diagnostics, and removal of unwanted immune responses against protein therapeutics. There have been continuous improvements in the performance of MHC binding prediction tools, but their general adoption by immunologists has been slow due to the lack of user‐friendly interfaces and guidelines. Current tools only provide minimal advice on what alleles to include, what lengths to consider, how to deal with homologous peptides, and what cutoffs should be considered relevant. This protocol provides step‐by‐step instructions with necessary recommendations for prediction of the best T cell epitope candidates with the newly developed online tool called TepiTool. TepiTool, which is part of the Immune Epitope Database (IEDB), provides some of the top MHC binding prediction algorithms for number of species including humans, chimpanzees, bovines, gorillas, macaques, mice, and pigs. The TepiTool is freely accessible at http://tools.iedb.org/tepitool/ . © 2016 by John Wiley & Sons, Inc.