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Curr Protoc Immunol. 2016 Aug 1;114:18.19.1-18.19.24. doi: 10.1002/cpim.12.

TepiTool: A Pipeline for Computational Prediction of T Cell Epitope Candidates.

Author information

1
La Jolla Institute for Allergy and Immunology, Division of Vaccine Discovery, La Jolla, California.

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/.

KEYWORDS:

CTL epitope prediction; MHC class II; MHC class I; T cell epitope; binding affinity prediction

PMID:
27479659
PMCID:
PMC4981331
DOI:
10.1002/cpim.12
[Indexed for MEDLINE]
Free PMC Article

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