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Proc Natl Acad Sci U S A. 2014 Jun 10;111(23):8577-82. doi: 10.1073/pnas.1321126111. Epub 2014 May 19.

Removing T-cell epitopes with computational protein design.

Author information

1
Institute for Protein Design, Department of Biochemistry and chrisk1@uw.edu.
2
Department of Immunology, University of Washington, Seattle, WA 98195; and.
3
National Cancer Institute and.
4
National Institute of Allergy and Infectious Disease, National Institutes of Health, Bethesda, MD 20892.
5
Institute for Protein Design, Department of Biochemistry and.

Abstract

Immune responses can make protein therapeutics ineffective or even dangerous. We describe a general computational protein design method for reducing immunogenicity by eliminating known and predicted T-cell epitopes and maximizing the content of human peptide sequences without disrupting protein structure and function. We show that the method recapitulates previous experimental results on immunogenicity reduction, and we use it to disrupt T-cell epitopes in GFP and Pseudomonas exotoxin A without disrupting function.

KEYWORDS:

Rosetta; biotherapeutics; deimmunization; immunotoxin; machine learning

PMID:
24843166
PMCID:
PMC4060723
DOI:
10.1073/pnas.1321126111
[Indexed for MEDLINE]
Free PMC Article
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