文章基本信息

标题：Removing T-cell epitopes with computational protein design
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作者：Chris King ; Esteban N. Garza ; Ronit Mazor 等
期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2014
卷号：111
期号：23
页码：8577-8582
DOI：10.1073/pnas.1321126111
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：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.
关键词：deimmunization ; machine learning ; biotherapeutics ; Rosetta ; immunotoxin