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  • 标题:Removing T-cell epitopes with computational protein design
  • 本地全文:下载
  • 作者:Chris King ; Esteban N. Garza ; Ronit Mazor
  • 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
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