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  • 标题:De novo design of synthetic prion domains
  • 本地全文:下载
  • 作者:James A. Toombs ; Michelina Petri ; Kacy R. Paul
  • 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:2012
  • 卷号:109
  • 期号:17
  • 页码:6519-6524
  • DOI:10.1073/pnas.1119366109
  • 语种:English
  • 出版社:The National Academy of Sciences of the United States of America
  • 摘要:Prions are important disease agents and epigenetic regulatory elements. Prion formation involves the structural conversion of proteins from a soluble form into an insoluble amyloid form. In many cases, this structural conversion is driven by a glutamine/asparagine (Q/N)-rich prion-forming domain. However, our understanding of the sequence requirements for prion formation and propagation by Q/N-rich domains has been insufficient for accurate prion propensity prediction or prion domain design. By focusing exclusively on amino acid composition, we have developed a prion aggregation prediction algorithm (PAPA), specifically designed to predict prion propensity of Q/N-rich proteins. Here, we show not only that this algorithm is far more effective than traditional amyloid prediction algorithms at predicting prion propensity of Q/N-rich proteins, but remarkably, also that PAPA is capable of rationally designing protein domains that function as prions in vivo.
  • 关键词:Sup35 ; yeast ; bioinformatics
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