Improving computational protein design by using structure-derived sequence profile
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Yang, Yuedong
Kim, Hyung Rae
Zhou, Yaoqi
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Abstract
Designing a protein sequence that will fold into a predefined structure is of both practical and fundamental interest. Many successful, computational designs in the last decade resulted from improved understanding of hydrophobic and polar interactions between side chains of amino acid residues in stabilizing protein tertiary structures. However, the coupling between main-chain backbone structure and local sequence has yet to be fully addressed. Here, we attempt to account for such coupling by using a sequence profile derived from the sequences of five residue fragments in a fragment library that are structurally matched to the five-residue segments contained in a target structure. We further introduced a term to reduce low complexity regions of designed sequences. These two terms together with optimized reference states for amino-acid residues were implemented in the RosettaDesign program. The new method, called RosettaDesign-SR, makes a 12% increase (from 34 to 46%) in fraction of proteins whose designed sequences are more than 35% identical to wild-type sequences. Meanwhile, it reduces 8% (from 22% to 14%) to the number of designed sequences that are not homologous to any known protein sequences according to psiblast. More importantly, the sequences designed by RosettaDesign-SR have 2-3% more polar residues at the surface and core regions of proteins and these surface and core polar residues have about 4% higher sequence identity to wild-type sequences than by RosettaDesign. Thus, the proteins designed by RosettaDesign-SR should be less likely to aggregate and more likely to have unique structures due to more specific polar interactions.
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Proteins: Structure, Function, and Bioinformatics
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78
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10
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© 2010 Wiley Periodicals, Inc. This is the accepted version of the following article: Improving computational protein design by using structure-derived sequence profile, Proteins: Structure, Function, and Bioinformatics, Vol. 78(10), 2010, pp. 2338-2348, which has been published in final form at dx.doi.org/10.1002/prot.22746.
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Bioinformatics
Mathematical Sciences
Biological Sciences
Information and Computing Sciences