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Proteins. 2016 Sep;84 Suppl 1:67-75. doi: 10.1002/prot.24974. Epub 2016 Feb 24.

Improved de novo structure prediction in CASP11 by incorporating coevolution information into Rosetta.

Ovchinnikov S1,2, Kim DE2,3, Wang RY1,2, Liu Y1,2, DiMaio F1,2, Baker D4,5,6.

Author information

1
Department of Biochemistry, University of Washington, Washington, Seattle 98195.
2
Institute for Protein Design, University of Washington, Washington, Seattle 98195.
3
Howard Hughes Medical Institute, University of Washington, Washington, Seattle 98195.
4
Department of Biochemistry, University of Washington, Washington, Seattle 98195. dabaker@u.washington.edu.
5
Institute for Protein Design, University of Washington, Washington, Seattle 98195. dabaker@u.washington.edu.
6
Howard Hughes Medical Institute, University of Washington, Washington, Seattle 98195. dabaker@u.washington.edu.

Abstract

We describe CASP11 de novo blind structure predictions made using the Rosetta structure prediction methodology with both automatic and human assisted protocols. Model accuracy was generally improved using coevolution derived residue-residue contact information as restraints during Rosetta conformational sampling and refinement, particularly when the number of sequences in the family was more than three times the length of the protein. The highlight was the human assisted prediction of T0806, a large and topologically complex target with no homologs of known structure, which had unprecedented accuracy-<3.0 Å root-mean-square deviation (RMSD) from the crystal structure over 223 residues. For this target, we increased the amount of conformational sampling over our fully automated method by employing an iterative hybridization protocol. Our results clearly demonstrate, in a blind prediction scenario, that coevolution derived contacts can considerably increase the accuracy of template-free structure modeling. Proteins 2016; 84(Suppl 1):67-75.

KEYWORDS:

ab initio prediction; coevolution; contact prediction; protein structure prediction; rosetta

PMID:
26677056
PMCID:
PMC5490371
DOI:
10.1002/prot.24974
[Indexed for MEDLINE]
Free PMC Article

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