title: Improved de novo structure prediction in CASP11 by incorporating coevolution information into Rosetta.
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. © 2015 Wiley Periodicals, Inc.
authors.affiliation: Department of Biochemistry, University of Washington, Washington, Seattle 98195.|Institute for Protein Design, University of Washington, Washington, Seattle 98195.
authors.forename: Sergey
authors.initials: S
authors.lastname: Ovchinnikov
authors.affiliation: Institute for Protein Design, University of Washington, Washington, Seattle 98195.|Howard Hughes Medical Institute, University of Washington, Washington, Seattle 98195.
authors.forename: David E
authors.initials: DE
authors.lastname: Kim
authors.affiliation: Department of Biochemistry, University of Washington, Washington, Seattle 98195.|Institute for Protein Design, University of Washington, Washington, Seattle 98195.
authors.forename: Ray Yu-Ruei
authors.initials: RY
authors.lastname: Wang
authors.affiliation: Department of Biochemistry, University of Washington, Washington, Seattle 98195.|Institute for Protein Design, University of Washington, Washington, Seattle 98195.
authors.forename: Yuan
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Department of Biochemistry, University of Washington, Washington, Seattle 98195.|Institute for Protein Design, University of Washington, Washington, Seattle 98195.
authors.forename: Frank
authors.initials: F
authors.lastname: DiMaio
authors.affiliation: Department of Biochemistry, University of Washington, Washington, Seattle 98195. dabaker@u.washington.edu.|Institute for Protein Design, University of Washington, Washington, Seattle 98195. dabaker@u.washington.edu.|Howard Hughes Medical Institute, University of Washington, Washington, Seattle 98195. dabaker@u.washington.edu.
authors.forename: David
authors.initials: D
authors.lastname: Baker
mesh_terms: D000595:Amino Acid Sequence; D019295:Computational Biology / Q000379:methods / Q000706:statistics & numerical data*; D018360:Crystallography, X-Ray; D019020:Directed Molecular Evolution; D004926:Escherichia coli / Q000737:chemistry; D029968:Escherichia coli Proteins / Q000737:chemistry*; D006801:Humans; D020407:Internet; D008958:Models, Molecular; D015233:Models, Statistical; D017510:Protein Folding; D054730:Protein Interaction Domains and Motifs; D017433:Protein Structure, Secondary; D016415:Sequence Alignment; D012984:Software
chemical_list: D029968:Escherichia coli Proteins; C559319:YaaA protein, E coli
keywords: ab initio prediction; coevolution; contact prediction; protein structure prediction; rosetta