Residue contacts predicted by evolutionary covariance extend the application of ab initio molecular replacement to larger and more challenging protein folds

dc.contributor.authorSimkovic, Felix
dc.contributor.authorThomas, Jens M. H.
dc.contributor.authorKeegan, Ronan M.
dc.contributor.authorWinn, Martyn D.
dc.contributor.authorMayans, Olga
dc.contributor.authorRigden, Daniel J.
dc.date.accessioned2016-08-09T13:35:05Z
dc.date.available2016-08-09T13:35:05Z
dc.date.issued2016-07-01eng
dc.description.abstractFor many protein families, the deluge of new sequence information together with new statistical protocols now allow the accurate prediction of contacting residues from sequence information alone. This offers the possibility of more accurate ab initio (non-homology-based) structure prediction. Such models can be used in structure solution by molecular replacement (MR) where the target fold is novel or is only distantly related to known structures. Here, AMPLE, an MR pipeline that assembles search-model ensembles from ab initio structure predictions (`decoys'), is employed to assess the value of contact-assisted ab initio models to the crystallographer. It is demonstrated that evolutionary covariance-derived residue–residue contact predictions improve the quality of ab initio models and, consequently, the success rate of MR using search models derived from them. For targets containing β-structure, decoy quality and MR performance were further improved by the use of a β-strand contact-filtering protocol. Such contact-guided decoys achieved 14 structure solutions from 21 attempted protein targets, compared with nine for simple Rosetta decoys. Previously encountered limitations were superseded in two key respects. Firstly, much larger targets of up to 221 residues in length were solved, which is far larger than the previously benchmarked threshold of 120 residues. Secondly, contact-guided decoys significantly improved success with β-sheet-rich proteins. Overall, the improved performance of contact-guided decoys suggests that MR is now applicable to a significantly wider range of protein targets than were previously tractable, and points to a direct benefit to structural biology from the recent remarkable advances in sequencing.eng
dc.description.versionpublishedeng
dc.identifier.doi10.1107/S2052252516008113eng
dc.identifier.ppn475836162
dc.identifier.urihttps://kops.uni-konstanz.de/handle/123456789/34989
dc.language.isoengeng
dc.rightsterms-of-use
dc.rights.urihttps://rightsstatements.org/page/InC/1.0/
dc.subjectmolecular replacement; protein structure prediction; evolutionary covariation; predicted contacts; ab initio modellingeng
dc.subject.ddc570eng
dc.titleResidue contacts predicted by evolutionary covariance extend the application of ab initio molecular replacement to larger and more challenging protein foldseng
dc.typeJOURNAL_ARTICLEeng
dspace.entity.typePublication
kops.citation.bibtex
@article{Simkovic2016-07-01Resid-34989,
  year={2016},
  doi={10.1107/S2052252516008113},
  title={Residue contacts predicted by evolutionary covariance extend the application of ab initio molecular replacement to larger and more challenging protein folds},
  number={4},
  volume={3},
  journal={IUCrJ},
  pages={259--270},
  author={Simkovic, Felix and Thomas, Jens M. H. and Keegan, Ronan M. and Winn, Martyn D. and Mayans, Olga and Rigden, Daniel J.}
}
kops.citation.iso690SIMKOVIC, Felix, Jens M. H. THOMAS, Ronan M. KEEGAN, Martyn D. WINN, Olga MAYANS, Daniel J. RIGDEN, 2016. Residue contacts predicted by evolutionary covariance extend the application of ab initio molecular replacement to larger and more challenging protein folds. In: IUCrJ. 2016, 3(4), pp. 259-270. eISSN 2052-2525. Available under: doi: 10.1107/S2052252516008113deu
kops.citation.iso690SIMKOVIC, Felix, Jens M. H. THOMAS, Ronan M. KEEGAN, Martyn D. WINN, Olga MAYANS, Daniel J. RIGDEN, 2016. Residue contacts predicted by evolutionary covariance extend the application of ab initio molecular replacement to larger and more challenging protein folds. In: IUCrJ. 2016, 3(4), pp. 259-270. eISSN 2052-2525. Available under: doi: 10.1107/S2052252516008113eng
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