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Alternate States of Proteins Revealed by Detailed Energy Landscape Mapping

Tyka, Michael D.; Keedy, Daniel A.; André, Ingemar LU ; DiMaio, Frank; Song, Yifan; Richardson, David C.; Richardson, Jane S. and Baker, David (2011) In Journal of Molecular Biology 405(2). p.607-618
Abstract
What conformations do protein molecules populate in solution? Crystallography provides a high-resolution description of protein structure in the crystal environment, while NMR describes structure in solution but using less data. NMR structures display more variability, but is this because crystal contacts are absent or because of fewer data constraints? Here we report unexpected insight into this issue obtained through analysis of de tailed protein energy landscapes generated by large-scale, native-enhanced sampling of conformational space with Rosetta@home for 111 protein domains. In the absence of tightly associating binding partners or ligands, the lowest-energy Rosetta models were nearly all <2.5 angstrom C alpha RMSD from the... (More)
What conformations do protein molecules populate in solution? Crystallography provides a high-resolution description of protein structure in the crystal environment, while NMR describes structure in solution but using less data. NMR structures display more variability, but is this because crystal contacts are absent or because of fewer data constraints? Here we report unexpected insight into this issue obtained through analysis of de tailed protein energy landscapes generated by large-scale, native-enhanced sampling of conformational space with Rosetta@home for 111 protein domains. In the absence of tightly associating binding partners or ligands, the lowest-energy Rosetta models were nearly all <2.5 angstrom C alpha RMSD from the experimental structure; this result demonstrates that structure prediction accuracy for globular proteins is limited mainly by the ability to sample close to the native structure. While the lowest-energy models are similar to deposited structures, they are not identical; the largest deviations are most often in regions involved in ligand, quaternary, or crystal contacts. For ligand binding proteins, the low energy models may resemble the apo structures, and for oligomeric proteins, the monomeric assembly intermediates. The deviations between the low energy models and crystal structures largely disappear when landscapes are computed in the context of the crystal lattice or multimer. The computed low-energy ensembles, with tight crystal-structure-like packing in the core, but more NMR-structure-like variability in loops, may in some cases resemble the native state ensembles of proteins better than individual crystal or NMR structures, and can suggest experimentally testable hypotheses relating alternative states and structural heterogeneity to function. (C) 2010 Elsevier Ltd. All rights reserved. (Less)
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author
organization
publishing date
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Contribution to journal
publication status
published
subject
keywords
Rosetta, alternative conformations, protein mobility, structure, prediction, validation
in
Journal of Molecular Biology
volume
405
issue
2
pages
607 - 618
publisher
Elsevier
external identifiers
  • wos:000286850300022
  • scopus:78650918983
ISSN
1089-8638
DOI
10.1016/j.jmb.2010.11.008
language
English
LU publication?
yes
id
2817b467-0b2c-44c2-a88c-cfa82325cc39 (old id 1882458)
date added to LUP
2011-04-01 08:42:35
date last changed
2017-10-22 04:19:42
@article{2817b467-0b2c-44c2-a88c-cfa82325cc39,
  abstract     = {What conformations do protein molecules populate in solution? Crystallography provides a high-resolution description of protein structure in the crystal environment, while NMR describes structure in solution but using less data. NMR structures display more variability, but is this because crystal contacts are absent or because of fewer data constraints? Here we report unexpected insight into this issue obtained through analysis of de tailed protein energy landscapes generated by large-scale, native-enhanced sampling of conformational space with Rosetta@home for 111 protein domains. In the absence of tightly associating binding partners or ligands, the lowest-energy Rosetta models were nearly all &lt;2.5 angstrom C alpha RMSD from the experimental structure; this result demonstrates that structure prediction accuracy for globular proteins is limited mainly by the ability to sample close to the native structure. While the lowest-energy models are similar to deposited structures, they are not identical; the largest deviations are most often in regions involved in ligand, quaternary, or crystal contacts. For ligand binding proteins, the low energy models may resemble the apo structures, and for oligomeric proteins, the monomeric assembly intermediates. The deviations between the low energy models and crystal structures largely disappear when landscapes are computed in the context of the crystal lattice or multimer. The computed low-energy ensembles, with tight crystal-structure-like packing in the core, but more NMR-structure-like variability in loops, may in some cases resemble the native state ensembles of proteins better than individual crystal or NMR structures, and can suggest experimentally testable hypotheses relating alternative states and structural heterogeneity to function. (C) 2010 Elsevier Ltd. All rights reserved.},
  author       = {Tyka, Michael D. and Keedy, Daniel A. and André, Ingemar and DiMaio, Frank and Song, Yifan and Richardson, David C. and Richardson, Jane S. and Baker, David},
  issn         = {1089-8638},
  keyword      = {Rosetta,alternative conformations,protein mobility,structure,prediction,validation},
  language     = {eng},
  number       = {2},
  pages        = {607--618},
  publisher    = {Elsevier},
  series       = {Journal of Molecular Biology},
  title        = {Alternate States of Proteins Revealed by Detailed Energy Landscape Mapping},
  url          = {http://dx.doi.org/10.1016/j.jmb.2010.11.008},
  volume       = {405},
  year         = {2011},
}