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Collective repacking reveals that the structures of protein cores are uniquely specified by steric repulsive interactions
Protein core repacking is a standard test of protein modeling software. A recent study of six different modeling software packages showed that they are more successful at predicting side chain conformations of core compared to surface residues. All the modeling software tested have multicomponent en...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7263838/ https://www.ncbi.nlm.nih.gov/pubmed/28201818 http://dx.doi.org/10.1093/protein/gzx011 |
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author | Gaines, J.C. Virrueta, A. Buch, D.A. Fleishman, S.J. O'Hern, C.S. Regan, L. |
author_facet | Gaines, J.C. Virrueta, A. Buch, D.A. Fleishman, S.J. O'Hern, C.S. Regan, L. |
author_sort | Gaines, J.C. |
collection | PubMed |
description | Protein core repacking is a standard test of protein modeling software. A recent study of six different modeling software packages showed that they are more successful at predicting side chain conformations of core compared to surface residues. All the modeling software tested have multicomponent energy functions, typically including contributions from solvation, electrostatics, hydrogen bonding and Lennard–Jones interactions in addition to statistical terms based on observed protein structures. We investigated to what extent a simplified energy function that includes only stereochemical constraints and repulsive hard-sphere interactions can correctly repack protein cores. For single residue and collective repacking, the hard-sphere model accurately recapitulates the observed side chain conformations for Ile, Leu, Phe, Thr, Trp, Tyr and Val. This result shows that there are no alternative, sterically allowed side chain conformations of core residues. Analysis of the same set of protein cores using the Rosetta software suite revealed that the hard-sphere model and Rosetta perform equally well on Ile, Leu, Phe, Thr and Val; the hard-sphere model performs better on Trp and Tyr and Rosetta performs better on Ser. We conclude that the high prediction accuracy in protein cores obtained by protein modeling software and our simplified hard-sphere approach reflects the high density of protein cores and dominance of steric repulsion. |
format | Online Article Text |
id | pubmed-7263838 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-72638382020-06-09 Collective repacking reveals that the structures of protein cores are uniquely specified by steric repulsive interactions Gaines, J.C. Virrueta, A. Buch, D.A. Fleishman, S.J. O'Hern, C.S. Regan, L. Protein Eng Des Sel Original Article Protein core repacking is a standard test of protein modeling software. A recent study of six different modeling software packages showed that they are more successful at predicting side chain conformations of core compared to surface residues. All the modeling software tested have multicomponent energy functions, typically including contributions from solvation, electrostatics, hydrogen bonding and Lennard–Jones interactions in addition to statistical terms based on observed protein structures. We investigated to what extent a simplified energy function that includes only stereochemical constraints and repulsive hard-sphere interactions can correctly repack protein cores. For single residue and collective repacking, the hard-sphere model accurately recapitulates the observed side chain conformations for Ile, Leu, Phe, Thr, Trp, Tyr and Val. This result shows that there are no alternative, sterically allowed side chain conformations of core residues. Analysis of the same set of protein cores using the Rosetta software suite revealed that the hard-sphere model and Rosetta perform equally well on Ile, Leu, Phe, Thr and Val; the hard-sphere model performs better on Trp and Tyr and Rosetta performs better on Ser. We conclude that the high prediction accuracy in protein cores obtained by protein modeling software and our simplified hard-sphere approach reflects the high density of protein cores and dominance of steric repulsion. Oxford University Press 2017-05 2017-02-15 /pmc/articles/PMC7263838/ /pubmed/28201818 http://dx.doi.org/10.1093/protein/gzx011 Text en © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Original Article Gaines, J.C. Virrueta, A. Buch, D.A. Fleishman, S.J. O'Hern, C.S. Regan, L. Collective repacking reveals that the structures of protein cores are uniquely specified by steric repulsive interactions |
title | Collective repacking reveals that the structures of protein cores are
uniquely specified by steric repulsive interactions |
title_full | Collective repacking reveals that the structures of protein cores are
uniquely specified by steric repulsive interactions |
title_fullStr | Collective repacking reveals that the structures of protein cores are
uniquely specified by steric repulsive interactions |
title_full_unstemmed | Collective repacking reveals that the structures of protein cores are
uniquely specified by steric repulsive interactions |
title_short | Collective repacking reveals that the structures of protein cores are
uniquely specified by steric repulsive interactions |
title_sort | collective repacking reveals that the structures of protein cores are
uniquely specified by steric repulsive interactions |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7263838/ https://www.ncbi.nlm.nih.gov/pubmed/28201818 http://dx.doi.org/10.1093/protein/gzx011 |
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