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Ensemble-based evaluation for protein structure models
Motivation: Comparing protein tertiary structures is a fundamental procedure in structural biology and protein bioinformatics. Structure comparison is important particularly for evaluating computational protein structure models. Most of the model structure evaluation methods perform rigid body super...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4908346/ https://www.ncbi.nlm.nih.gov/pubmed/27307633 http://dx.doi.org/10.1093/bioinformatics/btw262 |
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author | Jamroz, Michal Kolinski, Andrzej Kihara, Daisuke |
author_facet | Jamroz, Michal Kolinski, Andrzej Kihara, Daisuke |
author_sort | Jamroz, Michal |
collection | PubMed |
description | Motivation: Comparing protein tertiary structures is a fundamental procedure in structural biology and protein bioinformatics. Structure comparison is important particularly for evaluating computational protein structure models. Most of the model structure evaluation methods perform rigid body superimposition of a structure model to its crystal structure and measure the difference of the corresponding residue or atom positions between them. However, these methods neglect intrinsic flexibility of proteins by treating the native structure as a rigid molecule. Because different parts of proteins have different levels of flexibility, for example, exposed loop regions are usually more flexible than the core region of a protein structure, disagreement of a model to the native needs to be evaluated differently depending on the flexibility of residues in a protein. Results: We propose a score named FlexScore for comparing protein structures that consider flexibility of each residue in the native state of proteins. Flexibility information may be extracted from experiments such as NMR or molecular dynamics simulation. FlexScore considers an ensemble of conformations of a protein described as a multivariate Gaussian distribution of atomic displacements and compares a query computational model with the ensemble. We compare FlexScore with other commonly used structure similarity scores over various examples. FlexScore agrees with experts’ intuitive assessment of computational models and provides information of practical usefulness of models. Availability and implementation: https://bitbucket.org/mjamroz/flexscore Contact: dkihara@purdue.edu Supplementary information: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-4908346 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-49083462016-06-17 Ensemble-based evaluation for protein structure models Jamroz, Michal Kolinski, Andrzej Kihara, Daisuke Bioinformatics Ismb 2016 Proceedings July 8 to July 12, 2016, Orlando, Florida Motivation: Comparing protein tertiary structures is a fundamental procedure in structural biology and protein bioinformatics. Structure comparison is important particularly for evaluating computational protein structure models. Most of the model structure evaluation methods perform rigid body superimposition of a structure model to its crystal structure and measure the difference of the corresponding residue or atom positions between them. However, these methods neglect intrinsic flexibility of proteins by treating the native structure as a rigid molecule. Because different parts of proteins have different levels of flexibility, for example, exposed loop regions are usually more flexible than the core region of a protein structure, disagreement of a model to the native needs to be evaluated differently depending on the flexibility of residues in a protein. Results: We propose a score named FlexScore for comparing protein structures that consider flexibility of each residue in the native state of proteins. Flexibility information may be extracted from experiments such as NMR or molecular dynamics simulation. FlexScore considers an ensemble of conformations of a protein described as a multivariate Gaussian distribution of atomic displacements and compares a query computational model with the ensemble. We compare FlexScore with other commonly used structure similarity scores over various examples. FlexScore agrees with experts’ intuitive assessment of computational models and provides information of practical usefulness of models. Availability and implementation: https://bitbucket.org/mjamroz/flexscore Contact: dkihara@purdue.edu Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2016-06-15 2016-06-11 /pmc/articles/PMC4908346/ /pubmed/27307633 http://dx.doi.org/10.1093/bioinformatics/btw262 Text en © The Author 2016. Published by Oxford University Press. 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 re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Ismb 2016 Proceedings July 8 to July 12, 2016, Orlando, Florida Jamroz, Michal Kolinski, Andrzej Kihara, Daisuke Ensemble-based evaluation for protein structure models |
title | Ensemble-based evaluation for protein structure models |
title_full | Ensemble-based evaluation for protein structure models |
title_fullStr | Ensemble-based evaluation for protein structure models |
title_full_unstemmed | Ensemble-based evaluation for protein structure models |
title_short | Ensemble-based evaluation for protein structure models |
title_sort | ensemble-based evaluation for protein structure models |
topic | Ismb 2016 Proceedings July 8 to July 12, 2016, Orlando, Florida |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4908346/ https://www.ncbi.nlm.nih.gov/pubmed/27307633 http://dx.doi.org/10.1093/bioinformatics/btw262 |
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