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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...

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Autores principales: Jamroz, Michal, Kolinski, Andrzej, Kihara, Daisuke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
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.
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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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