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CABS-fold: server for the de novo and consensus-based prediction of protein structure

The CABS-fold web server provides tools for protein structure prediction from sequence only (de novo modeling) and also using alternative templates (consensus modeling). The web server is based on the CABS modeling procedures ranked in previous Critical Assessment of techniques for protein Structure...

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Detalles Bibliográficos
Autores principales: Blaszczyk, Maciej, Jamroz, Michal, Kmiecik, Sebastian, Kolinski, Andrzej
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3692050/
https://www.ncbi.nlm.nih.gov/pubmed/23748950
http://dx.doi.org/10.1093/nar/gkt462
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author Blaszczyk, Maciej
Jamroz, Michal
Kmiecik, Sebastian
Kolinski, Andrzej
author_facet Blaszczyk, Maciej
Jamroz, Michal
Kmiecik, Sebastian
Kolinski, Andrzej
author_sort Blaszczyk, Maciej
collection PubMed
description The CABS-fold web server provides tools for protein structure prediction from sequence only (de novo modeling) and also using alternative templates (consensus modeling). The web server is based on the CABS modeling procedures ranked in previous Critical Assessment of techniques for protein Structure Prediction competitions as one of the leading approaches for de novo and template-based modeling. Except for template data, fragmentary distance restraints can also be incorporated into the modeling process. The web server output is a coarse-grained trajectory of generated conformations, its Jmol representation and predicted models in all-atom resolution (together with accompanying analysis). CABS-fold can be freely accessed at http://biocomp.chem.uw.edu.pl/CABSfold.
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spelling pubmed-36920502013-06-25 CABS-fold: server for the de novo and consensus-based prediction of protein structure Blaszczyk, Maciej Jamroz, Michal Kmiecik, Sebastian Kolinski, Andrzej Nucleic Acids Res Articles The CABS-fold web server provides tools for protein structure prediction from sequence only (de novo modeling) and also using alternative templates (consensus modeling). The web server is based on the CABS modeling procedures ranked in previous Critical Assessment of techniques for protein Structure Prediction competitions as one of the leading approaches for de novo and template-based modeling. Except for template data, fragmentary distance restraints can also be incorporated into the modeling process. The web server output is a coarse-grained trajectory of generated conformations, its Jmol representation and predicted models in all-atom resolution (together with accompanying analysis). CABS-fold can be freely accessed at http://biocomp.chem.uw.edu.pl/CABSfold. Oxford University Press 2013-07 2013-06-08 /pmc/articles/PMC3692050/ /pubmed/23748950 http://dx.doi.org/10.1093/nar/gkt462 Text en © The Author(s) 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Blaszczyk, Maciej
Jamroz, Michal
Kmiecik, Sebastian
Kolinski, Andrzej
CABS-fold: server for the de novo and consensus-based prediction of protein structure
title CABS-fold: server for the de novo and consensus-based prediction of protein structure
title_full CABS-fold: server for the de novo and consensus-based prediction of protein structure
title_fullStr CABS-fold: server for the de novo and consensus-based prediction of protein structure
title_full_unstemmed CABS-fold: server for the de novo and consensus-based prediction of protein structure
title_short CABS-fold: server for the de novo and consensus-based prediction of protein structure
title_sort cabs-fold: server for the de novo and consensus-based prediction of protein structure
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3692050/
https://www.ncbi.nlm.nih.gov/pubmed/23748950
http://dx.doi.org/10.1093/nar/gkt462
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