GalaxyRefine2: simultaneous refinement of inaccurate local regions and overall protein structure.
Journal
Nucleic acids research
ISSN: 1362-4962
Titre abrégé: Nucleic Acids Res
Pays: England
ID NLM: 0411011
Informations de publication
Date de publication:
02 07 2019
02 07 2019
Historique:
accepted:
11
04
2019
revised:
01
04
2019
received:
31
01
2019
pubmed:
20
4
2019
medline:
20
5
2020
entrez:
20
4
2019
Statut:
ppublish
Résumé
The 3D structure of a protein can be predicted from its amino acid sequence with high accuracy for a large fraction of cases because of the availability of large quantities of experimental data and the advance of computational algorithms. Recently, deep learning methods exploiting the coevolution information obtained by comparing related protein sequences have been successfully used to generate highly accurate model structures even in the absence of template structure information. However, structures predicted based on either template structures or related sequences require further improvement in regions for which information is missing. Refining a predicted protein structure with insufficient information on certain regions is critical because these regions may be connected to functional specificity that is not conserved among related proteins. The GalaxyRefine2 web server, freely available via http://galaxy.seoklab.org/refine2, is an upgraded version of the GalaxyRefine protein structure refinement server and reflects recent developments successfully tested through CASP blind prediction experiments. This method adopts an iterative optimization approach involving various structure move sets to refine both local and global structures. The estimation of local error and hybridization of available homolog structures are also employed for effective conformation search.
Identifiants
pubmed: 31001635
pii: 5475172
doi: 10.1093/nar/gkz288
pmc: PMC6602442
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
W451-W455Informations de copyright
© The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.
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