Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints

Prediction of protein structures on the scale of genomes remains a challenge. Here the authors introduce a protein structure prediction method that uses deep learning to predict inter-atomic distances, torsion angles and hydrogen bonds, and apply it to predict the structures of 1475 Pfam domains.

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Autores principales:	Joe G. Greener, Shaun M. Kandathil, David T. Jones
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/ccdc53de641e49ecb1dcddc994cc5c94
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spelling	oai:doaj.org-article:ccdc53de641e49ecb1dcddc994cc5c942021-12-02T14:39:00ZDeep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints10.1038/s41467-019-11994-02041-1723https://doaj.org/article/ccdc53de641e49ecb1dcddc994cc5c942019-09-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-11994-0https://doaj.org/toc/2041-1723Prediction of protein structures on the scale of genomes remains a challenge. Here the authors introduce a protein structure prediction method that uses deep learning to predict inter-atomic distances, torsion angles and hydrogen bonds, and apply it to predict the structures of 1475 Pfam domains.Joe G. GreenerShaun M. KandathilDavid T. JonesNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-13 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Joe G. Greener Shaun M. Kandathil David T. Jones Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints
description	Prediction of protein structures on the scale of genomes remains a challenge. Here the authors introduce a protein structure prediction method that uses deep learning to predict inter-atomic distances, torsion angles and hydrogen bonds, and apply it to predict the structures of 1475 Pfam domains.
format	article
author	Joe G. Greener Shaun M. Kandathil David T. Jones
author_facet	Joe G. Greener Shaun M. Kandathil David T. Jones
author_sort	Joe G. Greener
title	Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints
title_short	Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints
title_full	Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints
title_fullStr	Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints
title_full_unstemmed	Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints
title_sort	deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/ccdc53de641e49ecb1dcddc994cc5c94
work_keys_str_mv	AT joeggreener deeplearningextendsdenovoproteinmodellingcoverageofgenomesusingiterativelypredictedstructuralconstraints AT shaunmkandathil deeplearningextendsdenovoproteinmodellingcoverageofgenomesusingiterativelypredictedstructuralconstraints AT davidtjones deeplearningextendsdenovoproteinmodellingcoverageofgenomesusingiterativelypredictedstructuralconstraints
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Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints

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