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CorNet: Assigning function to networks of co-evolving residues by automated literature mining

CorNet is a web-based tool for the analysis of co-evolving residue positions in protein super-family sequence alignments. CorNet projects external information such as mutation data extracted from literature on interactively displayed groups of co-evolving residue positions to shed light on the funct...

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Autores principales: van den Bergh, Tom, Tamo, Giorgio, Nobili, Alberto, Tao, Yifeng, Tan, Tianwei, Bornscheuer, Uwe T., Kuipers, Remko K. P., Vroling, Bas, de Jong, René M., Subramanian, Kalyanasundaram, Schaap, Peter J., Desmet, Tom, Nidetzky, Bernd, Vriend, Gert, Joosten, Henk-Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5436653/
https://www.ncbi.nlm.nih.gov/pubmed/28545124
http://dx.doi.org/10.1371/journal.pone.0176427
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author van den Bergh, Tom
Tamo, Giorgio
Nobili, Alberto
Tao, Yifeng
Tan, Tianwei
Bornscheuer, Uwe T.
Kuipers, Remko K. P.
Vroling, Bas
de Jong, René M.
Subramanian, Kalyanasundaram
Schaap, Peter J.
Desmet, Tom
Nidetzky, Bernd
Vriend, Gert
Joosten, Henk-Jan
author_facet van den Bergh, Tom
Tamo, Giorgio
Nobili, Alberto
Tao, Yifeng
Tan, Tianwei
Bornscheuer, Uwe T.
Kuipers, Remko K. P.
Vroling, Bas
de Jong, René M.
Subramanian, Kalyanasundaram
Schaap, Peter J.
Desmet, Tom
Nidetzky, Bernd
Vriend, Gert
Joosten, Henk-Jan
author_sort van den Bergh, Tom
collection PubMed
description CorNet is a web-based tool for the analysis of co-evolving residue positions in protein super-family sequence alignments. CorNet projects external information such as mutation data extracted from literature on interactively displayed groups of co-evolving residue positions to shed light on the functions associated with these groups and the residues in them. We used CorNet to analyse six enzyme super-families and found that groups of strongly co-evolving residues tend to consist of residues involved in a same function such as activity, specificity, co-factor binding, or enantioselectivity. This finding allows to assign a function to residues for which no data is available yet in the literature. A mutant library was designed to mutate residues observed in a group of co-evolving residues predicted to be involved in enantioselectivity, but for which no literature data is available yet. The resulting set of mutations indeed showed many instances of increased enantioselectivity.
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spelling pubmed-54366532017-05-27 CorNet: Assigning function to networks of co-evolving residues by automated literature mining van den Bergh, Tom Tamo, Giorgio Nobili, Alberto Tao, Yifeng Tan, Tianwei Bornscheuer, Uwe T. Kuipers, Remko K. P. Vroling, Bas de Jong, René M. Subramanian, Kalyanasundaram Schaap, Peter J. Desmet, Tom Nidetzky, Bernd Vriend, Gert Joosten, Henk-Jan PLoS One Research Article CorNet is a web-based tool for the analysis of co-evolving residue positions in protein super-family sequence alignments. CorNet projects external information such as mutation data extracted from literature on interactively displayed groups of co-evolving residue positions to shed light on the functions associated with these groups and the residues in them. We used CorNet to analyse six enzyme super-families and found that groups of strongly co-evolving residues tend to consist of residues involved in a same function such as activity, specificity, co-factor binding, or enantioselectivity. This finding allows to assign a function to residues for which no data is available yet in the literature. A mutant library was designed to mutate residues observed in a group of co-evolving residues predicted to be involved in enantioselectivity, but for which no literature data is available yet. The resulting set of mutations indeed showed many instances of increased enantioselectivity. Public Library of Science 2017-05-18 /pmc/articles/PMC5436653/ /pubmed/28545124 http://dx.doi.org/10.1371/journal.pone.0176427 Text en © 2017 van den Bergh et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
van den Bergh, Tom
Tamo, Giorgio
Nobili, Alberto
Tao, Yifeng
Tan, Tianwei
Bornscheuer, Uwe T.
Kuipers, Remko K. P.
Vroling, Bas
de Jong, René M.
Subramanian, Kalyanasundaram
Schaap, Peter J.
Desmet, Tom
Nidetzky, Bernd
Vriend, Gert
Joosten, Henk-Jan
CorNet: Assigning function to networks of co-evolving residues by automated literature mining
title CorNet: Assigning function to networks of co-evolving residues by automated literature mining
title_full CorNet: Assigning function to networks of co-evolving residues by automated literature mining
title_fullStr CorNet: Assigning function to networks of co-evolving residues by automated literature mining
title_full_unstemmed CorNet: Assigning function to networks of co-evolving residues by automated literature mining
title_short CorNet: Assigning function to networks of co-evolving residues by automated literature mining
title_sort cornet: assigning function to networks of co-evolving residues by automated literature mining
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5436653/
https://www.ncbi.nlm.nih.gov/pubmed/28545124
http://dx.doi.org/10.1371/journal.pone.0176427
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