Experimental and computational investigation of enzyme functional annotations uncovers misannotation in the EC 1.1.3.15 enzyme class.

Only a small fraction of genes deposited to databases have been experimentally characterised. The majority of proteins have their function assigned automatically, which can result in erroneous annotations. The reliability of current annotations in public databases is largely unknown; experimental at...

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Autores principales:	Elzbieta Rembeza, Martin K M Engqvist
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/9d656493b80a40cea28c4f707d8fb1a1
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spelling	oai:doaj.org-article:9d656493b80a40cea28c4f707d8fb1a12021-12-02T19:57:44ZExperimental and computational investigation of enzyme functional annotations uncovers misannotation in the EC 1.1.3.15 enzyme class.1553-734X1553-735810.1371/journal.pcbi.1009446https://doaj.org/article/9d656493b80a40cea28c4f707d8fb1a12021-09-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009446https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Only a small fraction of genes deposited to databases have been experimentally characterised. The majority of proteins have their function assigned automatically, which can result in erroneous annotations. The reliability of current annotations in public databases is largely unknown; experimental attempts to validate the accuracy within individual enzyme classes are lacking. In this study we performed an overview of functional annotations to the BRENDA enzyme database. We first applied a high-throughput experimental platform to verify functional annotations to an enzyme class of S-2-hydroxyacid oxidases (EC 1.1.3.15). We chose 122 representative sequences of the class and screened them for their predicted function. Based on the experimental results, predicted domain architecture and similarity to previously characterised S-2-hydroxyacid oxidases, we inferred that at least 78% of sequences in the enzyme class are misannotated. We experimentally confirmed four alternative activities among the misannotated sequences and showed that misannotation in the enzyme class increased over time. Finally, we performed a computational analysis of annotations to all enzyme classes in the BRENDA database, and showed that nearly 18% of all sequences are annotated to an enzyme class while sharing no similarity or domain architecture to experimentally characterised representatives. We showed that even well-studied enzyme classes of industrial relevance are affected by the problem of functional misannotation.Elzbieta RembezaMartin K M EngqvistPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 9, p e1009446 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Elzbieta Rembeza Martin K M Engqvist Experimental and computational investigation of enzyme functional annotations uncovers misannotation in the EC 1.1.3.15 enzyme class.
description	Only a small fraction of genes deposited to databases have been experimentally characterised. The majority of proteins have their function assigned automatically, which can result in erroneous annotations. The reliability of current annotations in public databases is largely unknown; experimental attempts to validate the accuracy within individual enzyme classes are lacking. In this study we performed an overview of functional annotations to the BRENDA enzyme database. We first applied a high-throughput experimental platform to verify functional annotations to an enzyme class of S-2-hydroxyacid oxidases (EC 1.1.3.15). We chose 122 representative sequences of the class and screened them for their predicted function. Based on the experimental results, predicted domain architecture and similarity to previously characterised S-2-hydroxyacid oxidases, we inferred that at least 78% of sequences in the enzyme class are misannotated. We experimentally confirmed four alternative activities among the misannotated sequences and showed that misannotation in the enzyme class increased over time. Finally, we performed a computational analysis of annotations to all enzyme classes in the BRENDA database, and showed that nearly 18% of all sequences are annotated to an enzyme class while sharing no similarity or domain architecture to experimentally characterised representatives. We showed that even well-studied enzyme classes of industrial relevance are affected by the problem of functional misannotation.
format	article
author	Elzbieta Rembeza Martin K M Engqvist
author_facet	Elzbieta Rembeza Martin K M Engqvist
author_sort	Elzbieta Rembeza
title	Experimental and computational investigation of enzyme functional annotations uncovers misannotation in the EC 1.1.3.15 enzyme class.
title_short	Experimental and computational investigation of enzyme functional annotations uncovers misannotation in the EC 1.1.3.15 enzyme class.
title_full	Experimental and computational investigation of enzyme functional annotations uncovers misannotation in the EC 1.1.3.15 enzyme class.
title_fullStr	Experimental and computational investigation of enzyme functional annotations uncovers misannotation in the EC 1.1.3.15 enzyme class.
title_full_unstemmed	Experimental and computational investigation of enzyme functional annotations uncovers misannotation in the EC 1.1.3.15 enzyme class.
title_sort	experimental and computational investigation of enzyme functional annotations uncovers misannotation in the ec 1.1.3.15 enzyme class.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/9d656493b80a40cea28c4f707d8fb1a1
work_keys_str_mv	AT elzbietarembeza experimentalandcomputationalinvestigationofenzymefunctionalannotationsuncoversmisannotationintheec11315enzymeclass AT martinkmengqvist experimentalandcomputationalinvestigationofenzymefunctionalannotationsuncoversmisannotationintheec11315enzymeclass
_version_	1718375792299212800

Experimental and computational investigation of enzyme functional annotations uncovers misannotation in the EC 1.1.3.15 enzyme class.

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