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Functional and informatics analysis enables glycosyltransferase activity prediction

Abstract:

The elucidation and prediction of how changes in a protein result in altered activities and selectivities remain a major challenge in chemistry. Two hurdles have prevented accurate family-wide models: obtaining (i) diverse datasets and (ii) suitable parameter frameworks that encapsulate activities in large sets. Here, we show that a relatively small but broad activity dataset is sufficient to train algorithms for functional prediction over the entire glycosyltransferase superfamily 1 (GT1) of...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Accepted Manuscript

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Publisher copy:
10.1038/s41589-018-0154-9

Authors


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Institution:
University of Oxford
Division:
MPLS Division
Department:
Chemistry
Subgroup:
Organic Chemistry
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ORCID:
0000-0002-2758-4531
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Publisher:
Nature Publishing Group Publisher's website
Journal:
Nature Chemical Biology Journal website
Volume:
14
Issue:
12
Pages:
1109-1117
Publication date:
2018-11-12
Acceptance date:
2018-09-19
DOI:
EISSN:
1552-4469
ISSN:
1552-4450
Pubs id:
pubs:943673
URN:
uri:913410fd-9cc3-4ebd-b6d3-0a67d181a122
UUID:
uuid:913410fd-9cc3-4ebd-b6d3-0a67d181a122
Local pid:
pubs:943673
Language:
English

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