Functional and informatics analysis enables glycosyltransferase activity prediction

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 i...

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Veröffentlicht in:	Nature chemical biology 2018-12, Vol.14 (12), p.1109-1117
Hauptverfasser:	Yang, Min, Fehl, Charlie, Lees, Karen V., Lim, Eng-Kiat, Offen, Wendy A., Davies, Gideon J., Bowles, Dianna J., Davidson, Matthew G., Roberts, Stephen J., Davis, Benjamin G.
Format:	Artikel
Sprache:	eng
Schlagworte:	631/92/603 631/92/607 631/92/72 639/638/630 Algorithms Annotations Arabidopsis Proteins - chemistry Arabidopsis Proteins - genetics Arabidopsis Proteins - metabolism Biocatalysts Biochemical Engineering Biochemistry Bioorganic Chemistry Catalytic Domain Cell Biology Chemistry Chemistry and Materials Science Chemistry/Food Science Computational Biology - methods Decision analysis Feature recognition Glucosyltransferases - chemistry Glucosyltransferases - metabolism Glycosyltransferase Glycosyltransferases - chemistry Glycosyltransferases - metabolism Informatics Mathematical models Modulators Mutagenesis, Site-Directed Novobiocin - metabolism Organic chemistry Pattern recognition Phylogeny Proteins Resveratrol - metabolism Structure-Activity Relationship Substrates
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