Reference : Confronting the catalytic dark matter encoded by sequenced genomes
Scientific journals : Article
Life sciences : Biochemistry, biophysics & molecular biology
Life sciences : Genetics & genetic processes
Systems Biomedicine
http://hdl.handle.net/10993/32682
Confronting the catalytic dark matter encoded by sequenced genomes
English
Ellens, Kenneth W. []
Christian, Nils []
Satagopam, Venkata mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
May, Patrick mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Linster, Carole mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
16-Nov-2017
Nucleic Acids Research
Oxford University Press
45
20
11495-11514
Yes (verified by ORBilu)
International
0305-1048
1362-4962
Oxford
United Kingdom
[en] Proteins of unknown function ; Enzymes ; Genome annotation ; metabolism ; proteome ; yeasts
[en] The post-genomic era has provided researchers with a deluge of protein sequences. However, a significant fraction of the proteins encoded by sequenced genomes remains without an identified function. Here, we aim at determining how many enzymes of uncertain or unknown function are still present in the Saccharomyces cerevisiae and human proteomes. Using information available in the Swiss-Prot, BRENDA and KEGG databases in combination with a Hidden Markov Model-based method, we estimate that >600 yeast and 2000 human proteins (>30% of their proteins of unknown function) are enzymes whose precise function(s) remain(s) to be determined. This illustrates the impressive scale of the ‘unknown enzyme problem’. We extensively review classical biochemical as well as more recent systematic experimental and computational approaches that can be used to support enzyme function discovery research. Finally, we discuss the possible roles of the elusive catalysts in light of recent developments in the fields of enzymology and metabolism as well as the significance of the unknown enzyme problem in the context of metabolic modeling, metabolic engineering and rare disease research.
Luxembourg Centre for Systems Biomedicine (LCSB): Enzymology & Metabolism (Linster Group) ; Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) ; University of Luxembourg: High Performance Computing - ULHPC
Researchers
http://hdl.handle.net/10993/32682
10.1093/nar/gkx937

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