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김동혁

Kim, Donghyuk
Systems Biology and Machine Learning Lab.
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Network Context and Selection in the Evolution to Enzyme Specificity

Author(s)
Nam, HojungLewis, Nathan E.Lerman, Joshua A.Lee, Dae-HeeChang, Roger L.Kim, DonghyukPalsson, Bernhard O.
Issued Date
2012-08
DOI
10.1126/science.1216861
URI
https://scholarworks.unist.ac.kr/handle/201301/24292
Fulltext
http://science.sciencemag.org/content/337/6098/1101
Citation
SCIENCE, v.337, no.6098, pp.1101 - 1104
Abstract
Enzymes are thought to have evolved highly specific catalytic activities from promiscuous ancestral proteins. By analyzing a genome-scale model of Escherichia coli metabolism, we found that 37% of its enzymes act on a variety of substrates and catalyze 65% of the known metabolic reactions. However, it is not apparent why these generalist enzymes remain. Here, we show that there are marked differences between generalist enzymes and specialist enzymes, known to catalyze a single chemical reaction on one particular substrate in vivo. Specialist enzymes (i) are frequently essential, (ii) maintain higher metabolic flux, and (iii) require more regulation of enzyme activity to control metabolic flux in dynamic environments than do generalist enzymes. Furthermore, these properties are conserved in Archaea and Eukarya. Thus, the metabolic network context and environmental conditions influence enzyme evolution toward high specificity.
Publisher
AMER ASSOC ADVANCEMENT SCIENCE
ISSN
0036-8075
Keyword
ESCHERICHIA-COLIMETABOLIC NETWORKGENE-EXPRESSIONFLUXESYEASTRECONSTRUCTIONPROMISCUITYPERSPECTIVEMODELS

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