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Rational Engineering of Enzyme Allosteric Regulation through Sequence Evolution Analysis

Overview of attention for article published in PLoS Computational Biology, July 2012
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Title
Rational Engineering of Enzyme Allosteric Regulation through Sequence Evolution Analysis
Published in
PLoS Computational Biology, July 2012
DOI 10.1371/journal.pcbi.1002612
Pubmed ID
Authors

Jae-Seong Yang, Sang Woo Seo, Sungho Jang, Gyoo Yeol Jung, Sanguk Kim

Abstract

Control of enzyme allosteric regulation is required to drive metabolic flux toward desired levels. Although the three-dimensional (3D) structures of many enzyme-ligand complexes are available, it is still difficult to rationally engineer an allosterically regulatable enzyme without decreasing its catalytic activity. Here, we describe an effective strategy to deregulate the allosteric inhibition of enzymes based on the molecular evolution and physicochemical characteristics of allosteric ligand-binding sites. We found that allosteric sites are evolutionarily variable and comprised of more hydrophobic residues than catalytic sites. We applied our findings to design mutations in selected target residues that deregulate the allosteric activity of fructose-1,6-bisphosphatase (FBPase). Specifically, charged amino acids at less conserved positions were substituted with hydrophobic or neutral amino acids with similar sizes. The engineered proteins successfully diminished the allosteric inhibition of E. coli FBPase without affecting its catalytic efficiency. We expect that our method will aid the rational design of enzyme allosteric regulation strategies and facilitate the control of metabolic flux.

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X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 170 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 2%
Korea, Republic of 2 1%
United Kingdom 1 <1%
Canada 1 <1%
Chile 1 <1%
Russia 1 <1%
Denmark 1 <1%
Japan 1 <1%
Spain 1 <1%
Other 0 0%
Unknown 158 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 52 31%
Researcher 25 15%
Student > Master 22 13%
Student > Bachelor 17 10%
Professor > Associate Professor 11 6%
Other 22 13%
Unknown 21 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 65 38%
Biochemistry, Genetics and Molecular Biology 35 21%
Chemistry 19 11%
Chemical Engineering 6 4%
Engineering 6 4%
Other 15 9%
Unknown 24 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 March 2014.
All research outputs
#15,739,010
of 25,373,627 outputs
Outputs from PLoS Computational Biology
#6,753
of 8,960 outputs
Outputs of similar age
#107,296
of 177,933 outputs
Outputs of similar age from PLoS Computational Biology
#79
of 114 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,960 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 177,933 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 114 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.