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How Protein Stability and New Functions Trade Off

Overview of attention for article published in PLoS Computational Biology, February 2008
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

Mentioned by

blogs
1 blog
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1 X user
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2 patents
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1 research highlight platform

Citations

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486 Dimensions

Readers on

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580 Mendeley
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6 CiteULike
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1 Connotea
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Title
How Protein Stability and New Functions Trade Off
Published in
PLoS Computational Biology, February 2008
DOI 10.1371/journal.pcbi.1000002
Pubmed ID
Authors

Nobuhiko Tokuriki, Francois Stricher, Luis Serrano, Dan S. Tawfik

Abstract

Numerous studies have noted that the evolution of new enzymatic specificities is accompanied by loss of the protein's thermodynamic stability (DeltaDeltaG), thus suggesting a tradeoff between the acquisition of new enzymatic functions and stability. However, since most mutations are destabilizing (DeltaDeltaG>0), one should ask how destabilizing mutations that confer new or altered enzymatic functions relative to all other mutations are. We applied DeltaDeltaG computations by FoldX to analyze the effects of 548 mutations that arose from the directed evolution of 22 different enzymes. The stability effects, location, and type of function-altering mutations were compared to DeltaDeltaG changes arising from all possible point mutations in the same enzymes. We found that mutations that modulate enzymatic functions are mostly destabilizing (average DeltaDeltaG = +0.9 kcal/mol), and are almost as destabilizing as the "average" mutation in these enzymes (+1.3 kcal/mol). Although their stability effects are not as dramatic as in key catalytic residues, mutations that modify the substrate binding pockets, and thus mediate new enzymatic specificities, place a larger stability burden than surface mutations that underline neutral, non-adaptive evolutionary changes. How are the destabilizing effects of functional mutations balanced to enable adaptation? Our analysis also indicated that many mutations that appear in directed evolution variants with no obvious role in the new function exert stabilizing effects that may compensate for the destabilizing effects of the crucial function-altering mutations. Thus, the evolution of new enzymatic activities, both in nature and in the laboratory, is dependent on the compensatory, stabilizing effect of apparently "silent" mutations in regions of the protein that are irrelevant to its function.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 580 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 14 2%
Germany 6 1%
United Kingdom 4 <1%
Argentina 4 <1%
India 4 <1%
Japan 3 <1%
Spain 3 <1%
Canada 3 <1%
France 2 <1%
Other 12 2%
Unknown 525 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 176 30%
Researcher 124 21%
Student > Bachelor 52 9%
Student > Master 50 9%
Professor > Associate Professor 35 6%
Other 83 14%
Unknown 60 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 226 39%
Biochemistry, Genetics and Molecular Biology 156 27%
Chemistry 41 7%
Computer Science 18 3%
Engineering 13 2%
Other 43 7%
Unknown 83 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 20 September 2023.
All research outputs
#2,409,937
of 25,373,627 outputs
Outputs from PLoS Computational Biology
#2,161
of 8,960 outputs
Outputs of similar age
#6,740
of 94,797 outputs
Outputs of similar age from PLoS Computational Biology
#10
of 39 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
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 has done well, scoring higher than 75% of its peers.
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 94,797 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 39 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.