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Evolutionary Optimization of Protein Folding

Overview of attention for article published in PLoS Computational Biology, January 2013
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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 (95th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Citations

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48 Dimensions

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mendeley
117 Mendeley
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6 CiteULike
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Title
Evolutionary Optimization of Protein Folding
Published in
PLoS Computational Biology, January 2013
DOI 10.1371/journal.pcbi.1002861
Pubmed ID
Authors

Cédric Debès, Minglei Wang, Gustavo Caetano-Anollés, Frauke Gräter

Abstract

Nature has shaped the make up of proteins since their appearance, [Formula: see text]3.8 billion years ago. However, the fundamental drivers of structural change responsible for the extraordinary diversity of proteins have yet to be elucidated. Here we explore if protein evolution affects folding speed. We estimated folding times for the present-day catalog of protein domains directly from their size-modified contact order. These values were mapped onto an evolutionary timeline of domain appearance derived from a phylogenomic analysis of protein domains in 989 fully-sequenced genomes. Our results show a clear overall increase of folding speed during evolution, with known ultra-fast downhill folders appearing rather late in the timeline. Remarkably, folding optimization depends on secondary structure. While alpha-folds showed a tendency to fold faster throughout evolution, beta-folds exhibited a trend of folding time increase during the last [Formula: see text]1.5 billion years that began during the "big bang" of domain combinations. As a consequence, these domain structures are on average slow folders today. Our results suggest that fast and efficient folding of domains shaped the universe of protein structure. This finding supports the hypothesis that optimization of the kinetic and thermodynamic accessibility of the native fold reduces protein aggregation propensities that hamper cellular functions.

X Demographics

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 117 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 4%
Hungary 1 <1%
Germany 1 <1%
Korea, Republic of 1 <1%
India 1 <1%
United Kingdom 1 <1%
France 1 <1%
Peru 1 <1%
Canada 1 <1%
Other 2 2%
Unknown 102 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 38 32%
Researcher 24 21%
Student > Bachelor 12 10%
Student > Master 10 9%
Professor 7 6%
Other 17 15%
Unknown 9 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 59 50%
Biochemistry, Genetics and Molecular Biology 21 18%
Computer Science 7 6%
Chemistry 7 6%
Physics and Astronomy 4 3%
Other 7 6%
Unknown 12 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 24. 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 07 January 2015.
All research outputs
#1,597,216
of 25,374,917 outputs
Outputs from PLoS Computational Biology
#1,366
of 8,960 outputs
Outputs of similar age
#14,466
of 292,509 outputs
Outputs of similar age from PLoS Computational Biology
#15
of 127 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd 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 84% 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 292,509 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 95% of its contemporaries.
We're also able to compare this research output to 127 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.