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Sequence entropy of folding and the absolute rate of amino acid substitutions

Overview of attention for article published in Nature Ecology & Evolution, October 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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4 news outlets
blogs
1 blog
twitter
66 X users
facebook
2 Facebook pages

Citations

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51 Dimensions

Readers on

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100 Mendeley
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Title
Sequence entropy of folding and the absolute rate of amino acid substitutions
Published in
Nature Ecology & Evolution, October 2017
DOI 10.1038/s41559-017-0338-9
Pubmed ID
Authors

Richard A. Goldstein, David D. Pollock

Abstract

Adequate representations of protein evolution should consider how the acceptance of mutations depends on the sequence context in which they arise. However, epistatic interactions among sites in a protein result in hererogeneities in the substitution rate, both temporal and spatial, that are beyond the capabilities of current models. Here we use parallels between amino acid substitutions and chemical reaction kinetics to develop an improved theory of protein evolution. We constructed a mechanistic framework for modelling amino acid substitution rates that uses the formalisms of statistical mechanics, with principles of population genetics underlying the analysis. Theoretical analyses and computer simulations of proteins under purifying selection for thermodynamic stability show that substitution rates and the stabilization of resident amino acids (the 'evolutionary Stokes shift') can be predicted from biophysics and the effect of sequence entropy alone. Furthermore, we demonstrate that substitutions predominantly occur when epistatic interactions result in near neutrality; substitution rates are determined by how often epistasis results in such nearly neutral conditions. This theory provides a general framework for modelling protein sequence change under purifying selection, potentially explains patterns of convergence and mutation rates in real proteins that are incompatible with previous models, and provides a better null model for the detection of adaptive changes.

X Demographics

X Demographics

The data shown below were collected from the profiles of 66 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 100 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 100 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 23 23%
Student > Ph. D. Student 22 22%
Student > Master 13 13%
Student > Bachelor 12 12%
Professor > Associate Professor 5 5%
Other 14 14%
Unknown 11 11%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 36 36%
Agricultural and Biological Sciences 33 33%
Chemistry 4 4%
Immunology and Microbiology 3 3%
Engineering 3 3%
Other 6 6%
Unknown 15 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 68. 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 29 May 2020.
All research outputs
#635,054
of 25,658,139 outputs
Outputs from Nature Ecology & Evolution
#1,013
of 2,176 outputs
Outputs of similar age
#13,359
of 339,200 outputs
Outputs of similar age from Nature Ecology & Evolution
#51
of 102 outputs
Altmetric has tracked 25,658,139 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,176 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 149.4. This one has gotten more attention than average, scoring higher than 53% 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 339,200 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 96% of its contemporaries.
We're also able to compare this research output to 102 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 50% of its contemporaries.