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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 (90th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

patent
9 patents

Readers on

mendeley
28 Mendeley
citeulike
1 CiteULike
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Article details
Title
Realistic modeling of the denatured states of proteins allows accurate calculations of the ph dependence of protein stability11Edited by B. Honig
Published in
Journal of Molecular Biology, December 1999
DOI 10.1006/jmbi.1999.3305
Pubmed ID
Authors
Abstract

Computational techniques based on continuum electrostatics treatments have been successful in predicting and interpreting the pKa values of ionizable amino acids in folded proteins. Despite this progress, efforts to reproduce the pH-dependence of protein stability have met with only limited success: agreement with experimental results has been only qualitative. It has been argued previously that the most likely reason for discrepancies is the presence of residual electrostatic interactions in the unfolded state, which cause pKa values to be shifted from their model compound values. Here we show that by constructing atomistic models of the unfolded state with a simple molecular mechanics protocol that uses the native state as a starting point, much improved reproduction of pH effects on protein stability can be obtained. In contrast, when a fully extended model of the unfolded state is used, no such improvement is obtained, a result that suggests that local interactions with residues nearby in the sequence are not sufficient to properly account for the pKa shifts in the unfolded state. In comparison to model compound values, the pKa values of acidic residues in "native-like" unfolded states are typically found to be shifted downwards by approximately 0.3 pH unit, in good agreement with the average downward shift deduced from experimental measurements. Given its success in the present situation, the protocol employed here for developing simple models of the unfolded state may prove useful in other computer simulation applications.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 1 4%
Italy 1 4%
Ireland 1 4%
Brazil 1 4%
Unknown 24 86%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 6 21%
Researcher 5 18%
Student > Ph. D. Student 4 14%
Professor > Associate Professor 3 11%
Other 2 7%
Other 6 21%
Unknown 2 7%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 12 43%
Chemistry 6 21%
Biochemistry, Genetics and Molecular Biology 4 14%
Pharmacology, Toxicology and Pharmaceutical Science 1 4%
Physics and Astronomy 1 4%
Other 0 0%
Unknown 4 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 14 April 2015.
All research outputs
#4,585,058
of 30,598,342 outputs
Outputs from Journal of Molecular Biology
#1,339
of 12,606 outputs
Outputs of similar age
#8,297
of 129,281 outputs
Outputs of similar age from Journal of Molecular Biology
#10
of 103 outputs
Altmetric has tracked 30,598,342 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,606 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.8. This one has done well, scoring higher than 83% 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 129,281 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 90% of its contemporaries.
We're also able to compare this research output to 103 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.