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A Unified View of “How Allostery Works”

Overview of attention for article published in PLoS Computational Biology, February 2014
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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)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

blogs
1 blog
twitter
14 X users
facebook
1 Facebook page
googleplus
1 Google+ user

Citations

dimensions_citation
337 Dimensions

Readers on

mendeley
448 Mendeley
citeulike
8 CiteULike
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Title
A Unified View of “How Allostery Works”
Published in
PLoS Computational Biology, February 2014
DOI 10.1371/journal.pcbi.1003394
Pubmed ID
Authors

Chung-Jung Tsai, Ruth Nussinov

Abstract

The question of how allostery works was posed almost 50 years ago. Since then it has been the focus of much effort. This is for two reasons: first, the intellectual curiosity of basic science and the desire to understand fundamental phenomena, and second, its vast practical importance. Allostery is at play in all processes in the living cell, and increasingly in drug discovery. Many models have been successfully formulated, and are able to describe allostery even in the absence of a detailed structural mechanism. However, conceptual schemes designed to qualitatively explain allosteric mechanisms usually lack a quantitative mathematical model, and are unable to link its thermodynamic and structural foundations. This hampers insight into oncogenic mutations in cancer progression and biased agonists' actions. Here, we describe how allostery works from three different standpoints: thermodynamics, free energy landscape of population shift, and structure; all with exactly the same allosteric descriptors. This results in a unified view which not only clarifies the elusive allosteric mechanism but also provides structural grasp of agonist-mediated signaling pathways, and guides allosteric drug discovery. Of note, the unified view reasons that allosteric coupling (or communication) does not determine the allosteric efficacy; however, a communication channel is what makes potential binding sites allosteric.

X Demographics

X Demographics

The data shown below were collected from the profiles of 14 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 448 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 2%
Czechia 2 <1%
United Kingdom 2 <1%
Brazil 1 <1%
India 1 <1%
Chile 1 <1%
Netherlands 1 <1%
Japan 1 <1%
Canada 1 <1%
Other 0 0%
Unknown 429 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 115 26%
Researcher 87 19%
Professor 36 8%
Student > Master 35 8%
Student > Bachelor 27 6%
Other 78 17%
Unknown 70 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 112 25%
Agricultural and Biological Sciences 107 24%
Chemistry 75 17%
Physics and Astronomy 21 5%
Engineering 10 2%
Other 40 9%
Unknown 83 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 05 April 2014.
All research outputs
#2,215,544
of 25,813,008 outputs
Outputs from PLoS Computational Biology
#1,942
of 9,044 outputs
Outputs of similar age
#24,814
of 324,696 outputs
Outputs of similar age from PLoS Computational Biology
#20
of 115 outputs
Altmetric has tracked 25,813,008 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,044 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.3. This one has done well, scoring higher than 78% 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 324,696 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 115 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.