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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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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.

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Mendeley readers

The data shown below were compiled from readership statistics for 446 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 427 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 114 26%
Researcher 87 20%
Professor 36 8%
Student > Master 35 8%
Student > Bachelor 27 6%
Other 79 18%
Unknown 68 15%
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 81 18%