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Correlated Inter-Domain Motions in Adenylate Kinase

Overview of attention for article published in PLoS Computational Biology, July 2014
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Title
Correlated Inter-Domain Motions in Adenylate Kinase
Published in
PLoS Computational Biology, July 2014
DOI 10.1371/journal.pcbi.1003721
Pubmed ID
Authors

Santiago Esteban-Martín, Robert Bryn Fenwick, Jörgen Ådén, Benjamin Cossins, Carlos W. Bertoncini, Victor Guallar, Magnus Wolf-Watz, Xavier Salvatella

Abstract

Correlated inter-domain motions in proteins can mediate fundamental biochemical processes such as signal transduction and allostery. Here we characterize at structural level the inter-domain coupling in a multidomain enzyme, Adenylate Kinase (AK), using computational methods that exploit the shape information encoded in residual dipolar couplings (RDCs) measured under steric alignment by nuclear magnetic resonance (NMR). We find experimental evidence for a multi-state equilibrium distribution along the opening/closing pathway of Adenylate Kinase, previously proposed from computational work, in which inter-domain interactions disfavour states where only the AMP binding domain is closed. In summary, we provide a robust experimental technique for study of allosteric regulation in AK and other enzymes.

X Demographics

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

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Korea, Republic of 1 2%
United States 1 2%
Canada 1 2%
Unknown 57 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 30%
Researcher 14 23%
Student > Bachelor 6 10%
Other 4 7%
Student > Doctoral Student 3 5%
Other 10 16%
Unknown 6 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 23%
Chemistry 13 21%
Biochemistry, Genetics and Molecular Biology 12 20%
Physics and Astronomy 4 7%
Engineering 3 5%
Other 6 10%
Unknown 9 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 August 2014.
All research outputs
#15,184,741
of 25,394,764 outputs
Outputs from PLoS Computational Biology
#6,529
of 8,964 outputs
Outputs of similar age
#119,062
of 239,422 outputs
Outputs of similar age from PLoS Computational Biology
#101
of 163 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,964 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 25th percentile – i.e., 25% of its peers scored the same or lower than it.
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 239,422 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 163 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.