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Collective Dynamics Underlying Allosteric Transitions in Hemoglobin

Overview of attention for article published in PLoS Computational Biology, September 2013
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  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Average Attention Score compared to outputs of the same age and source

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1 X user
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1 Wikipedia page

Citations

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30 Dimensions

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39 Mendeley
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2 CiteULike
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Title
Collective Dynamics Underlying Allosteric Transitions in Hemoglobin
Published in
PLoS Computational Biology, September 2013
DOI 10.1371/journal.pcbi.1003232
Pubmed ID
Authors

Martin D. Vesper, Bert L. de Groot

Abstract

Hemoglobin is the prototypic allosteric protein. Still, its molecular allosteric mechanism is not fully understood. To elucidate the mechanism of cooperativity on an atomistic level, we developed a novel computational technique to analyse the coupling of tertiary and quaternary motions. From Molecular Dynamics simulations showing spontaneous quaternary transitions, we separated the transition trajectories into two orthogonal sets of motions: one consisting of intra-chain motions only (referred to as tertiary-only) and one consisting of global inter-chain motions only (referred to as quaternary-only). The two underlying subspaces are orthogonal by construction and their direct sum is the space of full motions. Using Functional Mode Analysis, we were able to identify a collective coordinate within the tertiary-only subspace that is correlated to the most dominant motion within the quaternary-only motions, hence providing direct insight into the allosteric coupling mechanism between tertiary and quaternary conformation changes. This coupling-motion is substantially different from tertiary structure changes between the crystallographic structures of the T- and R-state. We found that hemoglobin's allosteric mechanism of communication between subunits is equally based on hydrogen bonds and steric interactions. In addition, we were able to affect the T-to-R transition rates by choosing different histidine protonation states, thereby providing a possible atomistic explanation for the Bohr effect.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Czechia 1 3%
Germany 1 3%
Italy 1 3%
Unknown 36 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 26%
Researcher 10 26%
Student > Doctoral Student 3 8%
Student > Postgraduate 3 8%
Student > Master 3 8%
Other 6 15%
Unknown 4 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 36%
Chemistry 9 23%
Biochemistry, Genetics and Molecular Biology 5 13%
Physics and Astronomy 2 5%
Computer Science 1 3%
Other 2 5%
Unknown 6 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 26 September 2013.
All research outputs
#8,262,107
of 25,374,647 outputs
Outputs from PLoS Computational Biology
#5,490
of 8,960 outputs
Outputs of similar age
#69,783
of 213,336 outputs
Outputs of similar age from PLoS Computational Biology
#58
of 119 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 8,960 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 37th percentile – i.e., 37% 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 213,336 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 119 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.