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Protein flexibility in the light of structural alphabets

Overview of attention for article published in Frontiers in Molecular Biosciences, May 2015
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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 (91st percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

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1 news outlet
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1 blog
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6 X users

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168 Mendeley
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Title
Protein flexibility in the light of structural alphabets
Published in
Frontiers in Molecular Biosciences, May 2015
DOI 10.3389/fmolb.2015.00020
Pubmed ID
Authors

Pierrick Craveur, Agnel P. Joseph, Jeremy Esque, Tarun J. Narwani, Floriane Noël, Nicolas Shinada, Matthieu Goguet, Sylvain Leonard, Pierre Poulain, Olivier Bertrand, Guilhem Faure, Joseph Rebehmed, Amine Ghozlane, Lakshmipuram S. Swapna, Ramachandra M. Bhaskara, Jonathan Barnoud, Stéphane Téletchéa, Vincent Jallu, Jiri Cerny, Bohdan Schneider, Catherine Etchebest, Narayanaswamy Srinivasan, Jean-Christophe Gelly, Alexandre G. de Brevern

Abstract

Protein structures are valuable tools to understand protein function. Nonetheless, proteins are often considered as rigid macromolecules while their structures exhibit specific flexibility, which is essential to complete their functions. Analyses of protein structures and dynamics are often performed with a simplified three-state description, i.e., the classical secondary structures. More precise and complete description of protein backbone conformation can be obtained using libraries of small protein fragments that are able to approximate every part of protein structures. These libraries, called structural alphabets (SAs), have been widely used in structure analysis field, from definition of ligand binding sites to superimposition of protein structures. SAs are also well suited to analyze the dynamics of protein structures. Here, we review innovative approaches that investigate protein flexibility based on SAs description. Coupled to various sources of experimental data (e.g., B-factor) and computational methodology (e.g., Molecular Dynamic simulation), SAs turn out to be powerful tools to analyze protein dynamics, e.g., to examine allosteric mechanisms in large set of structures in complexes, to identify order/disorder transition. SAs were also shown to be quite efficient to predict protein flexibility from amino-acid sequence. Finally, in this review, we exemplify the interest of SAs for studying flexibility with different cases of proteins implicated in pathologies and diseases.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 168 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Czechia 1 <1%
Belgium 1 <1%
Canada 1 <1%
Unknown 165 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 37 22%
Researcher 22 13%
Student > Master 19 11%
Student > Bachelor 16 10%
Professor 8 5%
Other 29 17%
Unknown 37 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 53 32%
Agricultural and Biological Sciences 34 20%
Computer Science 9 5%
Chemistry 9 5%
Pharmacology, Toxicology and Pharmaceutical Science 5 3%
Other 16 10%
Unknown 42 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 28 July 2022.
All research outputs
#1,702,084
of 22,979,862 outputs
Outputs from Frontiers in Molecular Biosciences
#77
of 3,846 outputs
Outputs of similar age
#23,187
of 267,177 outputs
Outputs of similar age from Frontiers in Molecular Biosciences
#2
of 29 outputs
Altmetric has tracked 22,979,862 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,846 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done particularly well, scoring higher than 97% 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 267,177 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 91% of its contemporaries.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.