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Structural Disorder in Eukaryotes

Overview of attention for article published in PLOS ONE, April 2012
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Title
Structural Disorder in Eukaryotes
Published in
PLOS ONE, April 2012
DOI 10.1371/journal.pone.0034687
Pubmed ID
Authors

Rita Pancsa, Peter Tompa

Abstract

Based on early bioinformatic studies on a handful of species, the frequency of structural disorder of proteins is generally thought to be much higher in eukaryotes than in prokaryotes. To refine this view, we present here a comparative prediction study and analysis of 194 fully described eukaryotic proteomes and 87 reference prokaryotes for structural disorder. We found that structural disorder does distinguish eukaryotes from prokaryotes, but its frequency spans a very wide range in the two superkingdoms that largely overlap. The number of disordered binding regions and different Pfam domain types also contribute to distinguish eukaryotes from prokaryotes. Unexpectedly, the highest levels--and highest variability--of predicted disorder is found in protists, i.e. single-celled eukaryotes, often surpassing more complex eukaryote organisms, plants and animals. This trend contrasts with that of the number of domain types, which increases rather monotonously toward more complex organisms. The level of structural disorder appears to be strongly correlated with lifestyle, because some obligate intracellular parasites and endosymbionts have the lowest levels, whereas host-changing parasites have the highest level of predicted disorder. We conclude that protists have been the evolutionary hot-bed of experimentation with structural disorder, in a period when structural disorder was actively invented and the major functional classes of disordered proteins established.

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Mendeley readers

The data shown below were compiled from readership statistics for 178 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 2 1%
United States 2 1%
Canada 2 1%
Hungary 1 <1%
United Kingdom 1 <1%
Peru 1 <1%
Poland 1 <1%
Unknown 168 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 50 28%
Researcher 29 16%
Student > Master 27 15%
Student > Bachelor 13 7%
Professor 8 4%
Other 31 17%
Unknown 20 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 71 40%
Biochemistry, Genetics and Molecular Biology 50 28%
Chemistry 11 6%
Computer Science 5 3%
Physics and Astronomy 5 3%
Other 11 6%
Unknown 25 14%