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A Generic Mechanism of Emergence of Amyloid Protofilaments from Disordered Oligomeric Aggregates

Overview of attention for article published in PLoS Computational Biology, November 2008
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Title
A Generic Mechanism of Emergence of Amyloid Protofilaments from Disordered Oligomeric Aggregates
Published in
PLoS Computational Biology, November 2008
DOI 10.1371/journal.pcbi.1000222
Pubmed ID
Authors

Stefan Auer, Filip Meersman, Christopher M. Dobson, Michele Vendruscolo

Abstract

The presence of oligomeric aggregates, which is often observed during the process of amyloid formation, has recently attracted much attention because it has been associated with a range of neurodegenerative conditions including Alzheimer's and Parkinson's diseases. We provide a description of a sequence-indepedent mechanism by which polypeptide chains aggregate by forming metastable oligomeric intermediate states prior to converting into fibrillar structures. Our results illustrate that the formation of ordered arrays of hydrogen bonds drives the formation of beta-sheets within the disordered oligomeric aggregates that form early under the effect of hydrophobic forces. Individual beta-sheets initially form with random orientations and subsequently tend to align into protofilaments as their lengths increase. Our results suggest that amyloid aggregation represents an example of the Ostwald step rule of first-order phase transitions by showing that ordered cross-beta structures emerge preferentially from disordered compact dynamical intermediate assemblies.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 107 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 5%
Portugal 2 2%
Chile 1 <1%
France 1 <1%
Netherlands 1 <1%
United Kingdom 1 <1%
Brazil 1 <1%
Spain 1 <1%
China 1 <1%
Other 0 0%
Unknown 93 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 33 31%
Researcher 26 24%
Professor > Associate Professor 10 9%
Student > Master 8 7%
Professor 6 6%
Other 11 10%
Unknown 13 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 28 26%
Chemistry 22 21%
Physics and Astronomy 14 13%
Biochemistry, Genetics and Molecular Biology 11 10%
Engineering 4 4%
Other 10 9%
Unknown 18 17%