Title |
Systematic In Vivo Analysis of the Intrinsic Determinants of Amyloid β Pathogenicity
|
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Published in |
PLoS Biology, October 2007
|
DOI | 10.1371/journal.pbio.0050290 |
Pubmed ID | |
Authors |
Leila M Luheshi, Gian Gaetano Tartaglia, Ann-Christin Brorsson, Amol P Pawar, Ian E Watson, Fabrizio Chiti, Michele Vendruscolo, David A Lomas, Christopher M Dobson, Damian C Crowther |
Abstract |
Protein aggregation into amyloid fibrils and protofibrillar aggregates is associated with a number of the most common neurodegenerative diseases. We have established, using a computational approach, that knowledge of the primary sequences of proteins is sufficient to predict their in vitro aggregation propensities. Here we demonstrate, using rational mutagenesis of the Abeta42 peptide based on such computational predictions of aggregation propensity, the existence of a strong correlation between the propensity of Abeta42 to form protofibrils and its effect on neuronal dysfunction and degeneration in a Drosophila model of Alzheimer disease. Our findings provide a quantitative description of the molecular basis for the pathogenicity of Abeta and link directly and systematically the intrinsic properties of biomolecules, predicted in silico and confirmed in vitro, to pathogenic events taking place in a living organism. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 50% |
Ireland | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 50% |
Members of the public | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 7 | 4% |
United States | 4 | 2% |
Germany | 2 | 1% |
Spain | 2 | 1% |
Brazil | 1 | <1% |
Iran, Islamic Republic of | 1 | <1% |
Israel | 1 | <1% |
Chile | 1 | <1% |
Slovenia | 1 | <1% |
Other | 0 | 0% |
Unknown | 165 | 89% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 57 | 31% |
Student > Ph. D. Student | 42 | 23% |
Professor | 14 | 8% |
Professor > Associate Professor | 13 | 7% |
Student > Master | 13 | 7% |
Other | 31 | 17% |
Unknown | 15 | 8% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 80 | 43% |
Chemistry | 28 | 15% |
Biochemistry, Genetics and Molecular Biology | 25 | 14% |
Neuroscience | 16 | 9% |
Medicine and Dentistry | 5 | 3% |
Other | 14 | 8% |
Unknown | 17 | 9% |