Direct Observation of the Interconversion of Normal and Toxic Forms of α-Synuclein
By N. Cremades, Samuel I. A. Cohen, E. Deas, A. Abramov, A. Chen, Á. Orte, Massimo Sandal, Richard W. Clarke, Paul D. Dunne, F. Aprile and 5 more. Cell, 2012
885 citations recorded by the source corpus.
Summary Here, we use single-molecule techniques to study the aggregation of α-synuclein, the protein whose misfolding and deposition is associated with Parkinson's disease. We identify a conformational change from the initially formed oligomers to stable, more compact proteinase-K-resistant oligomers as the key step that leads ultimately to fibril formation. The oligomers formed as a result of the structural conversion generate much higher levels of oxidative stress in rat primary neurons than do the oligomers formed initially, showing that they are more damaging to cells. The structural conversion is remarkably slow, indicating a high kinetic barrier for the conversion and suggesting that there is a significant period of time for the cellular protective machinery to operate and potentially for therapeutic intervention, prior to the onset of cellular damage. In the absence of added soluble protein, the assembly process is reversed and fibrils disaggregate to form stable oligomers, hence acting as a source of cytotoxic species.
Subfields: Cellular and Molecular Neuroscience, Neurology, Physiology
View Paper: https://www.semanticscholar.org/paper/f00a7f1ff062976c5c8078e0abae0beb978ae8af
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In Cellular and Molecular Neuroscience
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- Fabrizio Chiti
- Michele Vendruscolo
- S. Linse
- F. Hartl
- E. K. Kim
- E. Choi
Citations in the corpus
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- Mitochondrial dysfunction: mechanisms and advances in therapy (2024, background): “252 Though this structural turnover is remarkedly slow due to the kinetic barrier, the reaction speed would sharply increase with enhanced aggregation, formation of β sheet oligomers, and dysregulation of compensatory mechanisms.”
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- Molecular mechanisms of protein aggregation from global fitting of kinetic models (2016, background): “In the future, as kinetic data on aggregation intermediates, such as oligomers 22 , or on the size distribution of aggregates becomes more easily accessible, the models can be extended within this kinetic framework to take this additional information into account.”
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