The misfolding and pathological aggregation of α-synuclein forming insoluble amyloid deposits is associated with Parkinson's disease, the second most common neurodegenerative disease in the world population. Characterizing the self-assembly mechanism of α-synuclein is critical for discovering treatments against synucleinopathies. The intrinsically disordered property, high degrees of freedom, and macroscopic timescales of conformational conversion make its characterization extremely challenging in vitro and in silico. Here, we systematically investigated the dynamics of monomer misfolding and dimerization of the full-length α-synuclein using atomistic discrete molecular dynamics simulations. Our results suggested that both α-synuclein monomers and dimers mainly adopted unstructured formations with partial helices around the N-terminus (residues 8-32) and various β-sheets spanning the residues 35-56 (N-terminal tail) and residues 61-95 (NAC region). The C-terminus mostly assumed an unstructured formation wrapping around the lateral surface and the elongation edge of the β-sheet core formed by an N-terminal tail and NAC regions. Dimerization enhanced the β-sheet formation along with a decrease in the unstructured content. The inter-peptide β-sheets were mainly formed by the N-terminal tail and NACore (residues 68-78) regions, suggesting that these two regions played critical roles in the amyloid aggregation of α-synuclein. Interactions of the C-terminus with the N-terminal tail and the NAC region were significantly suppressed in the α-synuclein dimer, indicating that the interaction of the C-terminus with the N-terminal tail and NAC regions could prevent α-synuclein aggregation. These results on the structural ensembles and early aggregation dynamics of α-synuclein will help understand the nucleation and fibrillization of α-synuclein.
Molecular Insights into the Misfolding and Dimerization Dynamics of the Full-Length α-Synuclein from Atomistic Discrete Molecular Dynamics Simulations.
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作者:Zhang Yu, Wang Ying, Liu Yuying, Wei Guanghong, Ding Feng, Sun Yunxiang
| 期刊: | ACS Chemical Neuroscience | 影响因子: | 3.900 |
| 时间: | 2022 | 起止号: | 2022 Nov 2; 13(21):3126-3137 |
| doi: | 10.1021/acschemneuro.2c00531 | ||
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