Back

Non-micelle-like Amyloid Aggregate Stabilizes Amyloid β (1-42) Growth Nuclei Formation

Kurisaki, I.; Tanaka, S.

2022-12-10 biophysics
10.1101/2022.12.09.519846 bioRxiv
Show abstract

Protein aggregate formations are essential processes to regulate biochemical networks in the cell, while anomalously formed aggregates such as amyloid fibrils cause serious neuronal diseases. It has been discussed for a quarter century that protein crowding milieus, such as micelle-like aggregates, promote the formation of growth nuclei, fibril-growth competent aggregates which trigger rapid growth of pathogenic amyloid fibrils, but the mechanisms are still elusive, in particular at microscopic level. In this study, we examined the long-standing problem by employing atomistic molecular dynamics simulations for amyloid {beta}(1-42) (A{beta}42), the paradigmatic amyloid-forming peptide. First, we constructed an atomistic model of A{beta}42 growth nuclei in A{beta}42 aggregate milieu, the pentameric A{beta}42 protomer dimer surrounded by 40 A{beta}42 monomers. Next, we simulated A{beta}42 monomer dissociation from the A{beta}42 growth nuclei and examined the effect of A{beta}42 aggregate milieu on the process. A{beta}42 aggregates spatially restrict A{beta}42 monomer dissociation pathways, while such spatial restriction itself does not significantly suppress A{beta}42 monomer dissociation from the growth nuclei. Rather, A{beta}42 aggregate milieus thermodynamically stabilize an A{beta}42 monomer binding to the growth edge by making atomic contacts with the monomer and contributes to stable formation of growth nuclei. A part of the aggregate milieu anchors dissociating monomer to the remaining part of growth nuclei, suggesting cooperative suppression of A{beta}42 monomer dissociation from A{beta}42 growth nuclei. Since the A{beta}42 aggregate milieu does not take a micelle-like configuration, we here discuss a new mechanism for stable formation of A{beta}42 growth nuclei in the presence of aggregate milieu.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Physical Chemistry Chemical Physics
36 papers in training set
Top 0.1%
18.1%
2
The Journal of Physical Chemistry B
167 papers in training set
Top 0.1%
18.1%
3
The Journal of Physical Chemistry Letters
63 papers in training set
Top 0.1%
7.1%
4
Journal of Chemical Theory and Computation
140 papers in training set
Top 0.3%
6.1%
5
Journal of Chemical Information and Modeling
238 papers in training set
Top 1.0%
5.1%
50% of probability mass above
6
The Journal of Chemical Physics
56 papers in training set
Top 0.1%
4.2%
7
ACS Chemical Neuroscience
67 papers in training set
Top 0.3%
3.2%
8
Scientific Reports
3612 papers in training set
Top 44%
2.4%
9
Biophysical Journal
631 papers in training set
Top 3%
2.1%
10
Proteins: Structure, Function, and Bioinformatics
88 papers in training set
Top 0.6%
2.1%
11
PLOS Computational Biology
1863 papers in training set
Top 13%
1.9%
12
Computational and Structural Biotechnology Journal
242 papers in training set
Top 3%
1.9%
13
eLife
5828 papers in training set
Top 50%
1.7%
14
Frontiers in Molecular Biosciences
102 papers in training set
Top 0.9%
1.5%
15
International Journal of Molecular Sciences
494 papers in training set
Top 10%
1.3%
16
ACS Omega
105 papers in training set
Top 3%
1.1%
17
RSC Advances
22 papers in training set
Top 0.7%
1.0%
18
Biochemistry
148 papers in training set
Top 2%
1.0%
19
Communications Biology
993 papers in training set
Top 26%
1.0%
20
Chemical Science
73 papers in training set
Top 1%
1.0%
21
Biophysics and Physicobiology
11 papers in training set
Top 0.1%
0.8%
22
Nature Communications
5641 papers in training set
Top 58%
0.8%
23
Proceedings of the National Academy of Sciences
2444 papers in training set
Top 42%
0.8%
24
Biomolecules
100 papers in training set
Top 4%
0.6%
25
Cell Reports Physical Science
19 papers in training set
Top 0.3%
0.6%