Back

A Coarse-Grained Molecular Dynamics Investigation on Spontaneous Binding of Aβ9-40 Fibril with Cholesterol-mixed DPPC Bilayer

Agrawal, N.; Skelton, A. A.; Parisini, E.

2022-09-16 biochemistry
10.1101/2022.09.16.508209 bioRxiv
Show abstract

Alzheimers disease is the most common form of dementia. Its aetiology is characterized by the misfolding and aggregation of amyloid-{beta} (A{beta}) peptides into {beta}-sheet-rich A{beta} oligomers/fibrils. Whereas experimental studies have suggested that A{beta} oligomers/fibrils interact with the cell membranes and perturb their structures and dynamics, the molecular mechanism of this interaction is still not fully understood. In the present work, we have performed a total of 120 s-long simulations to investigate the interaction between trimeric or hexameric A{beta}1-40 fibrils with either a 100% DPPC bilayer, a 70% DPPC-30% cholesterol bilayer or a 50% DPPC-50 % cholesterol bilayer. Our simulation data capture the spontaneous binding of the aqueous A{beta}1-40 fibrils with the membranes and show that the central hydrophobic amino acid cluster, the lysine residue adjacent to it and the C-terminal hydrophobic residues are all involved in the process. Moreover, our data show that while the A{beta}1-40 fibril does not bind to the 100% DPPC bilayer, its binding affinity for the membrane increases with the amount of cholesterol. Overall, our data suggest that two clusters of hydrophobic residues and one lysine help A{beta}1-40 fibrils establish stable interactions with a cholesterol-rich DPPC bilayer. These residues are likely to represent potential target regions for the design of inhibitors, thus opening new avenues in structure-based drug design against A{beta} oligomer/fibril-membrane interaction.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.