Early-Stage Oligomerization of Prion-like Polypeptides Reveals the Molecular Mechanism of Amyloid-Disrupting Capacity by Proline Residues

Exploring Abeta42 monomer diffusion dynamics on fibril surfaces through molecular simulations

This study provides critical insights into the role of surface-mediated processes in Alzheimer's disease, with implications for the aggregation of Abeta42 peptides. Employing coarse-grained molecular dynamics simulations, we focus on elucidating the molecular intricacies of these processes beyond primary nucleation. Central to our investigation is the analysis of a freely diffusing Abeta42 monomer on preformed fibril structures. We conduct detailed calculations of the monomer's diffusion coefficient on fibril surfaces (as a one-dimensional case), along with various monomer orientations. Our findings reveal a strong and consistent correlation between the monomer's diffusion coefficient and its orientation on the surface. Further analysis differentiates the effects of parallel and perpendicular alignments with respect to the fibril axis. Additionally, we explore how different fibril surfaces influence monomer dynamics by comparing the C-terminal and N-terminal surfaces. We find that the monomer exhibits faster diffusion coefficients on the C-terminal surface. Differences in surface roughness (SR), quantified using root-mean-square distances, significantly affect monomer dynamics, thereby influencing its diffusion on the surface. Importantly, this study underscores that fibril twisting acts as a regulatory niche, selectively influencing these orientations and their diffusion properties necessary for facilitating fibril growth within biologically relevant time scales. This discovery opens new avenues for targeted therapeutic strategies aimed at manipulating fibril dynamics to mitigate the progression of Alzheimer's disease.

From Monomers to Hexamers: A Theoretical Probability of the Neighbor Density Approach to Dissect Protein Oligomerization in Cells

Deciphering the oligomeric state of proteins within cells is pivotal to understanding their role in intricate cellular processes. With the recent advances in single-molecule localization microscopy, previous efforts have harnessed protein location density approaches, coupled with simulations, to extract membrane protein oligomeric states in cells, highlighting the value of such techniques. However, a comprehensive theoretical approach that can be universally applied across different proteins (e.g., membrane and cytosolic proteins) remains elusive. Here, we introduce the theoretical probability of neighbor density (PND) as a robust tool to discern protein oligomeric states in cellular environments. Utilizing our approach, the theoretical PND was validated against simulated data for both membrane and cytosolic proteins, consistently aligning with experimental baselines for membrane proteins. This congruence was maintained even when adjusting for protein concentrations or exploring proteins of various oligomeric states. The strength of our method lies not only in its precision but also in its adaptability, accommodating diverse cellular protein scenarios without compromising the accuracy. The development and validation of the theoretical PND facilitate accurate protein oligomeric state determination and bolster our understanding of protein-mediated cellular functions.