Effect of Surface Roughness on Aggregation of Polypeptide Chains: A Monte Carlo Study

Area of Science:

• Biophysics
• Computational Biology
• Materials Science

Background:

• Amyloidogenic protein and peptide self-assembly into fibrils is linked to neurodegenerative diseases like Alzheimer's and Parkinson's.
• Protein aggregation occurs on surfaces, with topology (roughness) significantly influencing kinetics and morphology.
• Understanding surface effects is vital for developing therapies for amyloid-related diseases.

Purpose of the Study:

• To develop a simple lattice model to investigate the role of surface roughness in polypeptide chain aggregation.
• To analyze the impact of varying surface roughness on aggregation kinetics and aggregate morphology.

Main Methods:

• Development of a lattice model simulating polypeptide chain self-assembly on surfaces.
• Simulation of aggregation processes across a range of surface roughness parameters.
• Analysis of fibril formation rates and aggregate structures as a function of surface topology.

Main Results:

• Increased surface roughness was found to decelerate fibril formation, inhibiting it at high roughness levels.
• A subtle catalytic effect was predicted: slightly rough surfaces can promote polypeptide self-assembly.
• This catalytic effect is observed under moderate surface-polypeptide interactions, driven by energy-entropy competition.

Conclusions:

• Surface roughness is a critical factor modulating amyloidogenic protein aggregation kinetics and morphology.
• The findings suggest that tailored surface topographies could potentially be used to control or inhibit pathological protein aggregation.
• The study highlights the complex interplay between surface properties and self-assembly, offering insights into disease mechanisms and therapeutic strategies.