Influence of pH and sequence in peptide aggregation via molecular simulation

TL;DR

This study uses a coarse-grained simulation model to investigate how pH and peptide sequence influence aggregation behavior of amyloidogenic peptides, providing insights into thermodynamics and kinetics.

Contribution

It introduces a coarse-grained model that automatically incorporates pH effects to study peptide aggregation, highlighting the impact of sequence and pH on aggregation processes.

Findings

pH significantly affects peptide aggregation pathways

Sequence variations alter aggregation thermodynamics

Large-scale simulations capture realistic peptide aggregates

Abstract

We employ a recently developed coarse-grained model for peptides and proteins where the effect of pH is automatically included. We explore the effect of pH in the aggregation process of the amyloidogenic peptide KTVIIE and two related sequences, using three different pH environments. Simulations using large systems (24 peptides chains per box) allow us to correctly account for the formation of realistic peptide aggregates. We evaluate the thermodynamic and kinetic implications of changes in sequence and pH upon peptide aggregation, and we discuss how a minimalistic coarse-grained model can account for these details.