A general reaction network unifies the aggregation behaviour of the A$\beta$42 peptide and its variants
Georg Meisl, Xiaoting Yang, Christopher M. Dobson, Sara Linse and, Tuomas P. J. Knowles

TL;DR
This study develops a unified reaction network model that explains the aggregation kinetics of Aβ42 peptides under various electrostatic conditions, linking different variants and experimental setups into a single mechanistic framework.
Contribution
The paper introduces a minimal reaction network that unifies the aggregation mechanisms of Aβ42 peptides across different electrostatic conditions and variants.
Findings
Increased ionic strength accelerates surface catalyzed nucleation.
Surface nucleation saturates at high ionic strength.
The model links different peptide variants on a continuous mechanistic landscape.
Abstract
The amyloid peptide (A42), whose aggregation is associated with Alzheimer's disease, is an amphiphatic peptide with a high propensity to self-assemble. A42 has a net negative charge at physiological pH and modulations of intermolecular electrostatic interactions can significantly alter its aggregation behaviour. Variations in sequence and solution conditions lead to varied macroscopic behaviour, often resulting in a number of different mechanistic explanations for the aggregation of these closely related systems. Here we alter the electrostatic interactions governing the fibril aggregation kinetics by varying the ionic strength over an order of magnitude, which allows us to sample the space of different reaction mechanisms, and develop a minimal reaction network that explains the experimental kinetics under all the different conditions. We find that an increase in…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
