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Can local heating and molecular crowders disintegrate amyloid aggregates?
Naresh Kumar1, Prabir Khatua2, Sudipta Kumar Sinha1
1Department of Chemistry, Theoretical and Computational Biophysical Chemistry Group, Indian Institute of Technology Ropar Rupnagar Punjab 140001 India sudipta@iitrpr.ac.in +91-01881-232066.
Chemical Science
|April 26, 2024
Summary
This study explores Alzheimer's disease by simulating amyloid-beta (Aβ) octamer disintegration. Local heating and SDS failed to fully break down Aβ, revealing a multi-step breakdown mechanism.
Area of Science:
- Biophysics
- Computational Chemistry
- Neuroscience
Background:
- Alzheimer's disease is linked to amyloid-beta (Aβ) aggregate formation.
- Understanding Aβ aggregate disintegration is crucial for developing therapeutic strategies.
Purpose of the Study:
- To investigate the disintegration mechanism of a mature Aβ octamer.
- To explore the effects of local heating and crowding agents on Aβ disintegration.
- To propose a theoretical model for Aβ aggregation and disintegration kinetics.
Main Methods:
- Molecular dynamics simulations, including well-tempered metadynamics.
- Investigating local heating effects on Aβ segments.
- Varying sodium dodecyl sulphate (SDS) concentration to simulate crowding effects.
- Developing a novel two-state mean-field model.
Main Results:
- Aβ aggregates resist complete disintegration under local heating due to rapid thermal dissipation.
- High SDS concentrations inhibit aggregation but do not fully disintegrate existing aggregates.
- A multi-step Aβ octamer disintegration mechanism was revealed: octamer → pentamer/hexamer ⇌ tetramer → monomer.
- A rate-determining barrier of 45 kJ mol-1 was identified for the octamer to pentamer/hexamer transition.
- The mean-field model provides insights into Aβ growth and disintegration kinetics.
Conclusions:
- Complete disintegration of Aβ aggregates is challenging due to high energy barriers.
- The study elucidates a detailed Aβ octamer disintegration pathway.
- The developed mean-field model offers a theoretical framework for understanding Aβ aggregation dynamics.
- Findings guide the development of novel strategies to combat Alzheimer's disease by targeting Aβ aggregates.

