Literature DB >> 35258946

Mechanistic Kinetic Model Reveals How Amyloidogenic Hydrophobic Patches Facilitate the Amyloid-β Fibril Elongation.

Hengyi Xie1, Ana Rojas2, Gia G Maisuradze3, George Khelashvili1.   

Abstract

Abnormal aggregation of amyloid β (Aβ) peptides into fibrils plays a critical role in the development of Alzheimer's disease. A two-stage "dock-lock" model has been proposed for the Aβ fibril elongation process. However, the mechanisms of the Aβ monomer-fibril binding process have not been elucidated with the necessary molecular-level precision, so it remains unclear how the lock phase dynamics leads to the overall in-register binding of the Aβ monomer onto the fibril. To gain mechanistic insights into this critical step during the fibril elongation process, we used molecular dynamics (MD) simulations with a physics-based coarse-grained UNited-RESidue (UNRES) force field and sampled extensively the dynamics of the lock phase process, in which a fibril-bound Aβ(9-40) peptide rearranged to establish the native docking conformation. Analysis of the MD trajectories with Markov state models was used to quantify the kinetics of the rearrangement process and the most probable pathways leading to the overall native docking conformation of the incoming peptide. These revealed a key intermediate state in which an intra-monomer hairpin is formed between the central core amyloidogenic patch 18VFFA21 and the C-terminal hydrophobic patch 34LMVG37. This hairpin structure is highly favored as a transition state during the lock phase of the fibril elongation. We propose a molecular mechanism for facilitation of the Aβ fibril elongation by amyloidogenic hydrophobic patches.

Entities:  

Keywords:  Aβ peptide; Markov state model; UNRES force field; amyloids; replica-exchange molecular dynamics; transition path theory

Mesh:

Substances:

Year:  2022        PMID: 35258946      PMCID: PMC8986627          DOI: 10.1021/acschemneuro.1c00801

Source DB:  PubMed          Journal:  ACS Chem Neurosci        ISSN: 1948-7193            Impact factor:   4.418


  78 in total

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