Molecular Mechanism and Kinetics of Amyloid‑β42 Aggregate Formation: A Simulation Study
journal contributionposted on 08.11.2019, 21:44 by Viet Hoang Man, Xibing He, Beihong Ji, Shuhan Liu, Xiang-Qun Xie, Junmei Wang
As an important neuropathological hallmark of Alzheimer’s disease (AD), the oligomerization of amyloid-β (Aβ) peptides has been intensively investigated in both theoretical and experimental studies. However, the oligomerization space in terms of the kinetics, molecular mechanism, and oligomer structures remains mysterious to us. An equation that can quantitatively describe the time it takes for Aβ oligomers to appear in the human brain at a given Aβ monomer concentration is extremely vital for us to understand the development and disease progression of AD. In this study, we utilized molecular dynamics (MD) simulations to investigate the oligomerization of Aβ42 peptides at five different monomer concentrations. We have elucidated the formation pathways of Aβ tetramers, characterized the oligomer structures, estimated the oligomerization time for Aβ dimers, trimers, and tetramers, and for the first-time derived equations that could quantitatively describe the relationship between the oligomerization time and the monomer concentration. Applying these equations, our prediction of oligomerization time agrees well with the experimental and clinical findings, in spite of the limitations of our oligomerization simulations. We have found that the Aβ oligomerization time depends on the monomer concentration by a power of −2.4. The newly established equations will enable us to quantitatively estimate the risk score of AD, which is a function of age. Moreover, we have identified the most dominant pathway of forming Aβ tetramers, probably the most important and toxic Aβ oligomer. Our results have shown that the structures of Aβ42 dimer, trimer, and tetramer, which are distinguishable from each other, depend on the monomer concentration at which the oligomers form. Representative oligomer structures, which can serve as potential drug targets, have been identified by clustering analysis. The MD sampling adequacy has been validated by the excellent agreement between the calculated and measured collisional cross section (CCS) parameters (the prediction errors are within 2%). In a conclusion, this study provides the kinetics and structure basis for developing inhibitors to decelerate the Aβ oligomerization process.