Molecular simulations of amyloid beta assemblies

Grasso, Gianvito; Danani, Andrea

doi:10.1080/23746149.2020.1770627

Cited by 28 publications

(30 citation statements)

References 220 publications

(263 reference statements)

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“…To integrate the NMR experimental data and to evaluate the stability of the Aβ(1–42) conformation solved in HFIP/water 50/50 v / v when exposed to a complete aqueous system, we performed 50 ns molecular dynamics (MD) calculation starting from the 3D coordinates obtained from NMR spectra assignment. Although aware of the limitations of the traditional computational methods we used, the results are in agreement with those obtained with REMD protocols [ 33 , 34 , 35 , 36 , 37 ].…”

Section: Resultssupporting

confidence: 80%

Exploring the Early Stages of the Amyloid Aβ(1–42) Peptide Aggregation Process: An NMR Study

et al. 2021

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Alzheimer’s disease (AD) is a neurodegenerative pathology characterized by the presence of neurofibrillary tangles and amyloid plaques, the latter mainly composed of Aβ(1–40) and Aβ(1–42) peptides. The control of the Aβ aggregation process as a therapeutic strategy for AD has prompted the interest to investigate the conformation of the Aβ peptides, taking advantage of computational and experimental techniques. Mixtures composed of systematically different proportions of HFIP and water have been used to monitor, by NMR, the conformational transition of the Aβ(1–42) from soluble α-helical structure to β-sheet aggregates. In the previous studies, 50/50 HFIP/water proportion emerged as the solution condition where the first evident Aβ(1–42) conformational changes occur. In the hypothesis that this solvent reproduces the best condition to catch transitional helical-β-sheet Aβ(1–42) conformations, in this study, we report an extensive NMR conformational analysis of Aβ(1–42) in 50/50 HFIP/water v/v. Aβ(1–42) structure was solved by us, giving evidence that the evolution of Aβ(1–42) peptide from helical to the β-sheet may follow unexpected routes. Molecular dynamics simulations confirm that the structural model we calculated represents a starting condition for amyloid fibrils formation.

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Section: Resultssupporting

confidence: 80%

Exploring the Early Stages of the Amyloid Aβ(1–42) Peptide Aggregation Process: An NMR Study

et al. 2021

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“…Computational biology approaches have proven to be resourceful means to study biomolecular interactions when other methods of structural analysis provide incomplete information [ 12 , 13 , 14 , 15 ]. In the case of Aβ peptides, their lack of intrinsic structure in aqueous media, the fact that they gain different structures when interacting with specific partners, and their overall dynamic nature, makes these molecules very difficult to study using solution-based structural methods.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, several important intermolecular events involving Aβ, relevant to processes such as folding or binding, occur in a short time scale that is accessible with computational approaches. The complexity in these systems has also been holding back many computational efforts due to difficulties in obtaining adequate sampling [ 13 , 16 ]. Nevertheless, methods such as molecular dynamics (MD) simulations allow us to study the conformational space of many biomolecules at atomic resolution down to the µs timescale [ 13 , 15 , 17 ].…”

Section: Introductionmentioning

confidence: 99%

“…The complexity in these systems has also been holding back many computational efforts due to difficulties in obtaining adequate sampling [ 13 , 16 ]. Nevertheless, methods such as molecular dynamics (MD) simulations allow us to study the conformational space of many biomolecules at atomic resolution down to the µs timescale [ 13 , 15 , 17 ]. Also, these techniques can be complemented with molecular docking calculations, which provide starting configurations of macromolecular complexes that would otherwise take too long to obtain with MD simulations [ 18 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

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Computational Analysis of the Interactions between the S100B Extracellular Chaperone and Its Amyloid β Peptide Client

Rodrigues

Figueira

Gomes

et al. 2021

IJMS

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S100B is an astrocytic extracellular Ca2+-binding protein implicated in Alzheimer’s disease, whose role as a holdase-type chaperone delaying Aβ42 aggregation and toxicity was recently uncovered. Here, we employ computational biology approaches to dissect the structural details and dynamics of the interaction between S100B and Aβ42. Driven by previous structural data, we used the Aβ25–35 segment, which recapitulates key aspects of S100B activity, as a starting guide for the analysis. We used Haddock to establish a preferred binding mode, which was studied with the full length Aβ using long (1 μs) molecular dynamics (MD) simulations to investigate the structural dynamics and obtain representative interaction complexes. From the analysis, Aβ-Lys28 emerged as a key candidate for stabilizing interactions with the S100B binding cleft, in particular involving a triad composed of Met79, Thr82 and Glu86. Binding constant calculations concluded that coulombic interactions, presumably implicating the Lys28(Aβ)/Glu86(S100B) pair, are very relevant for the holdase-type chaperone activity. To confirm this experimentally, we examined the inhibitory effect of S100B over Aβ aggregation at high ionic strength. In agreement with the computational predictions, we observed that electrostatic perturbation of the Aβ-S100B interaction decreases anti-aggregation activity. Altogether, these findings unveil features relevant in the definition of selectivity of the S100B chaperone, with implications in Alzheimer’s disease.

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“…23,24 Although it is known that 14-3-3 proteins are involved in neurological disorders and the brain is the tissue with most concentration of these proteins, most of the computational studies involve the beta amyloid in comparison of 14-3-3 proteins. [25][26][27] Ingólfsson, et al, 3 recently reported a study of a realistic human brain plasma membrane using advances in computational power and molecular dynamics simulation (MD) techniques.…”

Section: Introductionmentioning

confidence: 99%

Molecular Dynamics Simulation of a Model Brain Membrane with and without a 14-3-3 tau Protein

Contreras-Aburto

Favela-Rosales²,

Arvayo-Zatarain

et al. 2021

Preprint

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An unbalanced composition of lipids and proteins in brain membranes is related to the appearance neurodegenrative diseases and recent investigations show that the 14-3-3 tau protein might relate to some of these diseases. This article reports results from a coarse-grained model brain membrane with and without a 14-3-3 τ/θ protein inside the membrane. We investigated the symmetrized partial density, thickness, diffusion coefficients, and deuterium order parameters of the membrane with and without protein. We observe a slight increase in heads and linkers in the symmetrized partial density of the membrane with the protein inserted and higher values of the deuterium order parameters for the brain model membrane with protein. We observe a reduction in the diffusion coefficient of the fluid membrane in the presence of the transmembrane tau protein. Our findings show that the protein can modify the structural and dynamical properties of the membrane. This work will serve as a guide for future investigations on the interactions of tau proteins with brain membrane models and their relation to neurodegenerative diseases.

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Molecular simulations of amyloid beta assemblies

Cited by 28 publications

References 220 publications

Exploring the Early Stages of the Amyloid Aβ(1–42) Peptide Aggregation Process: An NMR Study

Exploring the Early Stages of the Amyloid Aβ(1–42) Peptide Aggregation Process: An NMR Study

Computational Analysis of the Interactions between the S100B Extracellular Chaperone and Its Amyloid β Peptide Client

Molecular Dynamics Simulation of a Model Brain Membrane with and without a 14-3-3 tau Protein

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