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| Home > Publications database > Different Force Fields Give Rise to Different Amyloid Aggregation Pathways in Molecular Dynamics Simulations |
| Journal Article | FZJ-2021-00343 |
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2020
American Chemical Society64160
Washington, DC
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Please use a persistent id in citations: http://hdl.handle.net/2128/26808 doi:10.1021/acs.jcim.0c01063
Abstract: The progress toward understanding the molecularbasis of Alzheimers’s disease is strongly connected to elucidatingthe early aggregation events of the amyloid-β (Aβ) peptide.Molecular dynamics (MD) simulations provide a viable techniqueto study the aggregation of Aβ into oligomers with high spatial andtemporal resolution. However, the results of an MD simulation canonly be as good as the underlying force field. A recent study by ourgroup showed that none of the common force fields can distinguishbetween aggregation-prone and nonaggregating peptide sequences, producing a similar and in most cases too fast aggregationkinetics for all peptides. Since then, new force fields specially designed for intrinsically disordered proteins such as Aβ weredeveloped. Here, we assess the applicability of these new force fields to studying peptide aggregation using the Aβ16−22 peptide andmutations of it as test case. We investigate their performance in modeling the monomeric state, the aggregation into oligomers, andthe stability of the aggregation end product, i.e., the fibrillar state. A main finding is that changing the force field has a stronger effecton the simulated aggregation pathway than changing the peptide sequence. Also the new force fields are not able to reproduce theexperimental aggregation propensity order of the peptides. Dissecting the various energy contributions shows that AMBER99SB-dispoverestimates the interactions between the peptides and water, thereby inhibiting peptide aggregation. More promising results areobtained with CHARMM36m and especially its version with increased protein−water interactions. It is thus recommended to usethis force field for peptide aggregation simulations and base future reparameterizations on it.
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