Different Force Fields Give Rise to Different Amyloid Aggregation Pathways in Molecular Dynamics Simulations

Abstract

The progress towards understanding the molecular basis of Alzheimers's disease is strongly connected to elucidating the early aggregation events of the amyloid-β (Aβ) peptide. Molecular dynamics (MD) simulations provide a viable technique to study the aggregation of Aβ into oligomers with high spatial and temporal resolution. However, the results of an MD simulation can only be as good as the underlying force field. A recent study by our group showed that none of the force fields tested can distinguish between aggregation-prone and non-aggregating peptide sequences, producing the same and in most cases too fast aggregation kinetics for all peptides. Since then, new force fields specially designed for intrinsically disordered proteins such as Aβ were developed. Here, we assess the applicability of these new force fields to studying peptide aggregation using the Aβ 16−22 peptide and mutations of it as test case. We investigate their performance in modeling the monomeric state, the aggregation into oligomers, and the stability of the aggregation end product, i.e., the fibrillar state. A main finding is that changing the force field has a stronger effect on the simulated aggregation pathway than changing the peptide sequence. Also the new force fields are not able to reproduce the experimental aggregation propensity order of the peptides. Dissecting the various energy contributions shows that AMBER99SB-disp overestimates the interactions between the peptides and water, thereby inhibiting peptide aggregation.More promising results are obtained with CHARMM36m and especially its version with increased protein-water interactions. It is thus recommended to use this force field for peptide aggregation simulations and base future reparameterizations on it. IntroductionIntrinsically disordered proteins (IDPs) are a class of proteins which are either completely unstructured or contain large disordered regions in their native state, which comes with a high tendency towards self-assembly leading to non-toxic or toxic aggregates and fibrils that may be related to diseases. 1 One of the IDPs is the amyloid-beta peptide (Aβ), forming 2

AlphaFold2: A role for disordered protein prediction?

“…While experimental NMR [53][54][55][56][57][58][59][60][61][62] , and high-quality molecular simulations [63][64][65][66][67][68][69][70][71][72][73][74] are some of the most accurate methods for determining the (dis)ordered nature and dynamics of proteins, fast and computationally efficient methods play an important role.…”

Amyloid-β peptide dimers undergo a random coil to β-sheet transition in the aqueous phase but not at the neuronal membrane

“…When applied to monomeric A , Charmm36m yields more than 80% of the structures in a random coil and extended state, and the remaining ones feature transient -hairpins, which is in acceptable agreement with experimental data ( 20 ). Moreover, Charmm36m outperforms other force fields when it comes to modeling peptide aggregation ( 21 , 22 ). To the best of our knowledge, this simulation study breaks ground on two fronts: 1) It exceeds the simulation time of previous studies modeling A –membrane interactions by an order of magnitude, and 2) it studies the aggregation of A on a bilayer containing more than three different lipid types.…”

An Overview of Several Inhibitors for Alzheimer’s Disease: Characterization and Failure

“…While Amberff03w, CHARMM36m and CHARMM22* overestimated the α-helical structure for IDPs, thus favouring folded protein structures. Therefore, the three specific IDPs FFs were developed by incorporating the changes made in the pre-existing FFs ( Table 1 ) to enable an accurate description of the folded and misfolded proteins [ 15 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ].…”

“…Samantray et al [ 35 ] have examined recently developed IDPs FFs, namely AMBER99SB-disp, CHARMM36m, and CHARMM36 with enhanced protein-water interactions (CHARMM36mW) for the study of Aβ 16-22 (wildtype) aggregation and its mutation F19L Aβ 16−22 (mutation 1) and F19 V/F20 V Aβ 16−22 (mutation2), as model systems for testing purpose. In AMBER99-disp, the peptide-water interactions are increased too much resulting in an inhibition of the Aβ16-22 aggregation.…”

“…These results imply that improving the force field significantly impacted the simulation aggregation pathway than modifying the protein sequence. Samantray et al [ 35 ] strongly encourage the use of CHARMM36mW for studying a full-length Aβ, even though it is not a perfect force field, since it yielded a promising result for aggregation benchmark. Nevertheless, reparameterization of this specific force field is still required.…”