Effects of All-Atom Molecular Mechanics Force Fields on Amyloid Peptide Assembly: The Case of Aβ<sub>16–22</sub> Dimer

Man, Viet Hoang; He, Xibing; Derreumaux, Philippe; Ji, Beihong; Xie, Xiang‐Qun; Nguyen, Phuong H.; Wang, Junmei

doi:10.1021/acs.jctc.8b01107

Cited by 113 publications

(166 citation statements)

References 87 publications

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“…Due to the complexity of the parameterization process, various force fields are not guaranteed to exhibit the same effect on biomolecular behavior. [13][14][15][16][17][18][19][20][21][22][23][24][25][26] This has been seen previously when modifica-tions to torsion angle parameters have been shown to impede folding and generate incorrect structures. [27][28][29] Thus force field variations can affect sensitive biomolecular processes such as protein folding pathways.…”

Section: Introductionmentioning

confidence: 58%

Exploiting a Mechanical Perturbation of Titin Domain to Identify How Force Field Parameterization Affects Protein Refolding Pathways

Wang

Marszałek

2019

Preprint

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AbstractMolecular mechanics force fields have been shown to differ in their predictions of processes such as protein folding. To test how force field differences affect predicted protein behavior, we created a mechanically perturbed model of the beta-stranded I91 titin domain based on atomic force spectroscopy data and examined its refolding behavior using six different force fields. To examine the transferability of the force field discrepancies identified by this model, we compared the results to equilibrium simulations of the weakly helical peptide Ac-(AAQAA)3-NH2. The total simulation time was 80 µs. From these simulations we found significant differences in I91 perturbation refolding ability between force fields. Concurrently, Ac-(AAQAA)3-NH2 equilibration experiments indicated that although force fields have similar overall helical frequencies, they can differ in helical lifetimes. The combination of these results suggests that differences in force field parameterization may allow a more direct transition between the beta and alpha regions of the Ramachandran plot thereby affecting both beta-strand refolding ability and helical lifetimes. Furthermore, the combination of results suggests that using mechanically perturbed models can provide a controlled method to gain more insight into how force fields affect protein behavior.

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Section: Introductionmentioning

confidence: 58%

Exploiting a Mechanical Perturbation of Titin Domain to Identify How Force Field Parameterization Affects Protein Refolding Pathways

Wang

Marszałek

2019

Preprint

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“…experimental data for Aβ [63,64]. Moreover, AMBER FF14SB is fully compatible with 97 LIPID14 force-field [59], which is expected to provide optimal accuracy for both lipids 98 and peptide in the simulations.…”

Section: Introductionmentioning

confidence: 96%

“…AMBER FF14SB force-field is an improved version of FF99SB [60] used in 93 our previous simulations [52, 61]. Although older CHARMM force-fields tend to provide 94 better results for Aβ peptide than old AMBER force-fields [62], new AMBER versions, 95 especially AMBER FF14SB and CHARMM36m provide good agreement with 96experimental data for Aβ [63,64]. Moreover, AMBER FF14SB is fully compatible with 97 LIPID14 force-field [59], which is expected to provide optimal accuracy for both lipids 98 and peptide in the simulations.…”

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confidence: 99%

A computational model to unravel the function of amyloid-βpeptide in contact with a phospholipid membrane

Penna

Krupa

Huy

et al. 2020

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The normal synapse activity involves the release of copper and other divalent cations in the synaptic region. These ions have a strong impact on the membrane properties, especially when the membrane has charged groups, like it is the case of synapse. In this work we use an atomistic computational model of dimyristoyl-phosphatidylcholine (DMPC) membrane bilayer. We perturb this model with a simple model of divalent cation (Mg 2+ ), and with a single amyloid-β (Aβ) peptide of 42 residues, both with and without a single Cu 2+ ion bound to the N-terminus. In agreement with experimental results reported in the literature, the model confirms that divalent cations locally destabilize the DMPC membrane bilayer, and, for the first time, that the monomeric form of Aβ helps in avoiding the interactions between divalent cations and DMPC, preventing significant effects on the DMPC bilayer properties. These results are discussed in the frame of a protective role of diluted Aβ peptide floating in the synaptic region. Author summaryWe modelled the behavior of a Mg 2+ divalent cation, with the size of Zn 2+ and Cu 2+ , in contact with a phosphatidyl lipid bilayer. We also modelled the monomeric amyloid-β peptide 1-42, both free and Cu-loaded, the latter mimicking the final step of the binding between the peptide and the divalent cation. On the basis of the simulation results, we propose that the peptide hinders the strong interactions between the divalent cation and the membrane. Introduction 1Alzheimer's disease is a degenerative disease, with one histological hallmark being 2 extracellular deposits in the central nervous system [1]. These deposits are made of 3 amyloid peptides originated by the amyloid precursor protein (APP), a trans-membrane 4 protein with a multimodal function [2]. Amyloid-β (Aβ) peptides are produced with 5 proteolysis of APP at the membrane interface, by the enzymes β and γ-secretases. The 6 γ cleavage, that produces most of the neurotoxic peptides (39-42 residues), occurs 7 January 14, 2020 1/29 deeper in the membrane bilayer compared to β cleavage [3]. The production of these 8 toxic peptides at the membrane interface can have many important implications [4], 9 even before peptide aggregation occur and when oligomers are more abundant than 10 protofibrils [5, 6]: i) the toxic pathway can be influenced by interactions between 11 peptides and of peptides with the membrane; ii) the peptide, depending on its 12 concentration, can destabilize the membrane, contributing to cell instability and neuron 13 death (apoptosis). Both these effects are eventually exerted in a complex frame, with 14 many molecules present: APP N-terminus (before the cleavage); peptides in monomeric, 15 oligomeric and pre-fibrillar assemblies; other cofactors, like metal ions. Thus, even at 16 the monomer level, the interactions between amyloid peptides and biological membranes 17 are still poorly understood [7]. More complete models are required to contribute to 18 recent views of APP and Aβ, where Aβ aggregation is interpreted as a l...

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“…One of the main conclusions was that GROMOS54A7 13 and OPLS-AA 14,15 overstabilize protein-protein interactions, leading to an overestimation of the aggregation speed and an inhibition of protein-aggregate dissociation. Thereafter, Derreumaux and coworkers investigated the protein aggregation behavior for the Aβ 16−22 dimer using 17 different FFs in combination with conventional MD simulations, 16 following up their previous work where they had employed replica exchange MD to study dimers and trimers of Aβ 16−22 . 17 They concluded that FFs from CHARMM with updated CMAP correction 18,19 such as CHARMM22*, 20 CHARMM36, 21 and CHARMM36m, 9 along with FFs based on AMBER99 22 with modified torsional parameters for the backbone and for the four amino acids Ile, Leu, Asp, and Asn like AMBER99SB-ILDN 23 and AMBER14SB 24 are best suited for studying amyloid aggregation.…”

Section: Introductionmentioning

confidence: 99%

Different force fields give rise to different amyloid aggregation pathways in molecular dynamics simulations

Samantray

Yin

Kav

et al. 2020

Preprint

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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 Aβ16−22 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.

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Effects of All-Atom Molecular Mechanics Force Fields on Amyloid Peptide Assembly: The Case of Aβ_16–22 Dimer

Cited by 113 publications

References 87 publications

Exploiting a Mechanical Perturbation of Titin Domain to Identify How Force Field Parameterization Affects Protein Refolding Pathways

Exploiting a Mechanical Perturbation of Titin Domain to Identify How Force Field Parameterization Affects Protein Refolding Pathways

A computational model to unravel the function of amyloid-βpeptide in contact with a phospholipid membrane

Different force fields give rise to different amyloid aggregation pathways in molecular dynamics simulations

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Effects of All-Atom Molecular Mechanics Force Fields on Amyloid Peptide Assembly: The Case of Aβ16–22 Dimer

Cited by 113 publications

References 87 publications

Exploiting a Mechanical Perturbation of Titin Domain to Identify How Force Field Parameterization Affects Protein Refolding Pathways

Exploiting a Mechanical Perturbation of Titin Domain to Identify How Force Field Parameterization Affects Protein Refolding Pathways

A computational model to unravel the function of amyloid-βpeptide in contact with a phospholipid membrane

Different force fields give rise to different amyloid aggregation pathways in molecular dynamics simulations

Contact Info

Product

Resources

About

Effects of All-Atom Molecular Mechanics Force Fields on Amyloid Peptide Assembly: The Case of Aβ_16–22 Dimer