Revisiting the earliest signatures of amyloidogenesis: Roadmaps emerging from computational modeling and experiment

Molecular Insights into Cu/Zn Metal Response to the Amyloid β-Peptide (1-42)

Aβ1-40 peptide and Aβ1-42 peptide are the building units of beta-amyloid plaques present in Alzheimer's disease (AD)-affected brain. The binding affinity of various divalent metal ions such as Cu and Zn present in AD-affected brain with different amino acids available in Aβ-peptide became the focus to explore their role in soluble neurotoxic oligomer formation. Cu2+ metal ions are known to enhance the neurotoxicity of the Aβ1-42 peptide by catalyzing the formation of soluble neurotoxic oligomers. The competitive preference of both Cu2+ and Zn2+ simultaneously to interact with the Aβ-peptide is unknown. The divalent Cu and Zn ions were inserted in explicit aqueous Aβ1-42 peptide configurations to get insights into the binding competence of these metal ions with peptides using classical molecular dynamics (MD) simulations. The metal-ion interactions reveal that competitive binding preferences of various peptide sites become metal-ion-specific and differ significantly. For Cu2+, interactions are found to be more significant with respect to those of Asp-7, His-6, Glu-11, and His-14. Asp-1, Glu-3, Asp-7, His-6, Glu-11, and His-13 amino acid residues show higher affinity toward Zn2+ ions. MD simulations show notable variation in the solvent-accessible surface area in the hydrophobic region of the peptide. Infinitesimal mobility was obtained for Zn2+ compared to Cu2+ in an aqueous solution and Cu2+ diffusivity deviated significantly at different time scales, proving its labile features in aqueous Aβ1-42 peptides.

Aggregation of an Amyloidogenic Peptide on Gold Surfaces

Solid surfaces have been shown to affect the aggregation and assembly of many biomolecular systems. One important example is the formation of protein fibrils, which can occur on a range of biological and synthetic surfaces. The rate of fibrillation depends on both the protein structure and the surface chemistry, with the different molecular and oligomer structures adopted by proteins on surfaces likely to be crucial. In this paper, the aggregation of the model amyloidogenic peptide, Aβ(16-22), corresponding to a hydrophobic segment of the amyloid beta protein on a gold surface is studied using molecular dynamics simulation. Previous simulations of this peptide on gold surfaces have shown that it adopts conformations on surfaces that are quite different from those in bulk solution. These simulations show that this then leads to significant differences in the oligomer structures formed in solution and on gold surfaces. In particular, oligomers formed on the surface are low in beta-strands so are unlike the structures formed in bulk solution. When oligomers formed in solution adsorb onto gold surfaces they can then restructure themselves. This can then help explain the inhibition of Aβ(16-22) fibrillation by gold surfaces and nanoparticles seen experimentally.

Identification of Catechins' Binding Sites in Monomeric Aβ42 through Ensemble Docking and MD Simulations

The assembly of the amyloid-β peptide (Aβ) into toxic oligomers and fibrils is associated with Alzheimer's disease and dementia. Therefore, disrupting amyloid assembly by direct targeting of the Aβ monomeric form with small molecules or antibodies is a promising therapeutic strategy. However, given the dynamic nature of Aβ, standard computational tools cannot be easily applied for high-throughput structure-based virtual screening in drug discovery projects. In the current study, we propose a computational pipeline-in the framework of the ensemble docking strategy-to identify catechins' binding sites in monomeric Aβ₄₂. It is shown that both hydrophobic aromatic interactions and hydrogen bonding are crucial for the binding of catechins to Aβ₄₂. Additionally, it has been found that all the studied ligands, especially EGCG, can act as potent inhibitors against amyloid aggregation by blocking the central hydrophobic region of Aβ. Our findings are evaluated and confirmed with multi-microsecond MD simulations. Finally, it is suggested that our proposed pipeline, with low computational cost in comparison with MD simulations, is a suitable approach for the virtual screening of ligand libraries against Aβ.

Single-Particle Resolution of Copper-Associated Annular α-Synuclein Oligomers Reveals Potential Therapeutic Targets of Neurodegeneration

Metal ions stabilize protein–protein interactions and can modulate protein aggregation. Here, using liquid-based atomic force microscopy and molecular dynamics simulations, we study the concentration-dependent effect of Cu²⁺ ions on the aggregation pathway of α-synuclein (α-Syn) proteins, which play a key role in the pathology of Parkinson’s disease. The full spectrum of α-Syn aggregates in the presence and absence of Cu²⁺ ions from monomers to mature fibrils was resolved and quantified at the gold–water interface. Raman spectroscopy confirmed the atomic force microscopy (AFM) findings on the heterogeneity in aggregated states of α-Syn. The formation of annular oligomers was exclusively detected upon incubating α-Syn with Cu²⁺ ions. Our findings emphasize the importance of targeting annular α-Syn protein oligomers for therapeutic intervention and their potential role as biomarkers for early detection and monitoring progression of neurodegeneration.

Characterization of Amyloidogenic Peptide Aggregability in Helical Subspace

Prototypical amyloidogenic peptides amyloid-β (Aβ) and α-synuclein (αS) can undergo helix-helix associations via partially folded helical conformers, which may influence pathological progression to Alzheimer's (AD) and Parkinson's disease (PD), respectively. At the other extreme, stable folded helical conformers have been reported to resist self-assembly and amyloid formation. Experimental characterisation of such disparities in aggregation profiles due to subtle differences in peptide stabilities is precluded by the conformational heterogeneity of helical subspace. The diverse physical models used in molecular simulations allow sampling distinct regions of the phase space and are extensive in capturing the ensemble of rich helical subspace. Robust and powerful computational predictive methods utilizing network theory and free energy mapping can model the origin of helical population shifts in amyloidogenic peptides, which highlight their inherent aggregability. In this chapter, we discuss computational models, methods, design rules, and strategies to identify the driving force behind helical self-assembly and the molecular origin of aggregation resistance in helical intermediates of Aβ42 and αS. By extensive multiscale mapping of intrapeptide interactions, we show that the computational models can capture features that are otherwise imperceptible to experiments. Our models predict that targeting terminal residues may allow modulation and control of initial pathogenic aggregability of amyloidogenic peptides.

Predictive Modeling of Neurotoxic α-Synuclein Polymorphs

Assembly of monomeric α-synuclein (αS) into aggregation-resistant helically folded tetramers and related multimers is a key target for Parkinson's disease (PD). Protein dynamics hampers experimental characterization of the polymorphism of these structures and so computational modeling and simulation is providing a complementary approach to obtain high-resolution structural information on the assembly of αS and interactions with biological surfaces. These computational techniques are particularly valuable for intrinsically disordered proteins (IDPs) and short-lived peptide and protein assemblies with as yet undetermined 3D structures. Experimental observables such as NMR J-coupling constants and chemical shifts can be predicted directly from simulation data, and compared with available experimental data to generate the most physically realistic atomic-resolution structure. For appropriately validated and benchmarked computational models, macroscopic aggregation properties can be related to the calculated thermodynamic properties at an atomic level. In this chapter, we describe a useful protocol for designing helical αS multimers, especially tetramers, and scanning the peptide-membrane interface for cell-bound αS tetramers. These computationally modeled structures are validated by comparison with the range of available known experimental parameters at time of writing in early 2020, and used to generate predictive design rules to motivate and guide experiments.

Long-range Regulation of Partially Folded Amyloidogenic Peptides

Neurodegeneration involves abnormal aggregation of intrinsically disordered amyloidogenic peptides (IDPs), usually mediated by hydrophobic protein-protein interactions. There is mounting evidence that formation of α-helical intermediates is an early event during self-assembly of amyloid-β42 (Aβ42) and α-synuclein (αS) IDPs in Alzheimer’s and Parkinson’s disease pathogenesis, respectively. However, the driving force behind on-pathway molecular assembly of partially folded helical monomers into helical oligomers assembly remains unknown. Here, we employ extensive molecular dynamics simulations to sample the helical conformational sub-spaces of monomeric peptides of both Aβ42 and αS. Our computed free energies, population shifts, and dynamic cross-correlation network analyses reveal a common feature of long-range intra-peptide modulation of partial helical folds of the amyloidogenic central hydrophobic domains via concerted coupling with their charged terminal tails (N-terminus of Aβ42 and C-terminus of αS). The absence of such inter-domain fluctuations in both fully helical and completely unfolded (disordered) states suggests that long-range coupling regulates the dynamicity of partially folded helices, in both Aβ42 and αS peptides. The inter-domain coupling suggests a form of intra-molecular allosteric regulation of the aggregation trigger in partially folded helical monomers. This approach could be applied to study the broad range of amyloidogenic peptides, which could provide a new path to curbing pathogenic aggregation of partially folded conformers into oligomers, by inhibition of sites far from the hydrophobic core.

Edaravone inhibits the conformational transition of amyloid-β42: insights from molecular dynamics simulations

Previous work has shown that edaravone inhibits fibrillogenesis of amyloid-β protein (Aβ). However, the detailed mechanism by which edaravone inhibits the conformational transition of the Aβ42 monomer is not known at the molecular level. Here, explicit-solvent molecular dynamics (MD) simulations were coupled with molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) method to address the issue. MD simulations confirmed that edaravone inhibits the conformational transition of the Aβ42 monomer in a dose-dependent manner. It was found that the direct interactions between edaravone and Aβ42 are responsible for its inhibiting effects. The analysis of binding free energy using the MM-PBSA method demonstrated that the nonpolar interactions provide favourable contributions (about -71.7 kcal/mol). Conversely, the polar interactions are unfavourable for the binding process. A total of 14 residues were identified as greatly contributing to the binding free energy between edaravone and the Aβ42 monomer. In addition, the intra-peptide hydrophobic interactions were weakened and the salt bridge D23-K28 was interrupted by edaravone. Therefore, the conformational transition was inhibited. Our studies provide molecular-level insights into how edaravone molecules inhibit the conformational transition of the Aβ42 monomer, which may be useful for designing amyloid inhibitors.Communicated by Ramaswamy H. Sarma.

Molecular Simulations Reveal Terminal Group Mediated Stabilization of Helical Conformers in Both Amyloid-β42 and α-Synuclein

The presence of partially structured helices in natively unfolded amyloid-β42 (Aβ42) and α-synuclein (αS) has been shown to accelerate fibrillation in the onset of Alzheimer's and Parkinson's disease, respectively. At the other extreme, folded stable helical conformers have also been reported to resist amyloid formation. Recent studies indicate that amyloidogenic aggregation can be impeded using small molecules that stabilize the α-helical monomers and switch off the neurotoxic pathway. We predict a common intrapeptide route to stabilization based on the plasticity of helical conformations of Aβ42 and αS as assessed through extensive atomistic molecular dynamics (MD) computer simulations (∼36 μs) across ten distinct protein force field and water model combinations. Computed free energies and interaction maps (not obtainable from experiments alone) show that flexible terminal groups (N-terminus of Aβ42 and C-terminus of αS) show a tendency to stabilize folded helical conformations in both peptides via primary hydrophobic interactions with central hydrophobic domains, and secondary salt bridges with other domains. These interactions confer aggregation resistance by decreasing the population of partially structured helices and are absent in control simulations of complete unfolding. Computed helical stability is also significantly reduced in terminal-deleted variants. The models suggest new strategies to tackle neurodegeneration by rationally re-engineering terminal groups to optimize their predicted ability to deactivate helical monomers.