Compact fibril-like structure of amyloid β-peptide (1-42) monomers

Structure Comparison of Beta Amyloid Peptide Aβ 1-42 Isoforms. Molecular Dynamics Modeling

Beta amyloid peptide Aβ 1-42 (Aβ42) has a unique dual role in the human organism, as both the peptide with an important physiological function and one of the most toxic biological compounds provoking Alzheimer's disease (AD). There are several known Aβ42 isoforms that we discuss here that are highly neurotoxic and lead to the early onset of AD. Aβ42 is an intrinsically disordered protein with no experimentally solved structure under physiological conditions. The objective of this research was to establish the appropriate molecular dynamics (MD) methodology and model a uniform set of structures for the Aβ42 isoforms that form the core of this study. For that purpose, force field selection and verification including convergence testing for MD simulations was made. Replica exchange MD and conventional MD modeling of several Aβ42 and Aβ16 isoforms that have neurotoxic and amyloidogenic effects impacting the severity of Alzheimer's disease were carried out with the optimal force field and solvent parameters. A standardized ensemble of structures for the Aβ42 and Aβ16 isoforms covering 30-50% of the conformational ensembles extracted from the free energy minima was calculated from MD trajectories. The resulting data set of modeled structures includes Aβ42 wild type, isoD7, pS8, D7H, and H6R-Aβ42 and Aβ16 wild type, isoD7, pS8, D7H, and H6R-Aβ16. The representative structures are given in the Supporting Information; they are open for public access. In the study, we also evaluated the differences between the structures of Aβ42 isoforms and speculate on their possible relevance to the known functions. Utilizing several representative structures for a single disordered protein for docking, with their subsequent averaging by conformations, would markedly increase the reliability of docking results.

Unlocking novel therapies: cyclic peptide design for amyloidogenic targets through synergies of experiments, simulations, and machine learning

Existing therapies for neurodegenerative diseases like Parkinson's and Alzheimer's address only their symptoms and do not prevent disease onset. Common therapeutic agents, such as small molecules and antibodies struggle with insufficient selectivity, stability and bioavailability, leading to poor performance in clinical trials. Peptide-based therapeutics are emerging as promising candidates, with successful applications for cardiovascular diseases and cancers due to their high bioavailability, good efficacy and specificity. In particular, cyclic peptides have a long in vivo stability, while maintaining a robust antibody-like binding affinity. However, the de novo design of cyclic peptides is challenging due to the lack of long-lived druggable pockets of the target polypeptide, absence of exhaustive conformational distributions of the target and/or the binder, unknown binding site, methodological limitations, associated constraints (failed trials, time, money) and the vast combinatorial sequence space. Hence, efficient alignment and cooperation between disciplines, and synergies between experiments and simulations complemented by popular techniques like machine-learning can significantly speed up the therapeutic cyclic-peptide development for neurodegenerative diseases. We review the latest advancements in cyclic peptide design against amyloidogenic targets from a computational perspective in light of recent advancements and potential of machine learning to optimize the design process. We discuss the difficulties encountered when designing novel peptide-based inhibitors and we propose new strategies incorporating experiments, simulations and machine learning to design cyclic peptides to inhibit the toxic propagation of amyloidogenic polypeptides. Importantly, these strategies extend beyond the mere design of cyclic peptides and serve as template for the de novo generation of (bio)materials with programmable properties.

Effect of Terahertz Waves on the Structure of the Aβ42 Monomer, Dimer, and Protofibril: Insights from Molecular Dynamics Simulations

Amyloid-β (Aβ) and its assemblies play important roles in the pathogenesis of Alzheimer's disease (AD). Recent studies conducted by experimental and computational researchers have extensively explored the structure, assembly, and influence of biomolecules and cell membranes on Aβ. However, the impact of terahertz waves on the structures of Aβ monomers and aggregates remains largely unexplored. In this study, we systematically investigate the molecular mechanisms by which terahertz waves affect the structure of the Aβ42 monomer, dimer, and tetramer through all-atom molecular dynamics (MD) simulations. Our findings indicate that terahertz waves at a specific frequency (42.55 THz) can enhance intramolecular and intermolecular interactions in the Aβ42 monomer and dimer, respectively, by resonating with the symmetric stretching mode of the -COO- groups and the symmetric bending/stretching mode of -CH3 groups. Consequently, the β-structure content of the Aβ42 monomer is greatly increased, and the binding energy between the monomers in the Aβ42 dimer is significantly enhanced. Additionally, our observations suggest that terahertz waves can mildly stabilize the structure of tetrameric protofibrils by enhancing the interactions among peripheral peptides. Furthermore, we also investigated the effect of the frequency of terahertz waves on the structure of Aβ42. The present study contributes to a better understanding of the impact of external fields on the biobehavior of Aβ42 peptides and may shed some light on the potential risks associated with electromagnetic field radiation.

Inherent Adaptivity of Alzheimer Peptides to Crowded Environments

Amyloid β (Aβ) is the major constituent in senile plaques of Alzheimer's disease in which peptides initially undergo structural conversions to form elongated fibrils. The impact of crowding on the fibrillation pathways of Aβ40 and Aβ42 , the most common peptide isoforms are studied. PEG and Ficoll are used as model crowders to mimic a macromolecular enriched surrounding. The fibrillar growth is monitored with the help of ThT-fluorescence assays in order to extract two rates describing primary and secondary processes of nucleation and growth. Techniques as fluorescence correlation spectroscopy and analytical ultracentrifugation are used to discuss oligomeric states; fibril morphologies are investigated using negative-staining transmission electron microscopy. While excluded volume effects imposed by macromolecular crowding are expected to always increase rates of intermolecular interactions and structural conversion, a vast variety of effects are found depending on the peptide, the crowder, or ionic strength of the solution. While investigations of the obtained rates with respect to a reactant-occluded model are capable to display specific surface interactions with the crowder, the employment of crystallization-like models reveal the crowder-induced entropic gain withΔ Δ G fib crow = - 116 ± 21 k $\Delta \Delta G_{\text{fib}}^{\text{crow}}=-116\pm 21\; k$ J mol-1 per volume fraction of the crowder.

Dissecting the Molecular Mechanisms of the Co-Aggregation of Aβ40 and Aβ42 Peptides: A REMD Simulation Study

The aggregation of amyloid-β protein (Aβ) into oligomers and amyloid fibrils is closely related to Alzheimer's disease (AD). Aβ40 and Aβ42, as two most prominent isoforms of Aβ peptides, can cross-interact with each other and form co-aggregates, which affect the progression of the disease. However, the molecular determinants underlying Aβ40 and Aβ42 cross-interaction and the structural details of their co-oligomers remain elusive. Herein, we performed all-atom explicit-solvent replica exchange molecular dynamics simulations on Aβ40-Aβ42 heterogeneous and Aβ40/Aβ42 homogeneous dimer systems to dissect the co-aggregation mechanisms of the two isoforms. Our results show that the interpeptide main-chain interaction of Aβ40-Aβ42 is stronger than that of Aβ40-Aβ40 and Aβ42-Aβ42. The positions of hotspot residues in heterodimers and homodimers display high similarity, implying similar molecular recognition sites for both cross-interaction and self-interaction. Contact maps of Aβ40-Aβ42 heterodimers reveal that residue pairs crucial for cross-interaction are mostly located in the C-terminal hydrophobic regions of Aβ40 and Aβ42 peptides. Conformational analysis shows that Aβ40 and Aβ42 monomers can co-assemble into β-sheet-rich heterodimers with shorter β-sheets than those in homodimers, which is decremental to monomer addition. Similar molecular recognition sites and β-sheet distribution of Aβ40 and Aβ42 peptides are observed in heterodimers and homodimers, which may provide the molecular basis for the two isoforms' co-aggregation and cross-seeding. Our work dissects the co-aggregation mechanisms of Aβ40 and Aβ42 peptides at the atomic level, which will help for in-depth understanding of the cross-talk between the two Aβ isoforms and the pathogenesis of AD.

Modulation of Aβ42 Aggregation Kinetics and Pathway by Low-Molecular-Weight Inhibitors

The aggregation of amyloid-β 42 (Aβ42) is directly related to the pathogenesis of Alzheimer's disease. Here, we have investigated the early stages of the aggregation process, during which most of the cytotoxic species are formed. Aβ42 aggregation kinetics, characterized by the quantification of Aβ42 monomer consumption, were tracked by real-time solution NMR spectroscopy (RT-NMR) allowing the impact that low-molecular-weight (LMW) inhibitors and modulators exert on the aggregation process to be analysed. Distinct differences in the Aβ42 kinetic profiles were apparent and were further investigated kinetically and structurally by using thioflavin T (ThT) and transmission electron microscopy (TEM), respectively. LMW inhibitors were shown to have a differential impact on early-state aggregation. Insight provided here could direct future therapeutic design based on kinetic profiling of the process of fibril formation.

Modeling structural interconversion in Alzheimers' amyloid beta peptide with classical and intrinsically disordered protein force fields

A comprehensive understanding of the aggregation mechanism in amyloid beta 42 (Aβ42) peptide is imperative for developing therapeutic drugs to prevent or treat Alzheimer's disease. Because of the high flexibility and lack of native tertiary structures of Aβ42, molecular dynamics (MD) simulations may help elucidate the peptide's dynamics with atomic details and collectively improve ensembles not seen in experiments. We applied microsecond-timescale MD simulations to investigate the dynamics and conformational changes of Aβ42 by using a newly developed Amber force field (ff14IDPSFF). We compared the ff14IDPSFF and the regular ff14SB force field by examining the conformational changes of two distinct Aβ42 monomers in explicit solvent. Conformational ensembles obtained by simulations depend on the force field and initial structure, Aβ42^α-helix or Aβ42^β-strand. The ff14IDPSFF sampled a high ratio of disordered structures and diverse β-strand secondary structures; in contrast, ff14SB favored helicity during the Aβ42^α-helix simulations. The conformations obtained from Aβ42^β-strand simulations maintained a balanced content in the disordered and helical structures when simulated by ff14SB, but the conformers clearly favored disordered and β-sheet structures simulated by ff14IDPSFF. The results obtained with ff14IDPSFF qualitatively reproduced the NMR chemical shifts well. In-depth peptide and cluster analysis revealed some characteristic features that may be linked to early onset of the fibril-like structure. The C-terminal region (mainly M35-V40) featured in-registered anti-parallel β-strand (β-hairpin) conformations with tested systems. Our work should expand the knowledge of force field and structure dependency in MD simulations and reveals the underlying structural mechanism-function relationship in Aβ42 peptides. Communicated by Ramaswamy H. Sarma.

Interaction of Therapeutic d-Peptides with Aβ42 Monomers, Thermodynamics, and Binding Analysis

The aggregation of the amyloid-β (Aβ) peptide is a major hallmark of Alzheimer's disease. This peptide can aggregate into oligomers, proto-fibrils, and mature fibrils, which eventually assemble into amyloid plaques. The peptide monomers are the smallest assembly units and play an important role in most of the individual processes involved in amyloid fibril formation, such as primary and secondary nucleation and elongation. Several d-peptides have been confirmed as promising candidates to inhibit the aggregation of Aβ into toxic oligomers and fibrils by specifically interacting with monomeric species. In this work, we elucidate the structural interaction and thermodynamics of binding between three d-peptides (D3, ANK6, and RD2) and Aβ42 monomers by means of enhanced molecular dynamics simulations. Our study derives thermodynamic energies in good agreement with experimental values and suggests that there is an enhanced binding for D3 and ANK6, which leads to more stable complexes than for RD2. The binding of D3 to Aβ42 is shown to be weakly exothermic and mainly entropically driven, whereas the complex formation between the ANK6 and RD2 with the Aβ42 free monomer is weakly endothermic. In addition, the changes in the solvent-accessible surface area and the radius of gyration support that the binding between Aβ42 and d-peptides is mainly driven by electrostatic and hydrophobic interactions and leads to more compact conformations.

Interactive patches over amyloid-β oligomers mediate fractal self-assembly

The monomeric units of intrinsically disordered proteins self-assemble into oligomers, protofilaments, and eventually fibrils which may turn into amyloid. The aggregation of these proteins is primarily studied in bulk with no restriction on their degrees of freedom. Herein we experimentally demonstrate that amyloid-β (Aβ) aggregation under diffusion-limited conditions leads to its fractal self-assembly. Confocal microscopy and scanning electron microscopy with energy dispersion x-ray analysis were used to confirm that the fractal self-assemblies were formed from Aβ rather than the salt present in the two supporting media: deionized water and phosphate buffered saline. The results from the molecular docking experiments implicated that electrostatic and hydrophobic patches on the solvent-accessible surface area of the Aβ oligomers mediate the fractal self-assembly. These implications were tested with laser light scattering experiments on the oligomers formed by breaking mature fibrils of Aβ through sonication, which were observed to self-assemble into fractals when sonicated solutions were drop casted. The electrostatic interactions modulate the fractal morphologies with pH of the solution, which leads to a morphological phase transition observed through the variation in their fractal dimension. These transitions provide experimental evidence for the existing theoretical framework in terms of different kinetic models. The higher surface-to-volume ratio of these fractal self-assemblies may have applications in drug delivery, biosensing, and other biomedical applications.

Impact of Cu(II) and Al(III) on the conformational landscape of amyloidβ1-42

Metal ions have been found to play an important role in the formation of extracellular β-amyloid plaques, a major hallmark of Alzheimer's disease. In the present study, the conformational landscape of Aβ42 with Al(iii) and Cu(ii) has been explored using Gaussian accelerated molecular dynamics. Both metals reduce the flexibility of the peptide and entail a higher structural organization, although to different degrees. As a general trend, Cu(ii) binding leads to an increased α-helix content and to the formation of two α-helices that tend to organize in a U-shape. By contrast, most Al(iii) complexes induce a decrease in helical content, leading to more extended structures that favor the appearance of transitory β-strands.

β-Amyloid Peptide 1-42-Conjugated Magnetic Nanoparticles for the Isolation and Purification of Glycoproteins in Egg White

Aβ_1-42-conjugated magnetic nanoparticles, Aβ_1-42@MNP, were prepared by covalently coupling Aβ_1-42 to hyperbranched polyethyleneimine (PEI)-modified magnetic nanoparticles via N-(3-dimethylaminopropyl)-N'-ethylcarbodiimide hydrochloride (EDC). Aβ_1-42's high binding capacity to glycosyl groups facilitates Aβ_1-42@MNP composite to be a promising selective adsorbent for glycoproteins in egg whites. In our study, under conditions of pH 4.0, the adsorption efficiency of Aβ_1-42@MNP composite for ovalbumin (100 μg mL^-1) was 98.4% and its maximum adsorption capacity was 344.8 mg g ^-1; under the condition of pH 4.0 and 200 mmol L^-1 NaCl, its adsorption efficiencies for ovalbumin and ovotransferrin were 96.9% and 60.0%, respectively. According to these primary data, in practice, ovalbumin was removed from egg white by Aβ_1-42@MNP composite at pH 4.0 (step I), and then after adding NaCl until the final salt concentration reached 200 mmol L^-1 (pretreated egg white), we utilized the same adsorbent to further isolate/purify glycoproteins (step II). SDS-PAGE results showed that Aβ_1-42@MNP composite could largely remove ovalbumin in step I and could isolate/purify the remaining ovalbumin and ovotransferrin in step II. LC-MS/MS analysis results showed that the removal of ovalbumin reduced its percentage in egg white samples from 32.93% to 11.05% in step I and the remaining ovalbumin and ovotransferrin were enriched in step II, where the final percentage reached 11.6% and 12.6%, respectively. In summary, 81 protein species were identified after two-step extraction with Aβ_1-42@MNP on egg white, while only 46 protein species were identified directly from raw egg white without any pretreatment. This work well illustrates the excellent adsorption performance of Aβ_1-42@MNP composite to glycoproteins and its potential in the application of proteomic studies on low-abundance proteins in egg white.