Atomic-Level Description of Amyloid β-Dimer Formation

How ATP suppresses the fibrillation of amyloid peptides: analysis of the free-energy contributions

Recent experiments have revealed that adenosine triphosphate (ATP) suppresses the fibrillation of amyloid peptides - a process closely linked to neurodegenerative diseases such as Alzheimer's and Parkinson's. Apart from the adsorption of ATP onto amyloid peptides, the molecular understanding is still limited, leaving the underlying mechanism for the fibrillation suppression by ATP largely unclear, especially in regards to the molecular energetics. Here we provide an explanation at the molecular scale by quantifying the free energies using all-atom molecular dynamics simulations. We found that the changes of the free energies due to the addition of ATP lead to a significant equilibrium shift towards monomeric peptides in agreement with experiments. Despite ATP being a highly charged species, the decomposition of the free energies reveals that the van der Waals interactions with the peptide are decisive in determining the relative stabilization of the monomeric state. While the phosphate moiety exhibits strong electrostatic interactions, the compensation by the water solvent results in a minor, overall Coulomb contribution. Our quantitative analysis of the free energies identifies which intermolecular interactions are responsible for the suppression of the amyloid fibril formation by ATP and offers a promising method to analyze the roles of similarly complex cosolvents in aggregation processes.

Protein Corona Formation and Aggregation of Amyloid β 1-40-Coated Gold Nanocolloids

Amyloid fibrillogenesis is a pathogenic protein aggregation process that occurs through a highly ordered process of protein-protein interactions. To better understand the protein-protein interactions involved in amyloid fibril formation, we formed nanogold colloid aggregates by stepwise additions of ∼2 nmol of amyloid β 1-40 peptide (Aβ1-40) at pH ∼3.7 and ∼25 °C. The processes of protein corona formation and building of gold colloid [diameters (d) of 20 and 80 nm] aggregates were confirmed by a red-shift of the surface plasmon resonance (SPR) band, λpeak, as the number of Aβ1-40 peptides [N(Aβ1-40)] increased. The normalized red-shift of λpeak, Δλ, was correlated with the degree of protein aggregation, and this process was approximated as the adsorption isotherm explained by the Langmuir-Freundlich model. As the coverage fraction (θ) was analyzed as a function of ϕ, which is the N(Aβ1-40) per total surface area of nanogold colloids available for adsorption, the parameters for explaining the Langmuir-Freundlich model were in good agreement for both 20 and 80 nm gold, indicating that ϕ could define the stage of the aggregation process. Surface-enhanced Raman scattering (SERS) imaging was conducted at designated values of ϕ and suggested that a protein-gold surface interaction during the initial adsorption stage may be dependent on the nanosize. The 20 nm gold case seems to prefer a relatively smaller contacting section, such as a -C-N or C═C bond, but a plane of the benzene ring may play a significant role for 80 nm gold. Regardless of the size of the particles, the β-sheet and random coil conformations were considered to be used to form gold colloid aggregates. The methodology developed in this study allows for new insights into protein-protein interactions at distinct stages of aggregation.

Non-Ewald methods for evaluating the electrostatic interactions of charge systems: similarity and difference

In molecular simulations, it is essential to properly calculate the electrostatic interactions of particles in the physical system of interest. Here we consider a method called the non-Ewald method, which does not rely on the standard Ewald method with periodic boundary conditions, but instead relies on the cutoff-based techniques. We focus on the physicochemical and mathematical conceptual aspects of the method in order to gain a deeper understanding of the simulation methodology. In particular, we take into account the reaction field (RF) method, the isotropic periodic sum (IPS) method, and the zero-multipole summation method (ZMM). These cutoff-based methods are based on different physical ideas and are completely distinguishable in their underlying concepts. The RF and IPS methods are "additive" methods that incorporate information outside the cutoff region, via dielectric medium and isotropic boundary condition, respectively. In contrast, the ZMM is a "subtraction" method that tries to remove the artificial effects, generated near the boundary, from the cutoff sphere. Nonetheless, we find physical and/or mathematical similarities between these methods. In particular, the modified RF method can be derived by the principle of neutralization utilized in the ZMM, and we also found a direct relationship between IPS and ZMM.

Atomistic Pictures of Self-Assembled Helical Peptide Nanofibers

Spontaneous self-assembly of peptides has been at the forefront of supramolecular chemistry and materials science research over the last two decades. Despite the wealth of information on the morphology of the assembled objects, atomic resolution details of molecular arrangements inside them are largely unknown. In this paper, we investigated non-covalent assemblies of zwitterionic l-phenylalanine tripeptides in water using all-atom explicit-solvent molecular dynamics computer simulations. Our studies produced atomistic pictures of spontaneously assembled nanofibers composed of hundreds of peptide molecules. The dimensions of the nanofibers varied from 10 to 18 nm, with irregular helical twists along the long axes. Previously published experimental data, acquired under similar conditions, provided direct validation of the fibrous morphology and indirect support for the non-trivial helicity observed in our simulations. Quantitative analyses of peptide-water and peptide-peptide interactions revealed heterogeneous local environments of molecules across the nanometer length scales. The combination of electrostatic, hydrogen bonding, van der Waals, and hydrophobic interactions, adopted by a single molecule, was dependent on its relative position inside the fiber. Despite the presence of three hydrophobic phenyl groups, very few molecules were found to be completely shielded from the surrounding water, indicating a subtle role of the hydrophobic effect. Limited conformational flexibility of the tripeptide, along with bare electrostatic interactions, appeared to play a crucial role in the emergence of fibrous morphology of the nanostructures. Our analyses led us to formulate plausible qualitative explanations of the assembly behavior in terms of thermodynamic driving forces and kinetic considerations. We established a clear relationship between details of chemical interactions operating within few molecules and characteristics of the self-assembled states at much longer length scales.

Key Residue for Aggregation of Amyloid-β Peptides

It is known that oligomers of amyloid-β (Aβ) peptide are associated with Alzheimer's disease. Aβ has two isoforms: Aβ40 and Aβ42. Although the difference between Aβ40 and Aβ42 is only two additional C-terminal residues, Aβ42 aggregates much faster than Aβ40. It is unknown what role the C-terminal two residues play in accelerating aggregation. Since Aβ42 is more toxic than Aβ40, its oligomerization process needs to be clarified. Moreover, clarifying the differences between the oligomerization processes of Aβ40 and Aβ42 is essential to elucidate the key factors of oligomerization. Therefore, to investigate the dimerization process, which is the early oligomerization process, Hamiltonian replica-permutation molecular dynamics simulations were performed for Aβ40 and Aβ42. We identified a key residue, Arg5, for the Aβ42 dimerization. The two additional residues in Aβ42 allow the C-terminus to form contact with Arg5 because of the electrostatic attraction between them, and this contact stabilizes the β-hairpin. This β-hairpin promotes dimer formation through the intermolecular β-bridges. Thus, we examined the effects of amino acid substitutions of Arg5, thereby confirming that the mutations remarkably suppressed the aggregation of Aβ42. Moreover, the mutations of Arg5 suppressed the Aβ40 aggregation. It was found by analyzing the simulations that Arg5 is important for Aβ40 to form intermolecular contacts. Thus, it was clarified that the role of Arg5 in the oligomerization process varies due to the two additional C-terminal residues.

Development of a Hybrid-Resolution Force Field for Peptide Self-Assembly Simulations: Optimizing Peptide-Peptide and Peptide-Solvent Interactions

Atomic descriptions of peptide self-assembly are crucial to an understanding of disease-related peptide aggregation and the design of peptide-assembled materials. Obtaining these descriptions through computer simulation is challenging because current force fields, which were not designed for this process and are often unable to describe correctly peptide self-assembly behavior and the sequence dependence. Here, we developed a framework using dipeptide aggregation as a model system to improve force fields for simulations of self-assembly. Aggregation-related structural properties were designed and used to guide the optimization of peptide-peptide and peptide-solvent interactions. With this framework, we developed a self-assembly force field, termed PACE-ASM, by reoptimizing a hybrid-resolution force field that was originally developed for folding simulation. With its applicability in folding simulations, the new PACE was used to simulate the self-assembly of two disease-related short peptides, Aβ_16-21 and PHF6, into β-sheet-rich cross-β amyloids. These simulations reproduced the crystal structures of Aβ_16-21 and PHF6 amyloids at near-atomic resolution and captured the difference in packing orientations between the two sequences, a task which is challenging even with all-atom force fields. Apart from cross-β amyloids, the self-assembly of emerging helix-rich cross-α amyloids by another peptide PSMα3 can also be correctly described with the new PACE, manifesting the versatility of the force field. We demonstrated that the ability of the PACE-ASM to model peptide self-assembly is based largely on its improved description of peptide-peptide and peptide-solvent interactions. This was achieved with our optimization framework that can readily identify and address the deficiency in describing these interactions.

Replica permutation with solute tempering for molecular dynamics simulation and its application to the dimerization of amyloid-β fragments

We propose the replica permutation with solute tempering (RPST) by combining the replica-permutation method (RPM) and the replica exchange with solute tempering (REST). Temperature permutations are performed among more than two replicas in RPM, whereas temperature exchanges are performed between two replicas in the replica-exchange method (REM). The temperature transition in RPM occurs more efficiently than in REM. In REST, only the temperatures of the solute region, the solute temperatures, are exchanged to reduce the number of replicas compared to REM. Therefore, RPST is expected to be an improved method taking advantage of these methods. For comparison, we applied RPST, REST, RPM, and REM to two amyloid-β(16–22) peptides in explicit water. We calculated the transition ratio and the number of tunneling events in the temperature space and the number of dimerization events of amyloid-β(16–22) peptides. The results indicate that, in RPST, the number of replicas necessary for frequent random walks in the temperature and conformational spaces is reduced compared to the other three methods. In addition, we focused on the dimerization process of amyloid-β(16–22) peptides. The RPST simulation with a relatively small number of replicas shows that the two amyloid-β(16–22) peptides form the intermolecular antiparallel β-bridges due to the hydrophilic side-chain contact between Lys and Glu and hydrophobic side-chain contact between Leu, Val, and Phe, which stabilizes the dimer of the peptides.

The Effects of Different Glycosaminoglycans on the Structure and Aggregation of the Amyloid-β (16-22) Peptide

Aggregates of the amyloid-β (Aβ) peptide are implicated as a causative substance in Alzheimer's disease. Molecular dynamics simulations provide valuable contributions for elucidating the conformational transitions of monomeric and aggregated forms of Aβ be it in solution or in the presence of other molecules. Here, we study the effects of four different glycosaminoglycans (GAGs), three sulfated ones and a nonsulfated one, on the aggregation of Aβ_16-22. From experiments, it has been suggested that GAGs, which belong to the main components of the brain's extracellular space, favor amyloid fibril formation. Our simulation results reveal that the binding of Aβ_16-22 to the GAGs is driven by electrostatic attraction between the negative GAG charges and the positively charged K16 of Aβ_16-22. While these interactions have only minor effects on the GAG and Aβ_16-22 conformations at the 1 Aβ_16-22/1 GAG ratio, at the 2:2 stoichiometry the aggregation of Aβ_16-22 is considerably changed. In solution, the aggregation of Aβ_16-22 is strongly influenced by K16-E22 attraction, leading to antiparallel β-sheets. In the presence of GAGs, on the other hand, the interaction of K16 with the GAGs increases the importance of the hydrophobic interactions during Aβ_16-22 aggregation, which in turn yields parallel alignments. A templating and ordering effect of the GAGs on the Aβ_16-22 aggregates is observed. In summary, this study provides new insight at the atomic level on GAG-amyloid interactions, strengthening the view that sulfation of the GAGs plays a major role in this context.

Aggregation of disease-related peptides

Protein misfolding and aggregation of amyloid proteins is the fundamental cause of more than 20 diseases. Molecular mechanisms of the self-assembly and the formation of the toxic aggregates are still elusive. Computer simulations have been intensively used to study the aggregation of amyloid peptides of various amino acid lengths related to neurodegenerative diseases. We review atomistic and coarse-grained simulations of short amyloid peptides aimed at determining their transient oligomeric structures and the early and late aggregation steps.

Amino acid conformations control the morphological and chiral features of the self-assembled peptide nanostructures: Young investigators perspective

HYPOTHESIS

A variety of nanostructures with different chiral features can be self-assembled from short peptides with highly similar sequences. We hypothesize that these supramolecular nanostructures are ruled by the constituent amino acid residues which adopt their conformations under the influence of intra-/inter-molecular interactions during peptide self-assembly.

APPROACH

Through reviewing recent advances in the self-assembly of short peptides and focusing on the relationship between amino acid conformations, peptide secondary structures and intra-/inter-molecular interactions within the supramolecular architectures, we aim to rationalize the complex interactive processes involved in the self-assembly of short, designed peptides.

RESULTS

Given the highly complexing interactive processes, the adoption of amino acid conformations and their control over peptide self-assembly consist of 4 main steps: (1) Each amino acid residue adopts its unique conformation in a specific sequence; (2) The sequence exhibits its own main chain geometry and determines the propensity of the intermolecular alignment within the building block; (3) The structural propensity of the building block and the packing mode between them determine the self-assembled structural features such as twisting, growth and chirality; (4) In addition to intra-/inter-molecular interactions, inter-sheet and inter-building block interactions could also affect the residue conformations and nanostructures, causing structural readjustment.

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

We investigated the effects of 17 widely used atomistic molecular mechanics force fields (MMFFs) on the structures and kinetics of amyloid peptide assembly. To this end, we performed large-scale all-atom molecular dynamics simulations in explicit water on the dimer of the seven-residue fragment of the Alzheimer's amyloid-β peptide, Aβ16-22, for a total time of 0.34 ms. We compared the effects of these MMFFs by analyzing various global reaction coordinates, secondary structure contents, the fibril population, the in-register and out-of-register architectures, and the fibril formation time at 310 K. While the AMBER94, AMBER99, and AMBER12SB force fields do not predict any β-sheets, the seven force fields, AMBER96, GROMOS45a3, GROMOS53a5, GROMOS53a6, GROMOS43a1, GROMOS43a2, and GROMOS54a7, form β-sheets rapidly. In contrast, the following five force fields, AMBER99-ILDN, AMBER14SB, CHARMM22*, CHARMM36, and CHARMM36m, are the best candidates for studying amyloid peptide assembly, as they provide good balances in terms of structures and kinetics. We also investigated the assembly mechanisms of dimeric Aβ16-22 and found that the fibril formation rate is predominantly controlled by the total β-strand content.

Thermodynamic phase diagram of amyloid-β (16-22) peptide

The aggregation of monomeric amyloid β protein (Aβ) peptide into oligomers and amyloid fibrils in the mammalian brain is associated with Alzheimer's disease. Insight into the thermodynamic stability of the Aβ peptide in different polymeric states is fundamental to defining and predicting the aggregation process. Experimental determination of Aβ thermodynamic behavior is challenging due to the transient nature of Aβ oligomers and the low peptide solubility. Furthermore, quantitative calculation of a thermodynamic phase diagram for a specific peptide requires extremely long computational times. Here, using a coarse-grained protein model, molecular dynamics (MD) simulations are performed to determine an equilibrium concentration and temperature phase diagram for the amyloidogenic peptide fragment Aβ_16-22 Our results reveal that the only thermodynamically stable phases are the solution phase and the macroscopic fibrillar phase, and that there also exists a hierarchy of metastable phases. The boundary line between the solution phase and fibril phase is found by calculating the temperature-dependent solubility of a macroscopic Aβ_16-22 fibril consisting of an infinite number of β-sheet layers. This in silico determination of an equilibrium (solubility) phase diagram for a real amyloid-forming peptide, Aβ_16-22, over the temperature range of 277-330 K agrees well with fibrillation experiments and transmission electron microscopy (TEM) measurements of the fibril morphologies formed. This in silico approach of predicting peptide solubility is also potentially useful for optimizing biopharmaceutical production and manufacturing nanofiber scaffolds for tissue engineering.

Effects of a Hydrophilic/Hydrophobic Interface on Amyloid-β Peptides Studied by Molecular Dynamics Simulations and NMR Experiments

Oligomer formation of amyloid-β peptides (Aβ) is accelerated at a hydrophilic/hydrophobic interface. However, details of the acceleration mechanism have not been elucidated. To understand the effects of the interface on oligomerization at the atomic level, we performed molecular dynamics simulations for an Aβ40 monomer in the presence and absence of the hydrophilic/hydrophobic interface. Nuclear magnetic resonance experiments of Aβ40 peptides with gangliosidic micelles were also carried out. In the simulations and experiments, the hydrophobic residues of Aβ40 bound to the interface stably. Moreover, we found that Aβ40 formed a hairpin structure at the interface more readily than in bulk water. From these results, we discussed the acceleration mechanism of the oligomer formation at the interface.

Mechanistic insight into E22Q-mutation-induced antiparallel-to-parallel β-sheet transition of Aβ16−22fibrils: an all-atom simulation study

E22Q mutation of Aβ₁₆₋₂₂fibrils facilitates parallel β-sheet formation by enhancing Q22–Q22 hydrogen-bonding interaction and A21–A21, F20–F20, F19–F19 and V18–V18 hydrophobic interaction.

Assemblies of amyloid-β30-36 hexamer and its G33V/L34T mutants by replica-exchange molecular dynamics simulation

The aggregation of amyloid-β peptides is associated with the pathogenesis of Alzheimer’s disease, in which the 30–36 fragments play an important part as a fiber-forming hydrophobic region. The fibrillar structure of Aβ_30–36 has been detected by means of X-ray diffraction, but its oligomeric structural determination, biophysical characterization, and pathological mechanism remain elusive. In this study, we have investigated the structures of Aβ_30–36 hexamer as well as its G33V and L34T mutants in explicit water environment using replica-exchange molecular dynamics (REMD) simulations. Our results show that the wild-type (WT) Aβ_30–36 hexamer has a preference to form β-barrel and bilayer β-sheet conformations, while the G33V or L34T mutation disrupts the β-barrel structures: the G33V mutant is homogenized to adopt β-sheet-rich bilayers, and the structures of L34T mutant on the contrary get more diverse. The hydrophobic interaction plays a critical role in the formation and stability of oligomeric assemblies among all the three systems. In addition, the substitution of G33 by V reduces the β-sheet content in the most populated conformations of Aβ_30–36 oligomers through a steric effect. The L34T mutation disturbs the interpeptide hydrogen bonding network, and results in the increased coil content and morphological diversity. Our REMD runs provide structural details of WT and G33V/L34T mutant Aβ_30–36 oligomers, and molecular insight into the aggregation mechanism, which will be helpful for designing novel inhibitors or amyloid-based materials.

How accurate are your simulations? Effects of confined aqueous volume and AMBER FF99SB and CHARMM22/CMAP force field parameters on structural ensembles of intrinsically disordered proteins: Amyloid-β42 in water

Amyloid-β₄₂ (Aβ₄₂) is an intrinsically disordered peptide intimately related to the pathogenesis of several neurodegenerative diseases. Molecular dynamics (MD) simulations are extensively utilized in the characterization of the structures and conformational dynamics of intrinsically disordered proteins (IDPs) including Aβ₄₂, with AMBER and CHARMM parameters being commonly used in these studies. Recently, comparison of the effects of force field parameters on the Aβ₄₂ structures has started to gain significant attention. In this study, the structures of Aβ₄₂ are simulated using AMBER FF99SB and CHARMM22/CMAP parameters via replica exchange MD simulations utilizing a widely used clustering algorithm. These analyses show that the structural properties (extent and positioning of the elements of secondary and tertiary structure), radius of gyration values, number and position of salt bridges are extremely dependent on the chosen force field parameters notably with the usage of clustering algorithms. For example, predicted secondary structure elements, which are of the great importance for better understanding of the molecular mechanisms of neurodegenerative diseases, deviate enormously in models generated using currently available force field parameters for proteins. Based on the derived models, chemical shift values are calculated and compared to the experimentally determined data. This comparison revealed that although both force field parameters yield results in agreement with experiments, the obtained structural properties were rather different using a clustering algorithm. In other words, these results show that the predicted structures depend heavily on the force field parameters. Importantly, since none of the force field parameters currently utilized in MD studies were developed specifically taking into account the disordered nature of IDPs, these findings clearly indicate that new force field parameters have to be developed for IDPs considering their rapid flexibility and dynamics with high amplitude. Furthermore, molecular simulations of IDPs are typically conducted using one water volume. We show that the confined aqueous volume impacts the predicted structural properties of Aβ₄₂ in water. Although up to date, confined aqueous volume effects have been ignored in the MD simulations of IDPs in water, our data indicate that these effects have to be taken into account in predicting the structural and thermodynamic properties of disordered proteins in solution.

Theoretical approaches for dynamical ordering of biomolecular systems

BACKGROUND

Living systems are characterized by the dynamic assembly and disassembly of biomolecules. The dynamical ordering mechanism of these biomolecules has been investigated both experimentally and theoretically. The main theoretical approaches include quantum mechanical (QM) calculation, all-atom (AA) modeling, and coarse-grained (CG) modeling. The selected approach depends on the size of the target system (which differs among electrons, atoms, molecules, and molecular assemblies). These hierarchal approaches can be combined with molecular dynamics (MD) simulation and/or integral equation theories for liquids, which cover all size hierarchies.

SCOPE OF REVIEW

We review the framework of quantum mechanical/molecular mechanical (QM/MM) calculations, AA MD simulations, CG modeling, and integral equation theories. Applications of these methods to the dynamical ordering of biomolecular systems are also exemplified.

MAJOR CONCLUSIONS

The QM/MM calculation enables the study of chemical reactions. The AA MD simulation, which omits the QM calculation, can follow longer time-scale phenomena. By reducing the number of degrees of freedom and the computational cost, CG modeling can follow much longer time-scale phenomena than AA modeling. Integral equation theories for liquids elucidate the liquid structure, for example, whether the liquid follows a radial distribution function.

GENERAL SIGNIFICANCE

These theoretical approaches can analyze the dynamic behaviors of biomolecular systems. They also provide useful tools for exploring the dynamic ordering systems of biomolecules, such as self-assembly. This article is part of a Special Issue entitled "Biophysical Exploration of Dynamical Ordering of Biomolecular Systems" edited by Dr. Koichi Kato.

Amyloid Beta Peptide Folding in Reverse Micelles

Previously published experimental studies have suggested that when the 40-residue amyloid beta peptide is encapsulated in a reverse micelle, it folds into a structure that may nucleate amyloid fibril formation (Yeung, P. S.-W.; Axelsen, P. H. J. Am. Chem. Soc. 2012, 134, 6061 ). The factors that induce the formation of this structure have now been identified in a multi-microsecond simulation of the same reverse micelle system that was studied experimentally. Key features of the polypeptide-micelle interaction include the anchoring of a hydrophobic residue cluster into gaps in the reverse micelle surface, the formation of a beta turn at the anchor point that brings N- and C-terminal segments of the polypeptide into proximity, high ionic strength that promotes intramolecular hydrogen bond formation, and deformation of the reverse micelle surface to facilitate interactions with the surface along the entire length of the polypeptide. Together, these features cause the simulation-derived vibrational spectrum to red shift in a manner that reproduces the red-shift previously reported experimentally. On the basis of these findings, a new mechanism is proposed whereby membranes nucleate fibril formation and facilitate the in-register alignment of polypeptide strands that is characteristic of amyloid fibrils.

Influence of Hyperglycemic Conditions on Self-Association of the Alzheimer's Amyloid β (Aβ1-42) Peptide

Clinical studies have identified a correlation between type-2 diabetes mellitus and cognitive decrements en route to the onset of Alzheimer's disease (AD). Recent studies have established that post-translational modifications of the amyloid β (Aβ) peptide occur under hyperglycemic conditions; particularly, the process of glycation exacerbates its neurotoxicity and accelerates AD progression. In view of the assertion that macromolecular crowding has an altering effect on protein self-assembly, it is crucial to characterize the effects of hyperglycemic conditions via crowding on Aβ self-assembly. Toward this purpose, fully atomistic molecular dynamics simulations were performed to study the effects of glucose crowding on Aβ dimerization, which is the smallest known neurotoxic species. The dimers formed in the glucose-crowded environment were found to have weaker associations as compared to that of those formed in water. Binding free energy calculations show that the reduced binding strength of the dimers can be mainly attributed to the overall weakening of the dispersion interactions correlated with substantial loss of interpeptide contacts in the hydrophobic patches of the Aβ units. Analysis to discern the differential solvation pattern in the glucose-crowded and pure water systems revealed that glucose molecules cluster around the protein, at a distance of 5-7 Å, which traps the water molecules in close association with the protein surface. This preferential exclusion of glucose molecules and resulting hydration of the Aβ peptides has a screening effect on the hydrophobic interactions, which in turn diminishes the binding strength of the resulting dimers. Our results imply that physical effects attributed to crowded hyperglycemic environments are incapable of solely promoting Aβ self-assembly, indicating that further mechanistic studies are required to provide insights into the self-assembly of post-translationally modified Aβ peptides, known to possess aggravated toxicity, under these conditions.

Alzheimer's Protective Cross-Interaction between Wild-Type and A2T Variants Alters Aβ42 Dimer Structure

Whole genome sequencing has recently revealed the protective effect of a single A2T mutation in heterozygous carriers against Alzheimer's disease (AD) and age-related cognitive decline. The impact of the protective cross-interaction between the wild-type (WT) and A2T variants on the dimer structure is therefore of high interest, as the Aβ dimers are the smallest known neurotoxic species. Toward this goal, extensive atomistic replica exchange molecular dynamics simulations of the solvated WT homo- and A2T hetero- Aβ_1-42 dimers have been performed, resulting into a total of 51 μs of sampling for each system. Weakening of a set of transient, intrachain contacts formed between the central and C-terminal hydrophobic residues is observed in the heterodimeric system. The majority of the heterodimers with reduced interaction between central and C-terminal regions lack any significant secondary structure and display a weak interchain interface. Interestingly, the A2T N-terminus, particularly residue F4, is frequently engaged in tertiary and quaternary interactions with central and C-terminal hydrophobic residues in those distinct structures, leading to hydrophobic burial. This atypical involvement of the N-terminus within A2T heterodimer revealed in our simulations implies possible interference on Aβ₄₂ aggregation and toxic oligomer formation, which is consistent with experiments. In conclusion, the present study provides detailed structural insights onto A2T Aβ₄₂ heterodimer, which might provide molecular insights onto the AD protective effect of the A2T mutation in the heterozygous state.

In silico investigation on the inhibition of Aβ42 aggregation by Aβ40 peptide by potential of mean force study

Recent experimental data revealed that small, soluble Amyloid beta (Aβ₄₂) oligomers, especially dimers impair synaptic plasticity and memory leading to Alzheimer's disease. Here, we have studied dimerization of Aβ₄₂/Aβ₄₂ homo-dimer and Aβ₄₀/Aβ₄₂ hetero-dimer in terms of free energy profile by all-atom simulations using the ff99SB force field. We have found that in the presence of Aβ₄₀ peptide, there exists a strong tendency to form a hetero-dimer with Aβ₄₂ peptide, suggesting that a possible co-oligomerization. Furthermore, we have investigated the effects of Aβ₄₀ on the Aβ₄₂ peptide. Our study also shows that in presence of Aβ₄₀, the beta-content of Aβ₄₂ monomer is reduced. Additionally, certain residues important for bending in Aβ₄₂ peptide attained an increased flexibility in the presence of Aβ₄₀. The salt-bridge destabilization also manifested the impact of Aβ₄₀ on Aβ₄₂ peptide as a whole. Based on this, one may expect that Aβ₄₀ inhibits the aggregation propensity of Aβ₄₂. Moreover, the binding free energy obtained by the molecular mechanics-Poisson-Boltzmann surface area method also revealed a strong affinity between the two isoforms thereby suggests that Aβ₄₀ binding induces conformational change in Aβ₄₂. Our results suggest that co-oligomerization of Aβ isoforms may play a substantial role in Alzheimer's disease.

Interplay between Intrinsic Conformational Propensities and Intermolecular Interactions in the Self-Assembly of Short Surfactant-like Peptides Composed of Leucine/Isoleucine

To study how the conformational propensities of individual amino acid residues, primary structures (i.e., adjacent residues and molecular lengths), and intermolecular interactions of peptides affect their self-assembly properties, we report the use of replica exchange molecular dynamics (REMD) to investigate the monomers, dimers, and trimers of a series of short surfactant-like peptides (I3K, L3K, L4K, and L5K). For four-residue peptides X3K (I3K and L3K), the results show that their different aggregation behaviors arise from the different intrinsic conformational propensities of isoleucine and leucine. For LmK peptides (L3K, L4K, and L5K), the molecular length is found to dictate their aggregation via primarily modulating intermolecular interactions. Increasing the number of hydrophobic amino acid residues of LmK peptides enhances their intermolecular H-bonding and promotes the formation of β-strands in dimer and trimer aggregates, overwhelming the intrinsic preference of Leu for helical structures. Thus, the interplay between the conformational propensities of individual amino acid residues for secondary structures and molecular interactions determines the self-assembly properties of the peptides, and the competition between intramolecular and intermolecular H-bonding interactions determines the probability of β-sheet alignment of peptide molecules. These results are validated by comparing simulated and experimental CD spectra of the peptides. This study will aid the design of short peptide amphiphiles and improve the mechanistic understanding of their self-assembly behavior.

The interaction with gold suppresses fiber-like conformations of the amyloid β (16-22) peptide

Inorganic surfaces and nanoparticles can accelerate or inhibit the fibrillation process of proteins and peptides, including the biomedically relevant amyloid β peptide. However, the microscopic mechanisms that determine such an effect are still poorly understood. By means of large-scale, state-of-the-art enhanced sampling molecular dynamics simulations, here we identify an interaction mechanism between the segments 16-22 of the amyloid β peptide, known to be fibrillogenic by itself, and the Au(111) surface in water that leads to the suppression of fiber-like conformations from the peptide conformational ensemble. Moreover, thanks to advanced simulation analysis techniques, we characterize the conformational selection vs. induced fit nature of the gold effect. Our results disclose an inhibition mechanism that is rooted in the details of the microscopic peptide-surface interaction rather than in general phenomena such as peptide sequestration from the solution.

Study on the inter- and intra-peptide salt-bridge mechanism of Aβ23-28 oligomer interaction with small molecules: QM/MM method

Amyloid β (Aβ) peptides have long been known to be a potential candidate for the onset of Alzheimer's disease (AD). The biophysical properties of Aβ42 peptide aggregates are of significant importance for the amyloid cascade mechanism of AD. It is necessary to design an inhibitor using small molecules to reduce the aggregation process in Aβ42 peptides. Attention has been given to use the natural products as anti-aggregation compounds, directly targeting Aβ peptides. Polyphenols have been extensively studied as a class of amyloid inhibitors. 9,10-Anthraquinone (AQ) is present in abundance in medicinal plants (rhubarb), the Trp-Pro-Tyr (TPT) peptide has been found in the venom of the black mamba snake, and the morin molecule is naturally present in wine and green tea; several other polyphenol derivatives are under clinical trials to develop anti-neurodegenerative drugs. In vitro and in vivo results strongly suggest that AQ and morin molecules are potential inhibitors of Aβ aggregation; however, the detailed understanding of the inhibition mechanism remains largely unknown. The formation of Aβ fibrils and oligomers requires a conformational change from α-helix to β-sheet, which occurs due to the formation of a salt-bridge between Asp(23) and Lys(28) residues. The present study focused on investigating the salt-bridge mechanism in the monomer, dimer and oligomer of the Aβ23-28 peptide during the interaction with TPT, morin and AQ molecules. Interaction energy and natural bond orbital analyses have been carried out using the ONIOM(M05-2X/6-31++G(d,p):UFF) method. The QM/MM studies have been performed to study the mechanism of salt-bridge formation during the inhibition process of amyloid β protein aggregation. The TPT molecule, which binds with the Asp(23) and Lys(28) residues of Aβ, prevents the salt-bridge formation between Asp(23) and Lys(28) residues and consequently the probability of the formation of Aβ fibrils is reduced.

The good, the bad and the user in soft matter simulations

Molecular dynamics (MD) simulations have become popular in materials science, biochemistry, biophysics and several other fields. Improvements in computational resources, in quality of force field parameters and algorithms have yielded significant improvements in performance and reliability. On the other hand, no method of research is error free. In this review, we discuss a few examples of errors and artifacts due to various sources and discuss how to avoid them. Besides bringing attention to artifacts and proper practices in simulations, we also aim to provide the reader with a starting point to explore these issues further. In particular, we hope that the discussion encourages researchers to check software, parameters, protocols and, most importantly, their own practices in order to minimize the possibility of errors. The focus here is on practical issues. This article is part of a Special Issue entitled: Biosimulations edited by Ilpo Vattulainen and Tomasz Róg.

Conformational features of the Aβ42 peptide monomer and its interaction with the surrounding solvent

Heterogeneous conformational flexibility of the Aβ monomers has been found to be correlated with the corresponding non-uniform entropy gains.

Scaling of Multimillion-Atom Biological Molecular Dynamics Simulation on a Petascale Supercomputer

A strategy is described for a fast all-atom molecular dynamics simulation of multimillion-atom biological systems on massively parallel supercomputers. The strategy is developed using benchmark systems of particular interest to bioenergy research, comprising models of cellulose and lignocellulosic biomass in an aqueous solution. The approach involves using the reaction field (RF) method for the computation of long-range electrostatic interactions, which permits efficient scaling on many thousands of cores. Although the range of applicability of the RF method for biomolecular systems remains to be demonstrated, for the benchmark systems the use of the RF produces molecular dipole moments, Kirkwood G factors, other structural properties, and mean-square fluctuations in excellent agreement with those obtained with the commonly used Particle Mesh Ewald method. With RF, three million- and five million-atom biological systems scale well up to ∼30k cores, producing ∼30 ns/day. Atomistic simulations of very large systems for time scales approaching the microsecond would, therefore, appear now to be within reach.

Alzheimer's protective A2T mutation changes the conformational landscape of the Aβ₁₋₄₂ monomer differently than does the A2V mutation

The aggregation of amyloid-β (Aβ) peptides plays a crucial role in the etiology of Alzheimer's disease (AD). Recently, it has been reported that an A2T mutation in Aβ can protect against AD. Interestingly, a nonpolar A2V mutation also has been found to offer protection against AD in the heterozygous state, although it causes early-onset AD in homozygous carriers. Since the conformational landscape of the Aβ monomer is known to directly contribute to the early-stage aggregation mechanism, it is important to characterize the effects of the A2T and A2V mutations on Aβ₁₋₄₂ monomer structure. Here, we have performed extensive atomistic replica-exchange molecular dynamics simulations of the solvated wild-type (WT), A2V, and A2T Aβ₁₋₄₂ monomers. Our simulations reveal that although all three variants remain as collapsed coils in solution, there exist significant structural differences among them at shorter timescales. A2V exhibits an enhanced double-hairpin population in comparison to the WT, similar to those reported in toxic WT Aβ₁₋₄₂ oligomers. Such double-hairpin formation is caused by hydrophobic clustering between the N-terminus and the central and C-terminal hydrophobic patches. In contrast, the A2T mutation causes the N-terminus to engage in unusual electrostatic interactions with distant residues, such as K16 and E22, resulting in a unique population comprising only the C-terminal hairpin. These findings imply that a single A2X (where X = V or T) mutation in the primarily disordered N-terminus of the Aβ₁₋₄₂ monomer can dramatically alter the β-hairpin population and switch the equilibrium toward alternative structures. The atomistically detailed, comparative view of the structural landscapes of A2V and A2T variant monomers obtained in this study can enhance our understanding of the mechanistic differences in their early-stage aggregation.

Exploring the role of hydration and confinement in the aggregation of amyloidogenic peptides Aβ(16-22) and Sup35(7-13) in AOT reverse micelles

Knowledge of how intermolecular interactions of amyloid-forming proteins cause protein aggregation and how those interactions are affected by sequence and solution conditions is essential to our understanding of the onset of many degenerative diseases. Of particular interest is the aggregation of the amyloid-β (Aβ) peptide, linked to Alzheimer's disease, and the aggregation of the Sup35 yeast prion peptide, which resembles the mammalian prion protein linked to spongiform encephalopathies. To facilitate the study of these important peptides, experimentalists have identified small peptide congeners of the full-length proteins that exhibit amyloidogenic behavior, including the KLVFFAE sub-sequence, Aβ16-22, and the GNNQQNY subsequence, Sup357-13. In this study, molecular dynamics simulations were used to examine these peptide fragments encapsulated in reverse micelles (RMs) in order to identify the fundamental principles that govern how sequence and solution environment influence peptide aggregation. Aβ16-22 and Sup357-13 are observed to organize into anti-parallel and parallel β-sheet arrangements. Confinement in the sodium bis(2-ethylhexyl) sulfosuccinate (AOT) reverse micelles is shown to stabilize extended peptide conformations and enhance peptide aggregation. Substantial fluctuations in the reverse micelle shape are observed, in agreement with earlier studies. Shape fluctuations are found to facilitate peptide solvation through interactions between the peptide and AOT surfactant, including direct interaction between non-polar peptide residues and the aliphatic surfactant tails. Computed amide I IR spectra are compared with experimental spectra and found to reflect changes in the peptide structures induced by confinement in the RM environment. Furthermore, examination of the rotational anisotropy decay of water in the RM demonstrates that the water dynamics are sensitive to the presence of peptide as well as the peptide sequence. Overall, our results demonstrate that the RM is a complex confining environment where substantial direct interaction between the surfactant and peptides plays an important role in determining the resulting ensemble of peptide conformations. By extension the results suggest that similarly complex sequence-dependent interactions may determine conformational ensembles of amyloid-forming peptides in a cellular environment.

Coupling of Zinc-Binding and Secondary Structure in Nonfibrillar Aβ40 Peptide Oligomerization

Nonfibrillar neurotoxic amyloid β (Aβ) oligomer structures are typically rich in β-sheets, which could be promoted by metal ions like Zn(2+). Here, using molecular dynamics (MD) simulations, we systematically examined combinations of Aβ40 peptide conformations and Zn(2+) binding modes to probe the effects of secondary structure on Aβ dimerization energies and kinetics. We found that random conformations do not contribute to dimerization either thermodynamically or kinetically. Zn(2+) couples with preformed secondary structures (α-helix and β-hairpin) to speed dimerization and stabilize the resulting dimer. Partial α-helices increase the dimerization speed, and dimers with α-helix rich conformations have the lowest energy. When Zn(2+) coordinates with residues D1, H6, H13, and H14, Aβ40 β-hairpin monomers have the fastest dimerization speed. Dimers with experimentally observed zinc coordination (E11, H6, H13, and H14) form with slower rate but have lower energy. Zn(2+) cannot stabilize fibril-like β-arch dimers. However, Zn(2+)-bound β-arch tetramers have the lowest energy. Collectively, zinc-stabilized β-hairpin oligomers could be important in the nucleation-polymerization of cross-β structures. Our results are consistent with experimental findings that α-helix to β-structural transition should accompany Aβ aggregation in the presence of zinc ions and that Zn(2+) stabilizes nonfibrillar Aβ oligomers and, thus, inhibits formation of less toxic Aβ fibrils.

Aβ self-association and adsorption on a hydrophobic nanosurface: competitive effects and the detection of small oligomers via electrical response

Treatment of Alzheimer's disease (AD) is impeded by the lack of effective early diagnostic methods. Small, soluble Aβ globulomers play a major role in AD neurotoxicity, and detecting their presence in aqueous fluids could lead to suitable sensors. We evaluate the adsorption behavior of small Aβ oligomers on the surface of a single walled carbon nanotube of high curvature. While the intrinsic self-assembly propensity of Aβ is markedly hindered by adsorption, the oligomeric units show high degrees of surface immobilization. Immobilized complexes are capable of oligomeric growth, but with a shifted monomer-oligomer equilibrium compared to the free states. In the presence of an ionic solution and suitable external electric fields, magnitudes of the current blockades are found to be sensitive to the oligomeric number of the adsorbed complex. However, this sensitivity gradually diminishes with increasing oligomeric size. The results provide a proof-of-concept basis for further investigations in the design of sensors for detecting the toxic small oligomers of Aβ.

Interaction of amyloid inhibitor proteins with amyloid beta peptides: insight from molecular dynamics simulations

Knowledge of the detailed mechanism by which proteins such as human αB- crystallin and human lysozyme inhibit amyloid beta (Aβ) peptide aggregation is crucial for designing treatment for Alzheimer's disease. Thus, unconstrained, atomistic molecular dynamics simulations in explicit solvent have been performed to characterize the Aβ_17–42 assembly in presence of the αB-crystallin core domain and of lysozyme. Simulations reveal that both inhibitor proteins compete with inter-peptide interaction by binding to the peptides during the early stage of aggregation, which is consistent with their inhibitory action reported in experiments. However, the Aβ binding dynamics appear different for each inhibitor. The binding between crystallin and the peptide monomer, dominated by electrostatics, is relatively weak and transient due to the heterogeneous amino acid distribution of the inhibitor surface. The crystallin-bound Aβ oligomers are relatively long-lived, as they form more extensive contact surface with the inhibitor protein. In contrast, a high local density of arginines from lysozyme allows strong binding with Aβ peptide monomers, resulting in stable complexes. Our findings not only illustrate, in atomic detail, how the amyloid inhibitory mechanism of human αB-crystallin, a natural chaperone, is different from that of human lysozyme, but also may aid de novo design of amyloid inhibitors.

Effects of hydroxylated carbon nanotubes on the aggregation of Aβ16-22 peptides: a combined simulation and experimental study

The pathogenesis of Alzheimer's disease (AD) is associated with the aggregation of amyloid-β (Aβ) peptides into toxic aggregates with ?-sheet character. In a previous computational study, we showed that pristine single-walled carbon nanotubes (SWCNTs) can inhibit the formation of β-sheet-rich oligomers in the central hydrophobic core fragment of Aβ (Aβ16-22). However, the poor solubility of SWCNTs in water hinders their use in biomedical applications and nanomedicine. Here, we investigate the influence of hydroxylated SWCNT, a water-soluble SWCNT derivative, on the aggregation of Aβ16-22 peptides using all-atom explicit-water replica exchange molecular dynamics simulations. Our results show that hydroxylated SWCNTs can significantly inhibit β-sheet formation and shift the conformations of Aβ16-22 oligomers from ordered β-sheet-rich structures toward disordered coil aggregates. Detailed analyses of the SWCNT-Aβ interaction reveal that the inhibition of β-sheet formation by hydroxylated SWCNTs mainly results from strong electrostatic interactions between the hydroxyl groups of SWCNTs and the positively charged residue K16 of Aβ16-22 and hydrophobic and aromatic stacking interactions between SWCNTs and F19 and F20. In addition, our atomic force microscopy and thioflavin T fluorescence experiments confirm the inhibitory effect of both pristine and hydroxylated SWCNTs on Aβ16-22 fibrillization, in support of our previous and present replica exchange molecular dynamics simulation results. These results demonstrate that hydroxylated SWCNTs efficiently inhibit the aggregation of Aβ16-22; in addition, they offer molecular insight into the inhibition mechanism, thus providing new clues for the design of therapeutic drugs against amyloidosis.

Structural diversity of Alzheimer's disease amyloid-β dimers and their role in oligomerization and fibril formation

Alzheimer's disease (AD) is associated with the formation of toxic amyloid-β (Aβ)42 oligomers, and recent evidence supports a role for Aβ dimers as building blocks for oligomers. Molecular dynamics simulation studies have identified clans for the dominant conformations of Aβ42 forming dimers; however, it is unclear if a larger spectrum of dimers is involved and which set(s) of dimers might evolve to oligomers verse fibrils. Therefore, for this study we generated multiple structural conformations of Aβ42, using explicit all-atom molecular dynamics, and then clustering the different structures based on key conformational similarities. Those matching a selection threshold were then used to model a process of oligomerization. Remarkably, we showed a greater diversity in Aβ dimers than previously described. Depending on the clan family, different types of Aβ dimers were obtained. While some had the tendency to evolve into oligomeric rings, others formed fibrils of diverse characteristics. Then we selected the dimers that would evolve to membranephilic annular oligomers. Nearly one third of the 28 evaluated annular oligomers had the dimer interfaces between the neighboring Aβ42 monomers with possible salt bridges between the residue K28 from one side and either residue E22 or D23 on the other. Based on these results, key amino acids were identified for point mutations that either enhanced or suppressed the formation and toxicity of oligomer rings. Our studies suggest a greater diversity of Aβ dimers. Understanding the structure of Aβ dimers might be important for the rationale design of small molecules that block formation of toxic oligomers.

Dimerization process of amyloid-β(29-42) studied by the Hamiltonian replica-permutation molecular dynamics simulations

The amyloid-β peptides form amyloid fibrils which are associated with Alzheimer's disease. Amyloid-β(29-42) is its C-terminal fragment and a critical determinant of the amyloid formation rate. This fragment forms the amyloid fibril by itself. However, the fragment conformation in the fibril has yet to be determined. The oligomerization process including the dimerization process is also still unknown. The dimerization process corresponds to an early process of the amyloidogenesis. In order to investigate the dimerization process and conformations, we applied the Hamiltonian replica-permutation method, which is a better alternative to the Hamiltonian replica-exchange method, to two amyloid-β(29-42) molecules in explicit water solvent. At the first step of the dimerization process, two amyloid-β(29-42) molecules came close to each other and had intermolecular side chain contacts. When two molecules had the intermolecular side chain contacts, the amyloid-β(29-42) tended to have intramolecular secondary structures, especially β-hairpin structures. The two molecules had intermolecular β-bridge structures by coming much closer at the second step of the dimerization process. Formation of these intermolecular β-bridge structures was induced by the β-hairpin structures. The intermolecular β-sheet structures elongated at the final step. Structures of the amyloid-β(29-42) in the monomer and dimer states are also shown with the free-energy landscapes, which were obtained by performing efficient sampling in the conformational space in our simulations.

The conformational stability of nonfibrillar amyloid-β peptide oligomers critically depends on the C-terminal peptide length

The amyloid-β (Aβ) peptide is one key molecule in the pathogenesis of Alzheimer's disease. We investigated the conformational stability of a nonfibrillar tetrameric Aβ structure by molecular dynamics (MD) simulations revealing that the stability of the Aβ tetramer depends critically on the C-terminal length. In contrast to the Aβ17-40 tetramer, which proved to be instable, the simulations demonstrate structural integrity of the Aβ17-42 and Aβ17-43 tetramers. These differences in stability can be attributed to an extension of the middle strand of a three-stranded antiparallel β sheet through residues 41-43, only present in the longer Aβ species that aggregate faster and are more neurotoxic. Additional MD simulations demonstrate that this higher stability is also present in the monomers forming the tetramer. In conclusion, our findings suggest the existence of a nonfibrillar oligomer topology that is significantly more stable for the longer Aβ species, thus offering a structural explanation for their higher neurotoxicity.

Conformational distribution and α-helix to β-sheet transition of human amylin fragment dimer

Experiments suggested that the fibrillation of the 11-25 fragment (hIAPP(11-25)) of human islet amyloid polypeptide (hIAPP or amylin) involves the formation of transient α-helical intermediates, followed by conversion to β-sheet-rich structure. However, atomic details of α-helical intermediates and the transition mechanism are mostly unknown. We investigated the structural properties of the monomer and dimer in atomistic detail by replica exchange molecular dynamics (REMD) simulations. Transient α-helical monomers and dimers were both observed in the REMD trajectories. Our calculated H(α) chemical shifts based on the monomer REMD run are in agreement with the solution-state NMR experimental observations. Multiple 300 ns MD simulations at 310 K show that α-helix-to-β-sheet transition follows two mechanisms: the first involved direct transition of the random coil part of the helical conformation into antiparallel β-sheet, and in the second, the α-helical conformation unfolded and converted into antiparallel β-sheet. In both mechanisms, the α-helix-to-β-sheet transition occurred via random coil, and the transition was accompanied by an increase of interpeptide contacts. In addition, our REMD simulations revealed different temperature dependencies of helical and β-structures. Comparison with experimental data suggests that the propensity for hIAPP(11-25) to form α-helices and amyloid structures is concentration- and temperature-dependent.

Aβ(16-22) peptides can assemble into ordered β-barrels and bilayer β-sheets, while substitution of phenylalanine 19 by tryptophan increases the population of disordered aggregates

A recent experimental study reported that termini-uncapped Aβ(16-22) (with sequence KLVFFAE) peptides self-assembled into nanofibrils at pH 2.0. The oligomerization of this uncapped peptide at atomic level in acidic pH condition remains to be determined, as computational studies mainly focus on the self-assembly of capped Aβ(16-22) peptides at neutral pH condition. In this study, using replica exchange molecular dynamics (REMD) simulations with explicit solvent, we investigated the octameric structures of the uncapped Aβ(16-22) and its F19W variant at acidic pH condition. Our simulations reveal that the Aβ(16-22) octamers adopt various conformations, including closed β-barrels, bilayer β-sheets, and disordered aggregates. The closed β-barrel conformation is particularly interesting, as the cylindrical β-barrel has been reported recently as a cytotoxic species. Interpeptide contact probability analyses between all pairs of residues reveal that the hydrophobic and aromatic stacking interactions between F19 residues play an essential role in the formation of β-barrels and bilayer β-sheets. The importance of F19 and the steric effect on the structures of Aβ(16-22) octamers are further examined by REMD simulation of F19W mutant. This REMD run shows that substitution of F19 by W with a more bulky aromatic side chain significantly reduces the β-sheet content and in turn enhances the population of disordered aggregates, indicating that the steric effect significantly affect the self-assembly of low molecular weight Aβ(16-22) oligomers.