Structure and Physicochemical Properties of the Aβ42 Tetramer: Multiscale Molecular Dynamics Simulations

A Practical Guide to All-Atom and Coarse-Grained Molecular Dynamics Simulations Using Amber and Gromacs: A Case Study of Disulfide-Bond Impact on the Intrinsically Disordered Amyloid Beta

Intrinsically disordered proteins (IDPs) pose challenges to conventional experimental techniques due to their large-scale conformational fluctuations and transient structural elements. This work presents computational methods for studying IDPs at various resolutions using the Amber and Gromacs packages with both all-atom (Amber ff19SB with the OPC water model) and coarse-grained (Martini 3 and SIRAH) approaches. The effectiveness of these methodologies is demonstrated by examining the monomeric form of amyloid-β (Aβ42), an IDP, with and without disulfide bonds at different resolutions. Our results clearly show that the addition of a disulfide bond decreases the β-content of Aβ42; however, it increases the tendency of the monomeric Aβ42 to form fibril-like conformations, explaining the various aggregation rates observed in experiments. Moreover, analysis of the monomeric Aβ42 compactness, secondary structure content, and comparison between calculated and experimental chemical shifts demonstrates that all three methods provide a reasonable choice to study IDPs; however, coarse-grained approaches may lack some atomistic details, such as secondary structure recognition, due to the simplifications used. In general, this study not only explains the role of disulfide bonds in Aβ42 but also provides a step-by-step protocol for setting up, conducting, and analyzing molecular dynamics (MD) simulations, which is adaptable for studying other biomacromolecules, including folded and disordered proteins and peptides.

Integrating Explicit and Implicit Fullerene Models into UNRES Force Field for Protein Interaction Studies

Fullerenes, particularly C60, exhibit unique properties that make them promising candidates for various applications, including drug delivery and nanomedicine. However, their interactions with biomolecules, especially proteins, remain not fully understood. This study implements both explicit and implicit C60 models into the UNRES coarse-grained force field, enabling the investigation of fullerene-protein interactions without the need for restraints to stabilize protein structures. The UNRES force field offers computational efficiency, allowing for longer timescale simulations while maintaining accuracy. Five model proteins were studied: FK506 binding protein, HIV-1 protease, intestinal fatty acid binding protein, PCB-binding protein, and hen egg-white lysozyme. Molecular dynamics simulations were performed with and without C60 to assess protein stability and investigate the impact of fullerene interactions. Analysis of contact probabilities reveals distinct interaction patterns for each protein. FK506 binding protein (1FKF) shows specific binding sites, while intestinal fatty acid binding protein (1ICN) and uteroglobin (1UTR) exhibit more generalized interactions. The explicit C60 model shows good agreement with all-atom simulations in predicting protein flexibility, the position of C60 in the binding pocket, and the estimation of effective binding energies. The integration of explicit and implicit C60 models into the UNRES force field, coupled with recent advances in coarse-grained modeling and multiscale approaches, provides a powerful framework for investigating protein-nanoparticle interactions at biologically relevant scales without the need to use restraints stabilizing the protein, thus allowing for large conformational changes to occur. These computational tools, in synergy with experimental techniques, can aid in understanding the mechanisms and consequences of nanoparticle-biomolecule interactions, guiding the design of nanomaterials for biomedical applications.

Edge Substitution Effects of Histidine Tautomerization Behaviors on the Structural Properties and Aggregation Properties of Aβ(1-42) Mature Fibril

Histidine behaviors play critical roles in folding and misfolding processes due to the changes in net charge and the various N/N-H orientations on imidazole rings. However, the effect of histidine tautomerization (HIE (Nε-H, ε) and HID (Nδ-H, δ) states) behaviors on the edge chain of Aβ mature fibrils remains inadequately understood, which is critical for finding a strategy to disturb fibril elongation and growth. In the current study, eight independent molecular dynamics simulations were conducted to investigate such impacts on the structural and aggregation properties. Our results from three different binding models revealed that the binding contributions of edge substitution effects are primarily located between chains 1 and 2. Histidine states significantly influence the secondary structure of each domain. Further analysis confirmed that the C1_H6//C1_E11 intrachain interaction is essential in maintaining the internal stability of chain 1, while the C1_H13//C2_H13 and C1_H14//C2_H13 interchain interactions are critical in maintaining the interchain stability of the fibril structure. Our subsequent analysis revealed that the current edge substitution leads to the loss of the C1_H13//C1_E11 intrachain and C1_H13//C2_H14 interchain interactions. The N-terminal regularity was significantly directly influenced by histidine states, particularly by the residue of C1_H13. Our study provides valuable insights into the effect of histidine behaviors on the edge chain of Aβ mature fibril, advancing our understanding of the histidine behavior hypothesis in misfolding diseases.

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.

Martini on the Rocks: Can a Coarse-Grained Force Field Model Crystals?

Computational chemistry is an important tool in numerous scientific disciplines, including drug discovery and structural biology. Coarse-grained models offer simple representations of molecular systems that enable simulations of large-scale systems. Because there has been an increase in the adoption of such models for simulations of biomolecular systems, critical evaluation is warranted. Here, the stability of the amyloid peptide and organic crystals is evaluated using the Martini 3 coarse-grained force field. The crystals change shape drastically during the simulations. Radial distribution functions show that the distance between backbone beads in β-sheets increases by ∼1 Å, breaking the crystals. The melting points of organic compounds are much too low in the Martini force field. This suggests that Martini 3 lacks the specific interactions needed to accurately simulate peptides or organic crystals without imposing artificial restraints. The problems may be exacerbated by the use of the 12-6 potential, suggesting that a softer potential could improve this model for crystal simulations.

Stability of the Aβ42 Peptide in Mixed Solutions of Denaturants and Proline

Amyloid β-peptide (Aβ) is responsible for the neuronal damage and death of a patient with Alzheimer's disease (AD). Aβ42 oligomeric forms are dominant neurotoxins and are related to neurodegeneration. Their different forms are related to various pathological conditions in the brain. We investigated Aβ42 peptides in different environments of proline, urea, and GdmCl solutions (in pure and mixed binary forms) through atomistic molecular dynamics simulations. Preferential exclusion from the protein surface and facile formation of a large number of weak molecular interactions are the driving forces for the osmolyte's action. We have focused on these interactions between peptide monomers and pure/mixed osmolytes and denaturants. Urea, as usual, denatures the peptide strongly compared to the GdmCl by accumulation around the peptide. GdmCl shows lesser build-up around protein in contrast to urea but is involved in destabilizing the salt bridge formation of Asp23 and Lys28. Proline as an osmolyte protects the peptide from aggregation when mixed with urea and GdmCl solutions. In mixed solutions of two denaturants and osmolyte plus denaturant, the peptide shows enhanced stability as compared to pure denaturant urea solution. The enhanced stability of peptides in proline may be attributed to its exclusion from the peptide surface and favoring salt bridge 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.

Ambient Benzo[a]pyrene's Effect on Kinetic Modulation of Amyloid Beta Peptide Aggregation: A Tentative Association between Ultrafine Particulate Matter and Alzheimer's Disease

Long-time exposure to ambient ultrafine particles is associated with an increased risk of neurodegenerative diseases such as Alzheimer's disease (AD), which is triggered by the aggregation of Aβ peptide monomers into toxic oligomers. Among different ultrafine air pollutants, polycyclic aromatic hydrocarbons (PAHs) are known to have a negative neural impact; however, the impact mechanism remains obscure. We herein examined the effect of Benzo[a]Pyrene (B[a]P), one of the typical PAHs on Aβ₄₂ oligomerization using all-atom molecular dynamics simulations. In particular, the simulations were performed using four molecules of Aβ₄₂ in the presence of 5.00 mM, 12.5 mM, and 50.0 mM of B[a]P. The results revealed strong hydrophobic interactions between Aβ₄₂ peptides and B[a]P, which in turn resulted in increased interpeptide electrostatic interactions. Furthermore, 5.00 mM of B[a]P accelerated the kinetics of the formation of peptide tetramer by 30%, and stabilized C-terminus in Aβ₄₂ peptides, suggesting consequent progression of AD in the presence of 5.00 mM B[a]P. In contrast, 12.5 mM and 50.0 mM of B[a]P decreased interpeptide interactions and H-bonding due to the aggregation of numerous B[a]P clusters with the peptides, suppressing oligomerization kinetics of Aβ₄₂ peptides by 13% and 167%, respectively. While the study elucidates the effect of small environmental hydrophobic molecules on the formation of Aβ oligomers, the impact of ambient ultrafine particles on AD in the complex composition of the environmental realm requires further systematic delving into the field.

Early Stages of RNA-Mediated Conversion of Human Prions

Prion diseases are characterized by the conversion of prion proteins from a PrPC fold into a disease-causing PrPSC form that is self-replicating. A possible agent to trigger this conversion is polyadenosine RNA, but both mechanism and pathways of the conversion are poorly understood. Using coarse-grained molecular dynamic simulations we study the time evolution of PrPC over 600 μs. We find that both the D178N mutation and interacting with polyadenosine RNA reduce the helicity of the protein and encourage formation of segments with strand-like motifs. We conjecture that these transient β-strands nucleate the conversion of the protein to the scrapie conformation PrPSC.

Amyloid β Dodecamer Disrupts the Neuronal Membrane More Strongly than the Mature Fibril: Understanding the Role of Oligomers in Neurotoxicity

The amyloid cascade hypothesis states that senile plaques, composed of amyloid β (Aβ) fibrils, play a key role in Alzheimer’s disease (AD). However, recent experiments have shown that Aβ oligomers are more toxic to neurons than highly ordered fibrils. The molecular mechanism underlying this observation remains largely unknown. One of the possible scenarios for neurotoxicity is that Aβ peptides create pores in the lipid membrane that allow Ca²⁺ ions to enter cells, resulting in a signal of cell apoptosis. Hence, one might think that oligomers are more toxic due to their higher ability to create ion channels than fibrils. In this work, we study the effect of Aβ42 dodecamer and fibrils on a neuronal membrane, which is similar to that observed in AD patients, using all-atom molecular dynamics simulations. Due to short simulation times, we cannot observe the formation of pores, but useful insight on the early events of this process has been obtained. Namely, we showed that dodecamer distorts the lipid membrane to a greater extent than fibrils, which may indicate that ion channels can be more easily formed in the presence of oligomers. Based on this result, we anticipate that oligomers are more toxic than mature fibrils, as observed experimentally. Moreover, the Aβ–membrane interaction was found to be governed by the repulsive electrostatic interaction between Aβ and the ganglioside GM1 lipid. We calculated the bending and compressibility modulus of the membrane in the absence of Aβ and obtained good agreement with the experiment. We predict that the dodecamer will increase the compressibility modulus but has little effect on the bending modulus. Due to the weak interaction with the membrane, fibrils insignificantly change the membrane elastic properties.

Early aggregation mechanism of Aβ16-22 revealed by Markov state models

Aβ_16-22 is believed to have critical role in early aggregation of full length amyloids that are associated with the Alzheimer's disease and can aggregate to form amyloid fibrils. However, the early aggregation mechanism is still unsolved. Here, multiple long-term molecular dynamics simulations combining with Markov state model were used to probe the early oligomerization mechanism of Aβ_16-22 peptides. The identified dimeric form adopted either globular random-coil or extended β-strand like conformations. The observed dimers of these variants shared many overall conformational characteristics but differed in several aspects at detailed level. In all cases, the most common type of secondary structure was intermolecular antiparallel β-sheets. The inter-state transitions were very frequent ranges from few to hundred nanoseconds. More strikingly, those states which contain fraction of β secondary structure and significant amount of extended coiled structures, therefore exposed to the solvent, were majorly participated in aggregation. The assembly of low-energy dimers, in which the peptides form antiparallel β sheets, occurred by multiple pathways with the formation of an obligatory intermediates. We proposed that these states might facilitate the Aβ_16-22 aggregation through a significant component of the conformational selection mechanism, because they might increase the aggregates population by promoting the inter-chain hydrophobic and the hydrogen bond contacts. The formation of early stage antiparallel β sheet structures is critical for oligomerization, and at the same time provided a flat geometry to seed the ordered β-strand packing of the fibrils. Our findings hint at reorganization of this part of the molecule as a potentially critical step in Aβ aggregation and will insight into early oligomerization for large β amyloids.

Computational Models for the Study of Protein Aggregation

Protein aggregation has been studied by many groups around the world for many years because it can be the cause of a number of neurodegenerative diseases that have no effective treatment. Obtaining the structure of related fibrils and toxic oligomers, as well as describing the pathways and main factors that govern the self-organization process, is of paramount importance, but it is also very difficult. To solve this problem, experimental and computational methods are often combined to get the most out of each method. The effectiveness of the computational approach largely depends on the construction of a reasonable molecular model. Here we discussed different versions of the four most popular all-atom force fields AMBER, CHARMM, GROMOS, and OPLS, which have been developed for folded and intrinsically disordered proteins, or both. Continuous and discrete coarse-grained models, which were mainly used to study the kinetics of aggregation, are also summarized.

Computer Simulations Aimed at Exploring Protein Aggregation and Dissociation

Protein aggregation can lead to well-defined structures that are functional, but is also the cause of the death of neuron cells in many neurodegenerative diseases. The complexity of the molecular events involved in the aggregation kinetics of amyloid proteins and the transient and heterogeneous characters of all oligomers prevent high-resolution structural experiments. As a result, computer simulations have been used to determine the atomic structures of amyloid proteins at different association stages as well as to understand fibril dissociation. In this chapter, we first review the current computer simulation methods used for aggregation with some atomistic and coarse-grained results aimed at better characterizing the early formed oligomers and amyloid fibril formation. Then we present the applications of non-equilibrium molecular dynamics simulations to comprehend the dissociation of protein assemblies.

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

Amyloid beta (Aβ) oligomers are the most neurotoxic aggregates causing neuronal death and cognitive damage. A detailed elucidation of the aggregation pathways from oligomers to fibril formation is crucial to develop therapeutic strategies for Alzheimer's disease (AD). Although experimental techniques rely on the measure of time- and space-average properties, they face severe difficulties in the investigation of Aβ peptide aggregation due to their intrinsically disorder character. Computer simulation is a tool that allows tracing the molecular motion of molecules; hence it complements Aβ experiments, as it allows to explore the binding mechanism between metal ions and Aβ oligomers close to the cellular membrane at the atomic resolution. In this context, integrated studies of experiments and computer simulations can assist in mapping the complete pathways of aggregation and toxicity of Aβ peptides. Aβ oligomers are disordered proteins, and due to a rapid exploration of their intrinsic conformational space in real-time, they are challenging therapeutic targets. Therefore, no good drug candidate could have been identified for clinical use. Our previous investigations identified two small molecules, M30 (2-Octahydroisoquinolin-2(1H)-ylethanamine) and Gabapentin, capable of Aβ binding and inhibiting molecular aggregation, synaptotoxicity, intracellular calcium signaling, cellular toxicity and memory losses induced by Aβ. Thus, we recommend these molecules as novel candidates to assist anti-AD drug discovery in the near future. This review discusses the most recent research investigations about the Aβ dynamics in water, close contact with cell membranes, and several therapeutic strategies to remove plaque formation.

Theory and Practice of Coarse-Grained Molecular Dynamics of Biologically Important Systems

Molecular dynamics with coarse-grained models is nowadays extensively used to simulate biomolecular systems at large time and size scales, compared to those accessible to all-atom molecular dynamics. In this review article, we describe the physical basis of coarse-grained molecular dynamics, the coarse-grained force fields, the equations of motion and the respective numerical integration algorithms, and selected practical applications of coarse-grained molecular dynamics. We demonstrate that the motion of coarse-grained sites is governed by the potential of mean force and the friction and stochastic forces, resulting from integrating out the secondary degrees of freedom. Consequently, Langevin dynamics is a natural means of describing the motion of a system at the coarse-grained level and the potential of mean force is the physical basis of the coarse-grained force fields. Moreover, the choice of coarse-grained variables and the fact that coarse-grained sites often do not have spherical symmetry implies a non-diagonal inertia tensor. We describe selected coarse-grained models used in molecular dynamics simulations, including the most popular MARTINI model developed by Marrink's group and the UNICORN model of biological macromolecules developed in our laboratory. We conclude by discussing examples of the application of coarse-grained molecular dynamics to study biologically important processes.

Nanomechanical Stability of Aβ Tetramers and Fibril-like Structures: Molecular Dynamics Simulations

Alzheimer's disease (AD) is a neurodegenerative disorder and one of the main causes of dementia. The disease is associated with amyloid beta (Aβ) peptide aggregation forming initial clusters and then fibril structure and plaques. Other neurodegenerative diseases such as type 2 diabetes, amyotrophic lateral sclerosis, and Parkinson's disease follow a similar mechanism. Therefore, inhibition of Aβ aggregation is considered an effective way to prevent AD. Recent experiments have provided evidence that oligomers are more toxic agents than mature fibrils, prompting researchers to investigate various factors that may influence their properties. One of these factors is nanomechanical stability, which plays an important role in the self-assembly of Aβ and possibly other proteins. This stability is also likely to be related to cell toxicity. In this work, we compare the mechanical stability of Aβ-tetramers and fibrillar structures using a structure-based coarse-grained (CG) approach and all-atom molecular dynamics simulation. Our results support the evidence for an increase in mechanical stability during the Aβ fibrillization process, which is consistent with in vitro AFM characterization of Aβ42 oligomers. Namely, using a CG model, we showed that the Young modulus of tetramers is lower than that of fibrils and, as follows from the experiment, is about 1 GPa. Hydrogen bonds are the dominant contribution to the detachment of one chain from the Aβ fibril fragment. They tend to be more organized along the pulling direction, whereas in the Aβ tetramers no preference is observed.

Structural Studies Providing Insights into Production and Conformational Behavior of Amyloid-β Peptide Associated with Alzheimer's Disease Development

Alzheimer's disease is the most common type of neurodegenerative disease in the world. Genetic evidence strongly suggests that aberrant generation, aggregation, and/or clearance of neurotoxic amyloid-β peptides (Aβ) triggers the disease. Aβ accumulates at the points of contact of neurons in ordered cords and fibrils, forming the so-called senile plaques. Aβ isoforms of different lengths are found in healthy human brains regardless of age and appear to play a role in signaling pathways in the brain and to have neuroprotective properties at low concentrations. In recent years, different substances have been developed targeting Aβ production, aggregation, interaction with other molecules, and clearance, including peptide-based drugs. Aβ is a product of sequential cleavage of the membrane glycoprotein APP (amyloid precursor protein) by β- and γ-secretases. A number of familial mutations causing an early onset of the disease have been identified in the APP, especially in its transmembrane domain. The mutations are reported to influence the production, oligomerization, and conformational behavior of Aβ peptides. This review highlights the results of structural studies of the main proteins involved in Alzheimer's disease pathogenesis and the molecular mechanisms by which perspective therapeutic substances can affect Aβ production and nucleation.

Enhancing the binding of the β-sheet breaker peptide LPFFD to the amyloid-β fibrils by aromatic modifications: A molecular dynamics simulation study

Alzheimer's is a fatal neurodegenerative disease for which there is no cure at present. The disease is characterized by the presence of plaques in the brains of a patient, which are composed mainly of aggregates of the amyloid-β peptide in the form of β-sheet fibrils. Here, we investigated the possibility of exploiting the superior binding ability of aromatic amino acids to a particular model of the amyloid-β fibrils. which is a difficult target for drug design. The β-sheet breaker peptide LPFFD was modified with aromatic amino acids and its binding to these fibrils was studied. We found that the orientation and the electrostatic complementarity of the modified peptide with respect to the fibrils played a crucial role in determining whether its binding was improved by the aromatic amino acids. The modified LPFFD peptides were able to bind to those fibril residues. which are important in the aggregation of amyloid-β peptides and thus can potentially inhibit the further aggregation of the amyloid-beta peptides by blocking their interactions. We found that the tryptophan modified LPFFD peptides had the best binding affinities. In most cases, the aromatic amino acids in the N-terminus of the modified peptides made more contacts with the fibrils than those in the C-terminus. We also found that increasing the aromatic content did not significantly improve the binding of the LPFFD peptide to the fibrils. Our study can serve as a basis for the design of novel peptide-based drugs for Alzheimer's disease in which aromatic interactions play an important role.

Amyloid Oligomers: A Joint Experimental/Computational Perspective on Alzheimer's Disease, Parkinson's Disease, Type II Diabetes, and Amyotrophic Lateral Sclerosis

Protein misfolding and aggregation is observed in many amyloidogenic diseases affecting either the central nervous system or a variety of peripheral tissues. Structural and dynamic characterization of all species along the pathways from monomers to fibrils is challenging by experimental and computational means because they involve intrinsically disordered proteins in most diseases. Yet understanding how amyloid species become toxic is the challenge in developing a treatment for these diseases. Here we review what computer, in vitro, in vivo, and pharmacological experiments tell us about the accumulation and deposition of the oligomers of the (Aβ, tau), α-synuclein, IAPP, and superoxide dismutase 1 proteins, which have been the mainstream concept underlying Alzheimer's disease (AD), Parkinson's disease (PD), type II diabetes (T2D), and amyotrophic lateral sclerosis (ALS) research, respectively, for many years.

Nonequilibrium molecular dynamics simulations of infrared laser-induced dissociation of a tetrameric Aβ42 β-barrel in a neuronal membrane model

Experimental studies have reported that the amyloid-β proteins can form pores in cell membranes, and this could be one possible source of toxicity in Alzheimer's disease. Dissociation of these pores could therefore be a potential therapeutic approach. It is known that high photon density free-electron laser experiments and laser-induced nonequilibrium molecular dynamics simulations (NEMD) can dissociate amyloid fibrils at specific frequencies in vitro. Our question is whether NEMD simulations can dissociate amyloid pores in a bilayer mimicking a neuronal membrane, and as an example, we select a tetrameric Aβ42 β-barrel. Our simulations shows that the resonance between the laser field and the amide I vibrational mode of the barrel destabilises all intramolecular and intermolecular hydrogen bonds of Aβ42 and converts the β-barrel to a random/coil disordered oligomer. Starting from this disordered oligomer, extensive standard MD simulations shows sampling of disordered Aβ42 states without any increase of β-sheet and reports that the orientational order of lipids is minimally disturbed. Interestingly, the frequency to be employed to dissociate this beta-barrel is specific to the amino acid sequence. Taken together with our previous simulation results, this study indicates that infrared laser irradiation can dissociate amyloid fibrils and oligomers in bulk solution and in a membrane environment without affecting the surrounding molecules, offering therefore a promising way to retard the progression of AD.

Emergence of Barrel Motif in Amyloid-β Trimer: A Computational Study

Amyloid-β (Aβ) peptides form assemblies that are pathological hallmarks of Alzheimer's disease. Aβ oligomers are soluble, mobile, and toxic forms of the peptide that act in the extracellular space before assembling into protofibrils and fibrils. Therefore, oligomers play an important role in the mechanism of Alzheimer's disease. Since it is difficult to determine by experiment the atomic structures of oligomers, which accumulate fast and are polymorphic, computer simulation is a useful tool to investigate elusive oligomers' structures. In this work, we report extended all-atom molecular dynamics simulations, both canonical and replica exchange, of Aβ(1-42) trimer starting from two different initial conformations: (i) the pose produced by the best docking of a monomer aside of a dimer (simulation 1), representing oligomers freshly formed by assembling monomers, and (ii) a configuration extracted from an experimental mature fibril structure (simulation 2), representing settled oligomers in equilibrium with extended fibrils. We showed that in simulation 1, regions with small β-barrels are populated, indicating the chance of spontaneous formation of domains resembling channel-like structures. These structural domains are alternative to those more representative of mature fibrils (simulation 2), the latter showing a stable bundle of C-termini that is not sampled in simulation 1. Moreover, trimer of Aβ(1-42) can form internal pores that are large enough to be accessed by water molecules and Ca2+ ions.

Plant isoquinoline alkaloids as potential neurodrugs: A comparative study of the effects of benzo[c]phenanthridine and berberine-based compounds on β-amyloid aggregation

Herein we present a comparative study of the effects of isoquinoline alkaloids belonging to benzo[c]phenanthridine and berberine families on β-amyloid aggregation. Results obtained using a Thioflavine T (ThT) fluorescence assay and circular dichroism (CD) spectroscopy suggested that the benzo[c]phenanthridine nucleus, present in both sanguinarine and chelerythrine molecules, was directly involved in an inhibitory effect of Aβ_1-42 aggregation. Conversely, coralyne, that contains the isomeric berberine nucleus, significantly increased propensity for Aβ_1-42 to aggregate. Surface Plasmon Resonance (SPR) experiments provided quantitative estimation of these interactions: coralyne bound to Aβ_1-42 with an affinity (K_D = 11.6 μM) higher than benzo[c]phenanthridines. Molecular docking studies confirmed that all three compounds are able to recognize Aβ_1-42 in different aggregation forms suggesting their effective capacity to modulate the Aβ_1-42 self-recognition mechanism. Molecular dynamics simulations indicated that coralyne increased the β-content of Aβ_1-42, in early stages of aggregation, consistent with fluorescence-based promotion of the Aβ_1-42 self-recognition mechanism by this alkaloid. At the same time, sanguinarine induced Aβ_1-42 helical conformation corroborating its ability to delay aggregation as experimentally proved in vitro. The investigated compounds were shown to interfere with aggregation of Aβ_1-42 demonstrating their potential as starting leads for the development of therapeutic strategies in neurodegenerative diseases.

Latent Models of Molecular Dynamics Data: Automatic Order Parameter Generation for Peptide Fibrillization

Variational autoencoders are artificial neural networks with the capability to reduce highly dimensional sets of data to smaller dimensional, latent representations. In this work, these models are applied to molecular dynamics simulations of the self-assembly of coarse-grained peptides to obtain a singled-valued order parameter for amyloid aggregation. This automatically learned order parameter is constructed by time-averaging the latent parametrizations of internal coordinate representations and compared to the nematic order parameter which is commonly used to study ordering of similar systems in literature. It is found that the latent space value provides more tailored insight into the aggregation mechanism's details, correctly identifying fibril formation in instances where the nematic order parameter fails to do so. A means is provided by which the latent space value can be analyzed so that the major contributing internal coordinates are identified, allowing for a direct interpretation of the latent space order parameter in terms of the behavior of the system. The latent model is found to be an effective and convenient way of representing the data from the dynamic ensemble and provides a means of reducing the dimensionality of a system whose scale exceeds molecular systems so-far considered with similar tools. This bypasses a need for researcher speculation on what elements of a system best contribute to summarizing major transitions and suggests latent models are effective and insightful when applied to large systems with a diversity of complex behaviors.

Structures of the intrinsically disordered Aβ, tau and α-synuclein proteins in aqueous solution from computer simulations

Intrinsically disordered proteins (IDPs) play many biological roles in the human proteome ranging from vesicular transport, signal transduction to neurodegenerative diseases. The Aβ and tau proteins, and the α-synuclein protein, key players in Alzheimer's and Parkinson's diseases, respectively are fully disordered at the monomer level. The structural heterogeneity of the monomeric and oligomeric states and the high self-assembly propensity of these three IDPs have precluded experimental structural determination. Simulations have been used to determine the atomic structures of these IDPs. In this article, we review recent computer models to capture the equilibrium ensemble of Aβ, tau and α-synuclein proteins at different association steps in aqueous solution and present new results of the PEP-FOLD framework on α-synuclein monomer.

Molecular Mechanism and Kinetics of Amyloid-β42 Aggregate Formation: A Simulation Study

As an important neuropathological hallmark of Alzheimer's disease (AD), the oligomerization of amyloid-β (Aβ) peptides has been intensively investigated in both theoretical and experimental studies. However, the oligomerization space in terms of the kinetics, molecular mechanism, and oligomer structures remains mysterious to us. An equation that can quantitatively describe the time it takes for Aβ oligomers to appear in the human brain at a given Aβ monomer concentration is extremely vital for us to understand the development and disease progression of AD. In this study, we utilized molecular dynamics (MD) simulations to investigate the oligomerization of Aβ₄₂ peptides at five different monomer concentrations. We have elucidated the formation pathways of Aβ tetramers, characterized the oligomer structures, estimated the oligomerization time for Aβ dimers, trimers, and tetramers, and for the first-time derived equations that could quantitatively describe the relationship between the oligomerization time and the monomer concentration. Applying these equations, our prediction of oligomerization time agrees well with the experimental and clinical findings, in spite of the limitations of our oligomerization simulations. We have found that the Aβ oligomerization time depends on the monomer concentration by a power of -2.4. The newly established equations will enable us to quantitatively estimate the risk score of AD, which is a function of age. Moreover, we have identified the most dominant pathway of forming Aβ tetramers, probably the most important and toxic Aβ oligomer. Our results have shown that the structures of Aβ₄₂ dimer, trimer, and tetramer, which are distinguishable from each other, depend on the monomer concentration at which the oligomers form. Representative oligomer structures, which can serve as potential drug targets, have been identified by clustering analysis. The MD sampling adequacy has been validated by the excellent agreement between the calculated and measured collisional cross section (CCS) parameters (the prediction errors are within 2%). In a conclusion, this study provides the kinetics and structure basis for developing inhibitors to decelerate the Aβ oligomerization process.