Amyloid aggregation simulations: challenges, advances and perspectives

Helix-to-sheet transition of the Aβ42 peptide revealed using an enhanced sampling strategy and Markov state model

The self-assembly of Aβ peptides into toxic oligomers and fibrils is the primary cause of Alzheimer's disease. Moreover, the conformational transition from helix to sheet is considered a crucial step in the aggregation of Aβ peptides. However, the structural details of this process still remain unclear due to the heterogeneity and transient nature of the Aβ peptides. In this study, we developed an enhanced sampling strategy that combines artificial neural networks (ANN) with metadynamics to explore the conformational space of the Aβ42 peptides. The strategy consists of two parts: applying ANN to optimize CVs and conducting metadynamics based on the resulting CVs to sample conformations. The results showed that this strategy achieved better sampling performance in terms of the distribution of sampled conformations. The sampling efficiency is increased by 10-fold compared to our previous Hamiltonian Exchange Molecular Dynamics (MD) and by 1000-fold compared to ordinary MD. Based on the sampled conformations, we constructed a Markov state model to understand the detailed transition process. The intermediate states in this process are identified, and the connecting paths are analyzed. The conformational transitions in D23-K28 and M35-V40 are proven to be crucial for aggregation. These results are helpful in clarifying the mechanism and process of Aβ42 peptide aggregation. D23-K28 and M35-V40 can be identified as potential targets for screening and designing inhibitors of Aβ peptide aggregation.

The contrasting roles of co-solvents in protein formulations and food products

Protein aggregation is a major hurdle in developing biopharmaceuticals, in particular protein formulation area, but plays a pivotal role in food products. Co-solvents are used to suppress protein aggregation in pharmaceutical proteins. On the contrary, aggregation is encouraged in the process of food product making. Thus, it is expected that co-solvents play a contrasting role in biopharmaceutical formulation and food products. Here, we show several examples that utilize co-solvents, e.g., salting-out salts, sugars, polyols and divalent cations in promoting protein-protein interactions. The mechanisms of co-solvent effects on protein aggregation and solubility have been studied on aqueous protein solution and applied to develop pharmaceutical formulation based on the acquired scientific knowledge. On the contrary, co-solvents have been used in food industries based on empirical basis. Here, we will review the mechanisms of co-solvent effects on protein-protein interactions that can be applied to both pharmaceutical and food industries and hope to convey knowledge acquired through research on co-solvent interactions in aqueous protein solution and formulation to those involved in food science and provide those involved in protein solution research with the observations on aggregation behavior of food proteins.

Pyroglutamylation modulates electronic properties and the conformational ensemble of the amyloid β-peptide

Alzheimer's disease (AD) is a neurodegenerative disorder that is characterized by the formation of extracellular amyloid-β (Aβ) plaques. The underlying cause of AD is unknown, however, post-translational modifications (PTMs) of Aβ have been found in AD patients and are thought to play a role in protein aggregation. One such PTM is pyroglutamylation, which can occur at two sites in Aβ, Glu3 and Glu11. This modification of Aβ involves the truncation and charge-neutralization of N-terminal glutamate, causing Aβ to become more hydrophobic and prone to aggregation. The molecular mechanism by which the introduction of pyroglutamate (pE) promotes aggregation has not been determined. To gain a greater understanding of the role that charge neutralization and truncation of the N-terminus plays on Aβ conformational sampling, we used the Drude polarizable force field (FF) to perform molecular dynamics simulations on AβpE3-42 and AβpE11-42 and comparing their properties to previous simulations of Aβ1-42. The Drude polarizable FF allows for a more accurate representation of electrostatic interactions, therefore providing novel insights into the role that charge plays in protein dynamics. Here, we report the parametrization of pE in the Drude polarizable FF and the effect of pyroglutamylation on Aβ. We found that AβpE3-42 and AβpE11-42 alter the permanent and induced dipoles of the peptide. Specifically, we found that AβpE3-42 and AβpE11-42 have modification-specific backbone and sidechain polarization response and perturbed solvation properties that shift the Aβ conformational ensemble.

Can local heating and molecular crowders disintegrate amyloid aggregates?

The present study employs a blend of molecular dynamics simulations and a theoretical model to explore the potential disintegration mechanism of a matured Aβ octamer, aiming to offer a strategy to combat Alzheimer's disease. We investigate local heating and crowding effects on Aβ disintegration by selectively heating key Aβ segments and varying the concentration of sodium dodecyl sulphate (SDS), respectively. Despite initiation of disruption, Aβ aggregates resist complete disintegration during local heating due to rapid thermal energy distribution to the surrounding water. Conversely, although SDS molecules effectively inhibit Aβ aggregation at higher concentration through micelle formation, they fail to completely disintegrate the aggregate due to the exceedingly high energy barrier. To address the sampling challenge posed by the formidable energy barrier, we have performed well-tempered metadynamics simulations. Simulations reveal a multi-step disintegration mechanism for the Aβ octamer, suggesting a probable sequence: octamer → pentamer/hexamer ⇌ tetramer → monomer, with a rate-determining step constituting 45 kJ mol-1 barrier during the octamer to pentamer/hexamer transition. Additionally, we have proposed a novel two-state mean-field model based on Ising spins that offers an insight into the kinetics of the Aβ growth process and external perturbation effects on disintegration. Thus, the current simulation study, coupled with the newly introduced mean-field model, offers an insight into the detailed mechanisms underlying the Aβ aggregation process, guiding potential strategies for effective disintegration of Aβ aggregates.

Peptide Self-Assembly into Amyloid Fibrils: Unbiased All-Atom Simulations

Protein self-assembly plays an important role in biological systems, accounting for the formation of mesoscopic structures that can be highly symmetric as in the capsid of viruses or disordered as in molecular condensates or exhibit a one-dimensional fibrillar morphology as in amyloid fibrils. Deposits of the latter in tissues of individuals with degenerative diseases like Alzheimer's and Parkinson's has motivated extensive efforts to understand the sequence of molecular events accounting for their formation. These studies aim to identify on-pathway intermediates that may be the targets for therapeutic intervention. This detailed knowledge of fibril formation remains obscure, in part due to challenges with experimental analyses of these processes. However, important progress is being achieved for short amyloid peptides due to advances in our ability to perform completely unbiased all-atom simulations of the self-assembly process. This perspective discusses recent developments, their implications, and the hurdles that still need to be overcome to further advance the field.

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.

Molecular Mechanism of Tau Misfolding and Aggregation: Insights from Molecular Dynamics Simulation

Tau dysfunction has a close association with many neurodegenerative diseases, which are collectively referred to as tauopathies. Neurofibrillary tangles (NFTs) formed by misfolding and aggregation of tau are the main pathological process of tauopathy. Therefore, uncovering the misfolding and aggregation mechanism of tau protein will help to reveal the pathogenic mechanism of tauopathies. Molecular dynamics (MD) simulation is well suited for studying the dynamic process of protein structure changes. It provides detailed information on protein structure changes over time at the atomic resolution. At the same time, MD simulation can also simulate various conditions conveniently. Based on these advantages, MD simulations are widely used to study conformational transition problems such as protein misfolding and aggregation. Here, we summarized the structural features of tau, the factors affecting its misfolding and aggregation, and the applications of MD simulations in the study of tau misfolding and aggregation.

Perspective for Molecular Dynamics Simulation Studies of Amyloid-β Aggregates

The cause of Alzheimer's disease is related to aggregates such as oligomers and amyloid fibrils consisting of amyloid-β (Aβ) peptides. Molecular dynamics (MD) simulation studies have been conducted to understand the molecular mechanism of the formation and disruption of Aβ aggregates. In this Perspective, the MD simulation studies are classified into four categories, focusing on the target systems: aggregation of Aβ peptides in bulk solution, Aβ aggregation at the interface, aggregation inhibitor against Aβ peptides, and nonequilibrium MD simulation of Aβ aggregates. MD simulation studies in these categories are first reviewed. Future perspectives in each category are then presented. Finally, the overall perspective is presented on how MD simulations of Aβ aggregates can be utilized for developing Alzheimer's disease treatment.

Nucleation and Growth of Amyloid Fibrils

The formation of amyloid fibrils is a complex phenomenon that remains poorly understood at the atomic scale. Herein, we perform extended unbiased all-atom simulations in explicit solvent of a short amphipathic peptide to shed light on the three mechanisms accounting for fibril formation, namely, nucleation via primary and secondary mechanisms, and fibril growth. We find that primary nucleation takes place via the formation of an intermediate state made of two laminated β-sheets oriented perpendicular to each other. The amyloid fibril spine subsequently emerges from the rotation of these β-sheets to account for peptides that are parallel to each other and perpendicular to the main axis of the fibril. Growth of this spine, in turn, takes place via a dock-and-lock mechanism. We find that peptides dock onto the fibril tip either from bulk solution or after diffusing on the fibril surface. The latter docking pathway contributes significantly to populate the fibril tip with peptides. We also find that side chain interactions drive the motion of peptides in the lock phase during growth, enabling them to adopt the structure imposed by the fibril tip with atomic fidelity. Conversely, the docked peptide becomes trapped in a local free energy minimum when docked-conformations are sampled randomly. Our simulations also highlight the role played by nonpolar fibril surface patches in catalyzing and orienting the formation of small cross-β structures. More broadly, our simulations provide important new insights into the pathways and interactions accounting for primary and secondary nucleation as well as the growth of amyloid fibrils.

The stability and dynamics of the Aβ40/Aβ42 interlaced mixed fibrils

The accumulation of fibrillar amyloid-β (Aβ) aggregates in the brain, predominantly comprising 40- and 42-residue amyloid-β (Aβ40 and Aβ42), is a major pathological hallmark of Alzheimer's disease (AD). Aβ40 and Aβ42 naturally coexist in the brain under normal physiological conditions, and their interplay is generally considered to be a critical factor in the progression of AD. In addition to forming homogeneous oligomers and fibrils, Aβ40 and Aβ42 are also reported to co-assemble into hetero-oligomers and interlaced mixed fibrils, as evidenced by solid-state nuclear magnetic resonance spectroscopy (NMR), high molecular weight mass spectrometry and cross-seeding experiments. However, the exact molecular mechanisms underlying these processes remain unclear. In this study, we have used a recently resolved structurally uniform 1:1 mixture of Aβ40/Aβ42 interlaced mixed fibril as a prototype to gain insights into the molecular-level interactions between Aβ40 and Aβ42. We employed fully atomistic molecular dynamics simulation and compared the results with a homogeneous U-shaped Aβ40 fibrillar model. Our simulations using two different force fields provide conclusive evidence that the Aβ40/Aβ42 interlaced mixed fibril is energetically more favorable than the homogeneous Aβ40 fibrillar model. Furthermore, we also show that the increase in stability observed in the mixed model stems primarily from the packing interfaces and the stacking interfaces between C-termini. Our simulation results provide valuable mechanistic insights that are not readily accessible in experiment and could have significant implications for both the pathogenesis of AD and the development of current therapeutic strategies.Communicated by Ramaswamy H. Sarma.

Pathologic polyglutamine aggregation begins with a self-poisoning polymer crystal

A long-standing goal of amyloid research has been to characterize the structural basis of the rate-determining nucleating event. However, the ephemeral nature of nucleation has made this goal unachievable with existing biochemistry, structural biology, and computational approaches. Here, we addressed that limitation for polyglutamine (polyQ), a polypeptide sequence that causes Huntington's and other amyloid-associated neurodegenerative diseases when its length exceeds a characteristic threshold. To identify essential features of the polyQ amyloid nucleus, we used a direct intracellular reporter of self-association to quantify frequencies of amyloid appearance as a function of concentration, conformational templates, and rational polyQ sequence permutations. We found that nucleation of pathologically expanded polyQ involves segments of three glutamine (Q) residues at every other position. We demonstrate using molecular simulations that this pattern encodes a four-stranded steric zipper with interdigitated Q side chains. Once formed, the zipper poisoned its own growth by engaging naive polypeptides on orthogonal faces, in a fashion characteristic of polymer crystals with intramolecular nuclei. We further show that self-poisoning can be exploited to block amyloid formation, by genetically oligomerizing polyQ prior to nucleation. By uncovering the physical nature of the rate-limiting event for polyQ aggregation in cells, our findings elucidate the molecular etiology of polyQ diseases.

Disrupting Dimeric β-Amyloid by Electric Fields

The early oligomers of the amyloid Aβ peptide are implicated in Alzheimer's disease, but their transient nature complicates the characterization of their structure and toxicity. Here, we investigate the stability of the minimal toxic species, i.e., β-amyloid dimers, in the presence of an oscillating electric field. We first use deep learning (AlphaFold-multimer) for generating initial models of Aβ42 dimers. The flexibility and secondary structure content of the models are then analyzed by multiple runs of molecular dynamics (MD). Structurally stable models are similar to ensemble representatives from microsecond-long MD sampling. Finally, we employ the validated model as the starting structure of MD simulations in the presence of an external oscillating electric field and observe a fast decay of β-sheet content at high field strengths. Control simulations using the helical dimer of the 42-residue leucine zipper peptide show higher structural stability than the Aβ42 dimer. The simulation results provide evidence that an external electric field (oscillating at 1 GHz) can disrupt amyloid oligomers which should be further investigated by experiments with brain organoids in vitro and eventually in vivo.

Aggregation of an Amyloidogenic Peptide on Gold Surfaces

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

Pathologic polyglutamine aggregation begins with a self-poisoning polymer crystal

A long-standing goal of amyloid research has been to characterize the structural basis of the rate-determining nucleating event. However, the ephemeral nature of nucleation has made this goal unachievable with existing biochemistry, structural biology, and computational approaches. Here, we addressed that limitation for polyglutamine (polyQ), a polypeptide sequence that causes Huntington's and other amyloid-associated neurodegenerative diseases when its length exceeds a characteristic threshold. To identify essential features of the polyQ amyloid nucleus, we used a direct intracellular reporter of self-association to quantify frequencies of amyloid appearance as a function of concentration, conformational templates, and rational polyQ sequence permutations. We found that nucleation of pathologically expanded polyQ involves segments of three glutamine (Q) residues at every other position. We demonstrate using molecular simulations that this pattern encodes a four-stranded steric zipper with interdigitated Q side chains. Once formed, the zipper poisoned its own growth by engaging naive polypeptides on orthogonal faces, in a fashion characteristic of polymer crystals with intramolecular nuclei. We further show that self-poisoning can be exploited to block amyloid formation, by genetically oligomerizing polyQ prior to nucleation. By uncovering the physical nature of the rate-limiting event for polyQ aggregation in cells, our findings elucidate the molecular etiology of polyQ diseases.

Integrative modeling of diverse protein-peptide systems using CABS-dock

The CABS model can be applied to a wide range of protein-protein and protein-peptide molecular modeling tasks, such as simulating folding pathways, predicting structures, docking, and analyzing the structural dynamics of molecular complexes. In this work, we use the CABS-dock tool in two diverse modeling tasks: 1) predicting the structures of amyloid protofilaments and 2) identifying cleavage sites in the peptide substrates of proteolytic enzymes. In the first case, simulations of the simultaneous docking of amyloidogenic peptides indicated that the CABS model can accurately predict the structures of amyloid protofilaments which have an in-register parallel architecture. Scoring based on a combination of symmetry criteria and estimated interaction energy values for bound monomers enables the identification of protofilament models that closely match their experimental structures for 5 out of 6 analyzed systems. For the second task, it has been shown that CABS-dock coarse-grained docking simulations can be used to identify the positions of cleavage sites in the peptide substrates of proteolytic enzymes. The cleavage site position was correctly identified for 12 out of 15 analyzed peptides. When combined with sequence-based methods, these docking simulations may lead to an efficient way of predicting cleavage sites in degraded proteins. The method also provides the atomic structures of enzyme-substrate complexes, which can give insights into enzyme-substrate interactions that are crucial for the design of new potent inhibitors.

Critical Assessment of Self-Consistency Checks in the All-Atom Molecular Dynamics Simulation of Intrinsically Disordered Proteins

All atom simulations can be used to quantify conformational properties of Intrinsically Disordered Proteins (IDP). However, simulations must satisfy convergence checks to ensure observables computed from simulation are reliable and reproducible. While absolute convergence is purely a theoretical concept requiring infinitely long simulation, a more practical, yet rigorous, approach is to impose Self Consistency Checks (SCCs) to gain confidence in the simulated data. Currently there is no study of SCCs in IDPs, unlike their folded counterparts. In this paper, we introduce different criteria for self-consistency checks for IDPs. Next, we impose these SCCs to critically assess the performance of different simulation protocols using the N terminal domain of HIV Integrase and the linker region of SARS-CoV-2 Nucleoprotein as two model IDPs. All simulation protocols begin with all-atom implicit solvent Monte Carlo (MC) simulation and subsequent clustering of MC generated conformations to create the representative structures of the IDPs. These representative structures serve as the initial structure for subsequent molecular dynamics (MD) runs with explicit solvent. We conclude that generating multiple short (∼3 μs) MD simulation trajectories─all starting from the most representative MC generated conformation─and merging them is the protocol of choice due to (i) its ability to satisfy multiple SCCs, (ii) consistently reproducing experimental data, and (iii) the efficiency of running independent trajectories in parallel by harnessing multiple cores available in modern GPU clusters. Running one long trajectory (greater than 20 μs) can also satisfy the first two criteria but is less desirable due to prohibitive computation time. These findings help resolve the challenge of identifying a usable starting configuration, provide an objective measure of SCC, and establish rigorous criteria to determine the minimum length (for one long simulation) or number of trajectories needed in all-atom simulation of IDPs.

Interaction of the tau fibrils with the neuronal membrane

Tau proteins are recently gaining a lot of interest due to their active role in causing a range of tauopathies. Molecular mechanisms underlying the tau interaction with the neuronal membrane are hitherto unknown and difficult to characterize using experimental methods. Using the cryo-EM structure of the tau-fibrils we have used atomistic molecular dynamics simulation to model the tau fibril and neuronal membrane interaction using explicit solvation. The dynamics and structural characteristics of the tau fibril with the neuronal membrane are compared to the tau fibril in the aqueous phase to corroborate the effect of the neuronal membrane in the tau structure. Tau fibrils have been modelled using CHARMM-36m force field and the six component neuronal membrane composition is taken from the earlier simulation results. The timescale conceivable in our molecular dynamics simulations is of the order of microseconds which captures the onset of the interaction of the tau fibrils with the neuronal membrane. This interaction is found to impact the tau pathogenesis that finally causes neuronal toxicity. Our study initiates the understanding of tau conformational ensemble in the presence of neuronal membrane and sheds the light on the significant tau-membrane interactions.

Electrostatics-Induced Nucleated Conformational Transition of Protein Aggregation

Despite the wide existence of protein aggregation in nature and its intimate connection to many human diseases, the underlying mechanism remains unclear. Here, we develop a molecular theory by systematically incorporating the self-consistent field theory for charged macromolecules into the dilute solution thermodynamics. The kinetic pathway is tracked without any restriction on the morphology of the aggregates. We find that protein aggregation at low salt concentrations is via a two-step nucleated process involving a conformational transition from metastable spherical oligomer to elongated fibril. The scaling analysis elucidates the electrostatic origin of the conformational transition: the fibril enters the screening region much earlier than the spherical aggregate. As salt concentration increases, the classical mode of one-step nucleation corresponding to macroscopic liquid-liquid phase separation is recovered. Our results reveal that the screened electrostatic interaction is essential for the existence of the metastable oligomer and its subsequent conformational transition to fibril. The theoretical predictions of the kinetic pathway and the morphology of the aggregates are in good agreement with the experimental observations of real proteins.

Metastable alpha-rich and beta-rich conformations of small Aβ42 peptide oligomers

Probing the structures of amyloid-β (Aβ) peptides in the early steps of aggregation is extremely difficult experimentally and computationally. Yet, this knowledge is extremely important as small oligomers are the most toxic species. Experiments and simulations on Aβ42 monomer point to random coil conformations with either transient helical or β-strand content. Our current conformational description of small Aβ42 oligomers is funneled toward amorphous aggregates with some β-sheet content and rare high energy states with well-ordered assemblies of β-sheets. In this study, we emphasize another view based on metastable α-helix bundle oligomers spanning the C-terminal residues, which are predicted by the machine-learning AlphaFold2 method and supported indirectly by low-resolution experimental data on many amyloid polypeptides. This finding has consequences in developing novel chemical tools and to design potential therapies to reduce aggregation and toxicity.

IDP Force Fields Applied to Model PPII-Rich 33-mer Gliadin Peptides

The 33-mer gliadin peptide and its deamidated metabolite, 33-mer DGP, are the immunodominant peptides responsible for the adaptive immune response in celiac disease (CD). CD is a complex autoimmune chronic disorder triggered by gluten ingestion that affects the small intestine and affects ∼1% of the global population. The 33-mers are polyproline II-rich (PPII) and intrinsically disordered peptides (IDPs), whose structures remain elusive. We sampled the conformational ensembles of both 33-mer peptides via molecular dynamics simulations employing two force fields (FFs) (Amber ff03ws and Amber ff99SB-disp) specifically validated for other IDPs. Our results show that both FFs allow the extensive exploration of the conformational landscape, which was not possible with the standard FF GROMOS53A6 reported before. Clustering analysis of the trajectories showed that the five largest clusters (78-88% of the total structures) present elongated, semielongated, and curved conformations in both FFs. Large average radius of gyration and solvent-exposed surfaces characterized these structures. While the structures sampled are similar, the Amber ff99SB-disp trajectories explored folded conformations with a higher probability. In addition, PPII secondary structure was preserved throughout the trajectories (58-73%) together with a non-negligible content of β structures (11-23%), in agreement with previous experimental results. This work represents the initial step in studying further the interaction of these peptides with other biologically relevant molecules, which could lead to finally disclose the molecular events that lead to CD.

Inhibitory effects of sesquiterpene lactones on the aggregation and cytotoxicity of prion neuropeptide

The misfolding and conformational transformation of prion protein (PrP) are crucial to the progression of prion diseases. Screening for available natural inhibitors against prion proteins can contribute to the rational design and development of new anti-prion drugs and therapeutic strategies. The prion neuropeptide, PrP106-126 is commonly used as a model peptide of the abnormal PrP^Sc, and a number of potential inhibitors were explored against the amyloid fibril formation of PrP106-126. The well-known sesquiterpene lactone, artemisinin, shows diverse biological functions in anti-malarial, anti-cancer and lowering glucose. However, its inhibitory effect on PrP106-126 fibrillation is unclear. In this work, we selected two sesquiterpene lactones, artemisinin (1) and artesunate (2), to explore their roles in PrP106-126 aggregation by a series of physicochemical and biochemical methods. The results demonstrated that 1 and 2 could effectively impede the formation of amyloid fibrils and remodel the preformed fibrils. The binding of the small molecules to PrP106-126 was dominated by electrostatic, hydrophobic and hydrogen bonding interactions. In addition, both compounds exhibited neuroprotective effects by reducing peptide oligomerization. 2 showed better inhibition and regulation on peptide aggregation and cellular viability than 1 due to its specific succinate modification. Our study provides the information of sesquiterpene lactones to prevent PrP fibril formation and other related amyloidosis.

Biophysical and Integrative Characterization of Protein Intrinsic Disorder as a Prime Target for Drug Discovery

Protein intrinsic disorder is increasingly recognized for its biological and disease-driven functions. However, it represents significant challenges for biophysical studies due to its high conformational flexibility. In addressing these challenges, we highlight the complementary and distinct capabilities of a range of experimental and computational methods and further describe integrative strategies available for combining these techniques. Integrative biophysics methods provide valuable insights into the sequence–structure–function relationship of disordered proteins, setting the stage for protein intrinsic disorder to become a promising target for drug discovery. Finally, we briefly summarize recent advances in the development of new small molecule inhibitors targeting the disordered N-terminal domains of three vital transcription factors.

ALS-Linked A315T and A315E Mutations Enhance β-Barrel Formation of the TDP-43307-319 Hexamer: A REST2 Simulation Study

Pathogenic mutations of transactivation response element DNA-binding protein 43 (TDP-43) are closely linked with amyotrophic lateral sclerosis (ALS). It was recently reported that two ALS-linked familial mutants A315T and A315E of TDP-43_307-319 peptides can self-assemble into oligomers including tetramers, hexamers, and octamers, among which hexamers were suggested to form the β-barrel structure. However, due to the transient nature of oligomers, their conformational properties and the atomic mechanisms underlying the β-barrel formation remain largely elusive. Herein, we investigated the hexameric conformational distributions of the wild-type (WT) TDP-43_307-319 fragment and its A315T and A315E mutants by performing all-atom explicit-solvent replica exchange with solute tempering 2 simulations. Our simulations reveal that each peptide can self-assemble into diverse conformations including ordered β-barrels, bilayer β-sheets and/or monolayer β-sheets, and disordered complexes. A315T and A315E mutants display higher propensity to form β-barrel structures than the WT, which provides atomic explanation for their enhanced neurotoxicity reported previously. Detailed interaction analysis shows that A315T and A315E mutations increase inter-molecular interactions. Also, the β-barrel structures formed by the three different peptides are stabilized by distinct inter-peptide side-chain hydrogen bonding, hydrophobic, and aromatic stacking interactions. This study demonstrates the enhanced β-barrel formation of the TDP-43_307-319 hexamer by the pathogenic A315T and A315E mutations and reveals the underlying molecular determinants, which may be helpful for in-depth understanding of the ALS-mutation-induced neurotoxicity of TDP-43 protein.

Phosphorylation at Ser289 Enhances the Oligomerization of Tau Repeat R2

In tauopathies such as Alzheimer's disease (AD), aberrant phosphorylation causes the dissociation of tau proteins from microtubules. The dissociated tau then aggregates into sequent forms from soluble oligomers to paired helical filaments and insoluble neurofibrillary tangles (NFTs). NFTs is a hallmark of AD, while oligomers are found to be the most toxic form of the tau aggregates. Therefore, understanding tau oligomerization with regard to abnormal phosphorylation is important for the therapeutic development of AD. In this study, we investigated the impact of phosphorylated Ser289, one of the 40 aberrant phosphorylation sites of full-length tau proteins, on monomeric and dimeric structures of tau repeat R2 peptides. We carried out intensive replica exchange molecular dynamics simulation with a total simulation time of up to 0.1 ms. Our result showed that the phosphorylation significantly affected the structures of both the monomer and the dimer. For the monomer, the phosphorylation enhanced ordered-disordered structural transition and intramolecular interaction, leading to more compactness of the phosphorylated R2 compared to the wild-type one. As to the dimer, the phosphorylation increased intermolecular interaction and β-sheet formation, which can accelerate the oligomerization of R2 peptides. This result suggests that the phosphorylation at Ser289 is likely to promote tau aggregation. We also observed a phosphorylated Ser289-Na+-phosphorylated Ser289 bridge in the phosphorylated R2 dimer, suggesting an important role of cation ions in tau aggregation. Our findings suggest that phosphorylation at Ser289 should be taken into account in the inhibitor screening of tau oligomerization.

Insights into the Mixture of Aβ24 and Aβ42 Peptides from Atomistic Simulations

Amyloid-β (Aβ) oligomers play a central role in Alzheimer's disease (AD). Plaques of AD patients consist of Aβ40 and Aβ42 peptides and truncated Aβ peptides. The Aβ24 peptide, identified in human AD brains, was found to impair Aβ42 clearance through the brain-blood barrier. The Aβ24 peptide was also shown to reduce Aβ42 aggregation kinetics in pure buffer, but the underlying mechanism is unknown at atomistic level. In this study, we explored the conformational ensemble of the equimolar mixture of Aβ24 and Aβ42 by replica exchange molecular dynamics simulations and compared it to our previous results on the pure Aβ42 dimer. Our simulations demonstrate that the truncation at residue 24 changes the secondary, tertiary, and quaternary structures of the dimer, offering an explanation of the slower aggregation kinetics of the mixture.

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.

Effects of External Perturbations on Protein Systems: A Microscopic View

Protein folding can be viewed as the origami engineering of biology resulting from the long process of evolution. Even decades after its recognition, research efforts worldwide focus on demystifying molecular factors that underlie protein structure-function relationships; this is particularly relevant in the era of proteopathic disease. A complex co-occurrence of different physicochemical factors such as temperature, pressure, solvent, cosolvent, macromolecular crowding, confinement, and mutations that represent realistic biological environments are known to modulate the folding process and protein stability in unique ways. In the current review, we have contextually summarized the substantial efforts in unveiling individual effects of these perturbative factors, with major attention toward bottom-up approaches. Moreover, we briefly present some of the biotechnological applications of the insights derived from these studies over various applications including pharmaceuticals, biofuels, cryopreservation, and novel materials. Finally, we conclude by summarizing the challenges in studying the combined effects of multifactorial perturbations in protein folding and refer to complementary advances in experiment and computational techniques that lend insights to the emergent challenges.

Does the inclusion of electronic polarisability lead to a better modelling of peptide aggregation?

Simulating the process of amyloid aggregation with atomic detail is a challenging task for various reasons. One of them is that it is difficult to parametrise a force field such that all protein states ranging from the folded through the unfolded to the aggregated state are represented with the same level of accuracy. Here, we test whether the consideration of electronic polarisability improves the description of the different states of Aβ16-22. Surprisingly, the CHARMM Drude polarisable force field is found to perform worse than its unpolarisable counterpart CHARMM36m. Sources for this failure of the Drude model are discussed.

Multi-eGO: An in silico lens to look into protein aggregation kinetics at atomic resolution

Protein aggregation into amyloid fibrils is the archetype of aberrant biomolecular self-assembly processes, with more than 50 associated diseases that are mostly uncurable. Understanding aggregation mechanisms is thus of fundamental importance and goes in parallel with the structural characterization of the transient oligomers formed during the process. Oligomers have been proven elusive to high-resolution structural techniques, while the large sizes and long time scales, typical of aggregation processes, have limited the use of computational methods to date. To surmount these limitations, we here present multi-eGO, an atomistic, hybrid structure-based model which, leveraging the knowledge of monomers conformational dynamics and of fibril structures, efficiently captures the essential structural and kinetics aspects of protein aggregation. Multi-eGO molecular dynamics simulations can describe the aggregation kinetics of thousands of monomers. The concentration dependence of the simulated kinetics, as well as the structural features of the resulting fibrils, are in qualitative agreement with in vitro experiments carried out on an amyloidogenic peptide from Transthyretin, a protein responsible for one of the most common cardiac amyloidoses. Multi-eGO simulations allow the formation of primary nuclei in a sea of transient lower-order oligomers to be observed over time and at atomic resolution, following their growth and the subsequent secondary nucleation events, until the maturation of multiple fibrils is achieved. Multi-eGO, combined with the many experimental techniques deployed to study protein aggregation, can provide the structural basis needed to advance the design of molecules targeting amyloidogenic diseases.

ALS-associated A315E and A315pT variants exhibit distinct mechanisms in inducing irreversible aggregation of TDP-43312-317 peptides

Amyotrophic lateral sclerosis (ALS) is intensively associated with insoluble aggregates formed by transactivation response element DNA-binding protein 43 (TDP-43) in the cytoplasm of neuron cells. A recent experimental study reported that two ALS-linked familial variants, A315E and A315pT (pT, phosphorylated threonine), can induce irreversible aggregation of the TDP-43 ³¹²NFGAFS³¹⁷ segment (TDP-43_312-317). However, the underlying molecular mechanism remains largely elusive. Here, we investigated the early aggregation process of the wild type (WT) ³¹²NFGAFS³¹⁷ segment and its A315E and A315pT variants by performing multiple microsecond all-atom molecular dynamics simulations. Our simulations show that the two variants display lower fluidity than WT, consistent with their decreased labilities observed in previous denaturation assay experiments. Despite each of the two variants carrying one negative charge, unexpectedly, we find that both A315E mutation and A315pT phosphorylation enhance intermolecular interactions and result in the formation of more compact oligomers. Compared to WT, A315E oligomers possess low β-sheet content but a compact hydrophobic core, while A315pT oligomers have high β-sheet content and large β-sheets. Side chain hydrogen-bonding and hydrophobic interactions as well as N312-E315 salt bridges contribute most to the increased aggregation propensity of the A315E mutant. By contrast, main chain and side chain hydrogen-bonding interactions, side chain hydrophobic and aromatic interactions, are crucial to the enhanced aggregation capability of the A315pT variant. These results indicate that glutamate mutation and phosphorylation at position 315 induce the irreversible aggregation of TDP-43_312-317 peptides through differential mechanisms, which remind us that we should be careful in the investigation of the phosphorylation effect on protein aggregation by using phosphomimetic substitutions. This study provides mechanistic insights into the A315E/A315pT-induced irreversible aggregation of TDP-43_312-317, which may be helpful for the in-depth understanding of ALS-mutation/phosphorylation-associated liquid-to-solid phase transition of TDP-43 protein aggregates.

Pore Formation Mechanism of A-Beta Peptide on the Fluid Membrane: A Combined Coarse-Grained and All-Atomic Model

In Alzheimer’s disease, ion permeability through the ionic channel formed by Aβ peptides on cellular membranes appears to underlie neuronal cell death. An understanding of the formation mechanism of the toxic ionic channel by Aβ peptides is very important, but remains unclear. Our simulation results demonstrated the dynamics and mechanism of channel formation by Aβ1-28 peptides on the DPPC and POPC membrane by the coarse-grained method. The ionic channel formation is driven by the gyration of the radius and solvent accessible molecular surface area of Aβ1-28 peptides. The ionic channel formation mechanism was explored by the free energy profile based on the distribution of the gyration of the radius and solvent accessible molecular surface area of Aβ1-28 peptides on the fluid membrane. The stability and water permeability of the ionic channel formed by Aβ peptides was investigated by all-atomic model simulation. Our simulation showed that the ionic channel formed by Aβ1-28 peptides is very stable and has a good water permeability. This could help us to understand the pore formation mechanism by Aβ1-28 peptides on the fluidic membrane. It also provides us with a guideline by which to understand the toxicity of Aβ1-28 peptides’ pores to the cell.

Virtual Quasi-2D Intermediates as Building Blocks for Plausible Structural Models of Amyloid Fibrils from Proteins with Complex Topologies: A Case Study of Insulin

Conformational transitions of globular proteins into amyloid fibrils are complex multistage processes exceedingly challenging to simulate using molecular dynamics (MD). Slow monomer diffusion rates and rugged free energy landscapes disfavor swift self-assembly of orderly amyloid architectures within timescales accessible to all-atom MD. Here, we conduct a multiscale MD study of the amyloidogenic self-assembly of insulin: a small protein with a complex topology defined by two polypeptide chains interlinked by three disulfide bonds. To avoid kinetic traps, unconventional preplanarized insulin conformations are used as amyloid building blocks. These starting conformers generated through uniaxial compression of the native monomer in various spatial directions represent 6 distinct (out of 16 conceivable) two-dimensional (2D) topological classes varying in N-/C-terminal segments of insulin's A- and B-chains being placed inside or outside of the central loop constituted by the middle sections of both chains and Cys7A-Cys7B/Cys19B-Cys20A disulfide bonds. Simulations of the fibrillar self-assembly are initiated through a biased in-register alignment of two, three, or four layers of flat conformers belonging to a single topological class. The various starting topologies are conserved throughout the self-assembly process resulting in polymorphic amyloid fibrils varying in structural features such as helical twist, presence of cavities, and overall stability. Some of the protofilament structures obtained in this work are highly compatible with the earlier biophysical studies on insulin amyloid and high-resolution studies on insulin-derived amyloidogenic peptide models postulating the presence of steric zippers. Our approach provides in silico means to study amyloidogenic tendencies and viable amyloid architectures of larger disulfide-constrained proteins with complex topologies.

Simulations of Cross-Amyloid Aggregation of Amyloid-β and Islet Amyloid Polypeptide Fragments

Amyloid-beta (Aβ) and islet amyloid polypeptide (IAPP) are small peptides, classified as amyloids, that have the potential to self-assemble and form cytotoxic species, such as small soluble oligomers and large insoluble fibrils. The formation of Aβ aggregates facilitates the progression of Alzheimer's disease (AD), while IAPP aggregates induce pancreatic β-cell apoptosis, leading to exacerbation of Type 2 diabetes (T2D). Cross-amyloid interactions between Aβ and IAPP have been described both in vivo and in vitro, implying the role of Aβ or IAPP as modulators of cytotoxic self-aggregation of each species, and suggesting that Aβ-IAPP interactions are a potential molecular link between AD and T2D. Using molecular dynamics simulations, "hot spot" regions of the two peptides were studied to understand the formation of hexamers in a heterogenous and homogenous peptide-containing environment. Systems of only Aβ_(16-22) peptides formed antiparallel, β-barrel-like structures, while systems of only IAPP_(20-29) peptides formed stacked, parallel beta sheets and had relatively unstable aggregation structures after 2 μs of simulation time. Systems containing both Aβ and IAPP (1:1 ratio) hexamers showed antiparallel, β-barrel-like structures, with an interdigitated arrangement of Aβ_(16-22) and IAPP_(20-29). These β-barrel structures have features of cytotoxic amyloid species identified in previous literature. Ultimately, this work seeks to provide atomistic insight into both the mechanism behind cross-amyloid interactions and structural morphologies of these toxic amyloid species.

Influencing factors and characterization methods of nanoparticles regulating amyloid aggregation

Human disorders associated with amyloid aggregation, such as Alzheimer's disease and Parkinson's disease, afflict the lives of millions worldwide. When peptides and proteins in the body are converted to amyloids, which have a tendency to aggregate, the toxic oligomers produced during the aggregation process can trigger a range of diseases. Nanoparticles (NPs) have been found to possess surface effects that can modulate the amyloid aggregation process and they have potential application value in the treatment of diseases related to amyloid aggregation and fibrillary tangles. In this review, we discuss recent progress relating to studies of nanoparticles that regulate amyloid aggregation. The review focuses on the factors influencing this regulation, which are important as guidelines for the future design of NPs for the treatment of amyloid aggregation. We describe the characterization methods that have been utilized so far in such studies. This review provides research information and characterization methods for the rational design of NPs, which should result in therapeutic strategies for amyloid diseases.

Molecular Dynamics Simulation Studies on the Aggregation of Amyloid-β Peptides and Their Disaggregation by Ultrasonic Wave and Infrared Laser Irradiation

Alzheimer’s disease is understood to be caused by amyloid fibrils and oligomers formed by aggregated amyloid-β (Aβ) peptides. This review article presents molecular dynamics (MD) simulation studies of Aβ peptides and Aβ fragments on their aggregation, aggregation inhibition, amyloid fibril conformations in equilibrium, and disruption of the amyloid fibril by ultrasonic wave and infrared laser irradiation. In the aggregation of Aβ, a β-hairpin structure promotes the formation of intermolecular β-sheet structures. Aβ peptides tend to exist at hydrophilic/hydrophobic interfaces and form more β-hairpin structures than in bulk water. These facts are the reasons why the aggregation is accelerated at the interface. We also explain how polyphenols, which are attracting attention as aggregation inhibitors of Aβ peptides, interact with Aβ. An MD simulation study of the Aβ amyloid fibrils in equilibrium is also presented: the Aβ amyloid fibril has a different structure at one end from that at the other end. The amyloid fibrils can be destroyed by ultrasonic wave and infrared laser irradiation. The molecular mechanisms of these amyloid fibril disruptions are also explained, particularly focusing on the function of water molecules. Finally, we discuss the prospects for developing treatments for Alzheimer’s disease using MD simulations.

Molecular simulations of proteins: From simplified physical interactions to complex biological phenomena

Molecular dynamics simulation is the most popular computational technique for investigating the structural and dynamical behaviour of proteins, in search of the molecular basis of their function. Far from being a completely settled field of research, simulations are still evolving to best capture the essential features of the atomic interactions that govern a protein's inner motions. Modern force fields are becoming increasingly accurate in providing a physical description adequate to this purpose, and allow us to model complex biological systems under fairly realistic conditions. Furthermore, the use of accelerated sampling techniques is improving our access to the observation of progressively larger molecular structures, longer time scales, and more hidden functional events. In this review, the basic principles of molecular dynamics simulations and a number of key applications in the area of protein science are summarized, and some of the most important results are discussed. Examples include the study of the structure, dynamics and binding properties of 'difficult' targets, such as intrinsically disordered proteins and membrane receptors, and the investigation of challenging phenomena like hydration-driven processes and protein aggregation. The findings described provide an overall picture of the current state of this research field, and indicate new perspectives on the road ahead to the upcoming future of molecular simulations.

Triterpenoids impede the fibrillation and cytotoxicity of human islet amyloid polypeptide

The inhibition of human islet amyloid polypeptide (hIAPP) deposition to block its toxicity is an important strategy for the prevention and treatment of type II diabetes mellitus (T2DM).Natural compounds with pharmacological properties and low toxicity can serve as a good point to discover potential inhibitors of protein misfolding, which may be useful for the treatment of various amyloidosis-related diseases. Previous studies have reported that triterpenoids, such as maslinic acid (MA) and momordicin I (MI), can modulate glucose metabolism partially by reducing insulin resistance. However, the internal antidiabetic mechanism of these triterpenoids remains unclear. In this study, we examined the inhibition and disaggregation of MAandits isomer MI on the fibrillation of hIAPP using various experimental and computational approaches. The assembly behaviors and peptide-induced cytotoxicity of hIAPP could be effectively resisted by MA and MI. Moreover, the interaction of the two triterpenoids with hIAPP displayed a spontaneous and exothermic process. Moreover, molecular dynamics simulation results of different peptides revealed that MA and MI could bind to Asn and other non-polar residues near the core C-terminal region and reduce the oligomerization of hIAPP. The binding affinity was predominantly contributed by hydrophobic, electrostatic and hydrogen bonding interactions. The present work provides valuable data for MA and MI to treat T2DM and amyloidosis-related diseases.

Effect of Cholesterol Molecules on Aβ1-42 Wild-Type and Mutants Trimers

Alzheimer’s disease displays aggregates of the amyloid-beta (Aβ) peptide in the brain, and there is increasing evidence that cholesterol may contribute to the pathogenesis of the disease. Though many experimental and theoretical studies have focused on the interactions of Aβ oligomers with membrane models containing cholesterol, an understanding of the effect of free cholesterol on small Aβ42 oligomers is not fully established. To address this question, we report on replica exchange with a solute tempering simulation of an Aβ42 trimer with cholesterol and compare it with a previous replica exchange molecular dynamics simulation. We show that the binding hot spots of cholesterol are rather complex, involving hydrophobic residues L17–F20 and L30–M35 with a non-negligible contribution of loop residues D22–K28 and N-terminus residues. We also examine the effects of cholesterol on the trimers of the disease-causing A21G and disease-protective A2T mutations by molecular dynamics simulations. We show that these two mutations moderately impact cholesterol-binding modes. In our REST2 simulations, we find that cholesterol is rarely inserted into aggregates but rather attached as dimers and trimers at the surface of Aβ42 oligomers. We propose that cholesterol acts as a glue to speed up the formation of larger aggregates; this provides a mechanistic link between cholesterol and Alzheimer’s disease.

Peptide Self-Assembled Nanostructures: From Models to Therapeutic Peptides

Self-assembly is the most suitable approach to obtaining peptide-based materials on the nano- and mesoscopic scales. Applications span from peptide drugs for personalized therapy to light harvesting and electron conductive media for solar energy production and bioelectronics, respectively. In this study, we will discuss the self-assembly of selected model and bioactive peptides, in particular reviewing our recent work on the formation of peptide architectures of nano- and mesoscopic size in solution and on solid substrates. The hierarchical and cooperative characters of peptide self-assembly will be highlighted, focusing on the structural and dynamical properties of the peptide building blocks and on the nature of the intermolecular interactions driving the aggregation phenomena in a given environment. These results will pave the way for the understanding of the still-debated mechanism of action of an antimicrobial peptide (trichogin GA IV) and the pharmacokinetic properties of a peptide drug (semaglutide) currently in use for the therapy of type-II diabetes.

How the Choice of Force-Field Affects the Stability and Self-Assembly Process of Supramolecular CTA Fibers

In recent years, computational methods have become an essential element of studies focusing on the self-assembly process. Although they provide unique insights, they face challenges, from which two are the most often mentioned in the literature: the temporal and spatial scale of the self-assembly. A less often mentioned issue, but not less important, is the choice of the force-field. The repetitive nature of the supramolecular structure results in many similar interactions. Consequently, even a small deviation in these interactions can lead to significant energy differences in the whole structure. However, studies comparing different force-fields for self-assembling systems are scarce. In this article, we compare molecular dynamics simulations for trifold hydrogen-bonded fibers performed with different force-fields, namely GROMOS, CHARMM General Force Field (CGenFF), CHARMM Drude, General Amber Force-Field (GAFF), Martini, and polarized Martini. Briefly, we tested the force-fields by simulating: (i) spontaneous self-assembly (none form a fiber within 500 ns), (ii) stability of the fiber (observed for CHARMM Drude, GAFF, MartiniP), (iii) dimerization (observed for GROMOS, GAFF, and MartiniP), and (iv) oligomerization (observed for CHARMM Drude and MartiniP). This system shows that knowledge of the force-field behavior regarding interactions in oligomer and larger self-assembled structures is crucial for designing efficient simulation protocols for self-assembling systems.

Anatomy and Formation Mechanisms of Early Amyloid-β Oligomers with Lateral Branching: Graph Network Analysis on Large-Scale Simulations

Oligomeric amyloid-β aggregates (AβOs) effectively trigger Alzheimer's disease-related toxicity, generating great interest in understanding their structures and formation mechanisms. However, AβOs are heterogeneous and transient, making their structure and formation difficult to study. Here, we performed graph network analysis of tens of microsecond massive simulations of early amyloid-β (Aβ) aggregations at near-atomic resolution to characterize AβO structures with sizes up to 20-mers. We found that AβOs exhibit highly curvilinear, irregular shapes with occasional lateral branches, consistent with recent cryo-electron tomography experiments. We also found that Aβ40 oligomers were more likely to develop branches than Aβ42 oligomers, explaining an experimental observation that only Aβ40 was trapped in network-like aggregates and exhibited slower fibrillization kinetics. Moreover, AβO architecture dissection revealed that their curvilinear appearance is related to the local packing geometries of neighboring peptides and that Aβ40's greater branching ability originates from specific C-terminal interactions at branching interfaces. Finally, we demonstrate that whether Aβ oligomerization causes oligomers to elongate or to branch depends on the sizes and shapes of colliding aggregates. Collectively, this study provides bottom-up structural information for understanding early Aβ aggregation and AβO toxicity.

Graph network analysis on large-scale simulations uncovers the differential branching behaviours of large Aβ40 and Aβ42 oligomers.

Impact of Electronic Polarization on Preformed, β-Strand Rich Homogenous and Heterogeneous Amyloid Oligomers

Amyloids are a subset of intrinsically disordered proteins (IDPs) that self-assemble into cross-[Formula: see text] oligomers and fibrils. The structural plasticity of amyloids leads to sampling of metastable, low-molecular-weight oligomers that contribute to cytotoxicity. Of interest are amyloid-[Formula: see text] (A[Formula: see text] and islet amyloid polypeptide (IAPP), which are involved in the pathology of Alzheimer’s disease and Type 2 diabetes mellitus, respectively. In addition to forming homogenous oligomers and fibrils, these species have been found to cross-aggregate in heterogeneous structures. Biophysical properties, including electronic effects, that are unique or conserved between homogenous and heterogeneous amyloids oligomers are thus far unexplored. Here, we simulated homogenous and heterogeneous amyloid oligomers of A[Formula: see text] and IAPP[Formula: see text] fragments using the Drude oscillator model to investigate the impact of electronic polarization on the structural morphology and stability of preformed hexamers. Upon simulation of preformed, [Formula: see text]-strand rich oligomers with Drude, structural rearrangement occurred causing some loss of [Formula: see text]-strand structure in favor of random coil content for all oligomers. Homogenous A[Formula: see text] was the most stable system, deriving stability from low polarization in hydrophobic residues and through salt bridge formation. Changes in polarization were observed primarily for A[Formula: see text] residues in heterogeneous cross-amyloid systems, displaying a decrease in charged residue dipole moments and an increase in hydrophobic sidechain dipole moments. This work is the first study utilizing the Drude-2019 force field with amyloid oligomers, providing insight into the impact of electronic effects on oligomer structure and highlighting the importance of different microenvironments on amyloid oligomer stability.

Disorder-to-order transition of the amyloid-β peptide upon lipid binding

There is mounting evidence that Alzheimer's disease progression and severity are linked to neuronal membrane damage caused by aggregates of the amyloid-β (Aβ) peptide. However, the detailed mechanism behind the membrane damage is not well understood yet. Recently, the lipid-chaperone hypothesis has been put forward, based on which the formation of complexes between Aβ and free lipids enables an easy insertion of Aβ into membranes. In order to test this hypothesis, we performed numerous all-atom molecular dynamics simulations. We studied the complex formation between individual lipids, considering both POPC and DPPC, and Aβ and examined whether the resulting complexes would be able to insert into lipid membranes. Complex formation at a one-to-one ratio was readily observed, yet with minimal effects on Aβ's characteristics. Most importantly, the peptide remains largely disordered in 1:1 complexes, and the complex does not insert into the membrane; instead, it is adsorbed to the membrane surface. The results change considerably once Aβ forms a complex with a POPC cluster composed of three lipid molecules. The hydrophobic interactions between Aβ and the lipid tails cause the peptide to fold into either a helical or a β-sheet structure. These observations provide atomic insight into the disorder-to-order transition that is needed for membrane insertion or amyloid aggregation to proceed.

Multiscale Modeling of Amyloid Fibrils Formed by Aggregating Peptides Derived from the Amyloidogenic Fragment of the A-Chain of Insulin

Computational prediction of molecular structures of amyloid fibrils remains an exceedingly challenging task. In this work, we propose a multi-scale modeling procedure for the structure prediction of amyloid fibrils formed by the association of ACC_1-13 aggregation-prone peptides derived from the N-terminal region of insulin’s A-chain. First, a large number of protofilament models composed of five copies of interacting ACC_1-13 peptides were predicted by application of CABS-dock coarse-grained (CG) docking simulations. Next, the models were reconstructed to all-atom (AA) representations and refined during molecular dynamics (MD) simulations in explicit solvent. The top-scored protofilament models, selected using symmetry criteria, were used for the assembly of long fibril structures. Finally, the amyloid fibril models resulting from the AA MD simulations were compared with atomic force microscopy (AFM) imaging experimental data. The obtained results indicate that the proposed multi-scale modeling procedure is capable of predicting protofilaments with high accuracy and may be applied for structure prediction and analysis of other amyloid fibrils.

Exploring amyloid oligomers with peptide model systems

The assembly of amyloidogenic peptides and proteins, such as the β-amyloid peptide, α-synuclein, huntingtin, tau, and islet amyloid polypeptide, into amyloid fibrils and oligomers is directly linked to amyloid diseases, such as Alzheimer's, Parkinson's, and Huntington's diseases, frontotemporal dementias, and type II diabetes. Although amyloid oligomers have emerged as especially important in amyloid diseases, high-resolution structures of the oligomers formed by full-length amyloidogenic peptides and proteins have remained elusive. Investigations of oligomers assembled from fragments or stabilized β-hairpin segments of amyloidogenic peptides and proteins have allowed investigators to illuminate some of the structural, biophysical, and biological properties of amyloid oligomers. Here, we summarize recent advances in the application of these peptide model systems to investigate and understand the structures, biological properties, and biophysical properties of amyloid oligomers.

Amyloid-β peptide dimers undergo a random coil to β-sheet transition in the aqueous phase but not at the neuronal membrane

Mounting evidence suggests that the neuronal cell membrane is the main site of oligomer-mediated neuronal toxicity of amyloid-β peptides in Alzheimer's disease. To gain a detailed understanding of the mutual interference of amyloid-β oligomers and the neuronal membrane, we carried out microseconds of all-atom molecular dynamics (MD) simulations on the dimerization of amyloid-β (Aβ)42 in the aqueous phase and in the presence of a lipid bilayer mimicking the in vivo composition of neuronal membranes. The dimerization in solution is characterized by a random coil to β-sheet transition that seems on pathway to amyloid aggregation, while the interactions with the neuronal membrane decrease the order of the Aβ42 dimer by attenuating its propensity to form a β-sheet structure. The main lipid interaction partners of Aβ42 are the surface-exposed sugar groups of the gangliosides GM1. As the neurotoxic activity of amyloid oligomers increases with oligomer order, these results suggest that GM1 is neuroprotective against Aβ-mediated toxicity.

Energy landscapes of protein aggregation and conformation switching in intrinsically disordered proteins

The protein folding problem was apparently solved recently by the advent of a deep learning method for protein structure prediction called AlphaFold. However, this program is not able to make predictions about the protein folding pathways. Moreover, it only treats about half of the human proteome, as the remaining proteins are intrinsically disordered or contain disordered regions. By definition these proteins differ from natively folded proteins and do not adopt a properly folded structure in solution. However these intrinsically disordered proteins (IDPs) also systematically differ in amino acid composition and uniquely often become folded upon binding to an interaction partner. These factors preclude solving IDP structures by current machine-learning methods like AlphaFold, which also cannot solve the protein aggregation problem, since this meta-folding process can give rise to different aggregate sizes and structures. An alternative computational method is provided by molecular dynamics simulations that already successfully explored the energy landscapes of IDP conformational switching and protein aggregation in multiple cases. These energy landscapes are very different from those of 'simple' protein folding, where one energy funnel leads to a unique protein structure. Instead, the energy landscapes of IDP conformational switching and protein aggregation feature a number of minima for different competing low-energy structures. In this review, I discuss the characteristics of these multifunneled energy landscapes in detail, illustrated by molecular dynamics simulations that elucidated the underlying conformational transitions and aggregation processes.