Key Residue for Aggregation of Amyloid-β Peptides

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.

Nonequilibrium Molecular Dynamics Method to Generate Poiseuille-Like Flow between Lipid Bilayers

There are various flows inside and outside cells in vivo. Nonequilibrium molecular dynamics (NEMD) simulation is a useful tool for understanding the effects of these flows on the dynamics of biomolecules. We propose an NEMD method to generate a Poiseuille-like flow between lipid bilayers. We extended the conventional equilibrium MD method to produce a flow by adding constant external force terms to the water molecules. Using the Lagrange multiplier method, the center of mass of the lipid bilayer is constrained so that the flow does not sweep away the lipid bilayer, but the individual lipid molecules fluctuate. The temperature of the system is controlled properly in the solution and membrane by using the Nosé-Hoover thermostat. We found that the flow velocity increases linearly as the applied external force term increases. It is possible to estimate the appropriate value of acceleration to generate a flow with an arbitrary velocity using this proportional relation once a single short MD simulation is performed. We also found that the flow between two lipid bilayers is slower than the analytical solution of the Navier-Stokes equations between rigid parallel plates due to the interactions between water molecules and the membrane. This method can be applied not only to a flow on lipid membranes but also to a flow on soft surfaces generally.

Critical aggregation concentration and reversibility of amyloid-β (1-40) oligomers

Amyloid-beta (Aβ) aggregation is a critical factor in the pathogenesis of Alzheimer's disease, with distinct aggregation behaviours observed between its isoforms Amyloid-β 1-40 (Aβ40) and 1-42 (Aβ42). In this study, we investigated the aggregation properties of Aβ40 using fluorescence correlation spectroscopy (FCS) and detailed data analysis. Our results reveal that Aβ40 undergoes a two-step cooperative aggregation process. The first step, characterized by a critical aggregation concentration (cac) of 0.5 ± 0.3 μM, results in the formation of metastable oligomers of 5-25 monomers and stable oligomers of 50-100 monomers, with less than 10 % of the total amyloid aggregated. The second step, with a cac of 19 ± 2 μM, leads to the formation of much larger aggregates, consistent with protofibrils, and approximately 50 % aggregated amyloid. Notably, the cac for Aβ40 is significantly higher, and the fraction of aggregated amyloid is much lower compared to Aβ42, indicating a lower propensity for aggregation. Additionally, our findings suggest that Aβ40 early oligomers are reversible upon dilution, albeit with a kinetic barrier to disaggregation. These insights into the aggregation mechanisms of Aβ40 enhance our understanding of its role in Alzheimer's disease and may inform therapeutic strategies targeting amyloid aggregation.

Cerebrospinal fluid in the differential diagnosis of Alzheimer's disease: an update of the literature

INTRODUCTION

The importance of cerebrospinal fluid (CSF) biomarkers in Alzheimer's disease (AD) diagnosis is rapidly increasing, and there is a growing interest in the use of CSF biomarkers in monitoring the response to therapy, especially in the light of newly available approaches to the therapy of neurodegenerative diseases.

AREAS COVERED

In this review we discuss the most relevant measures of neurodegeneration that are being used to distinguish patients with AD from healthy controls and individuals with mild cognitive impairment, in order to provide an overview of the latest information available in the scientific literature. We focus on markers related to amyloid processing, markers associated with neurofibrillary tangles, neuroinflammation, neuroaxonal injury and degeneration, synaptic loss and dysfunction, and markers of α-synuclein pathology.

EXPERT OPINION

In addition to neuropsychological evaluation, core CSF biomarkers (Aβ42, t-tau, and p-tau181) have been recommended for improvement of timely, accurate and differential diagnosis of AD, as well as to assess the risk and rate of disease progression. In addition to the core CSF biomarkers, various other markers related to synaptic dysfunction, neuroinflammation, and glial activation (neurogranin, SNAP-25, Nfl, YKL-40, TREM2) are now investigated and have yet to be validated for future potential clinical use in AD diagnosis.

Single-Molecule Kinetic Observation of Antibody Interactions with Growing Amyloid β Fibrils

Understanding the dynamic assembly process of amyloid β (Aβ) during fibril formation is essential for developing effective therapeutic strategies against Alzheimer's disease. Here, we employed high-speed atomic force microscopy to observe the growth of Aβ fibrils at the single-molecule level, focusing specifically on their interaction with anti-Aβ antibodies. Our findings show that fibril growth consists of intermittent periods of elongation and pausing, which are dictated by the alternating addition of Aβ monomers to protofilaments. We highlight the distinctive interaction of antibody 4396C, which specifically binds to the fibril ends in the paused state, suggesting a unique mechanism to hinder fibril elongation. Through real-time visualization of fibril growth and antibody interactions combined with molecular simulation, this study provides a refined understanding of Aβ assembly during fibril formation and suggests novel strategies for Alzheimer's therapy aimed at inhibiting the fibril elongation.

Comprehending the Efficacy of Whitlock's Caffeine-Pincered Molecular Tweezer on β-Amyloid Aggregation

Alzheimer's disease (AD) stands as one of the most prevalent neurodegenerative conditions, leading to cognitive impairment, with no cure and preventive measures. Misfolding and aberrant aggregation of amyloid-β (Aβ) peptides are believed to be the underlying cause of AD. These amyloid aggregates culminate in the development of toxic Aβ oligomers and subsequent accumulation of β-amyloid plaques amidst neuronal cells in the brain, marking the hallmarks of AD. Drug development for the potentially curative treatment of Alzheimer's is, therefore, a tremendous challenge for the scientific community. In this study, we investigate the potency of Whitlock's caffeine-armed molecular tweezer in combating the deleterious effects of Aβ aggregation, with special emphasis on the seven residue Aβ16-22 fragment. Extensive all-atom molecular dynamics simulations are conducted to probe the various structural and conformational transitions of the peptides in an aqueous medium in both the presence and absence of tweezers. To explore the specifics of peptide-tweezer interactions, radial distribution functions, contact number calculations, binding free energies, and 2-D kernel density plots depicting the variation of distance-angle between the aromatic planes of the peptide-tweezer pair are computed. The central hydrophobic core, particularly the aromatic Phe residues, is crucial in the development of harmful amyloid oligomers. Notably, all analyses indicate reduced interpeptide interactions in the presence of the tweezer, which is attributed to the tweezer-Phe aromatic interaction. Upon increasing the tweezer concentration, the residues of the peptide are further encased in a hydrophobic environment created by the self-aggregating tweezer cluster, leading to the segregation of the peptide residues. This is further aided by the weakening of interstrand hydrogen bonding between the peptides, thereby impeding their self-aggregation and preventing the formation of neurotoxic β-amyloid. Furthermore, the study also highlights the efficacy of the molecular tweezer in destabilizing preformed amyloid fibrils as well as hindering the aggregation of the full-length Aβ1-42 peptide.

Why Is Arginine the Only Amino Acid That Inhibits Polyglutamine Monomers from Taking on Toxic Conformations?

Polyglutamine (polyQ) diseases are devastating neurodegenerative disorders characterized by abnormal expansion of glutamine repeats within specific proteins. The aggregation of polyQ proteins is a critical pathological hallmark of these diseases. Arginine was identified as a promising inhibitory compound because it prevents polyQ-protein monomers from forming intra- and intermolecular β-sheet structures and hinders polyQ proteins from aggregating to form oligomers. Such an aggregation inhibitory effect was not observed in other amino acids. However, the underlying molecular mechanism of the aggregation inhibition and the factors that differentiate arginine from other amino acids, in terms of the inhibition of the polyQ-protein aggregation, remain poorly understood. Here, we performed replica-permutation molecular dynamics simulations to elucidate the molecular mechanism by which arginine inhibits the formation of the intramolecular β-sheet structure of a polyQ monomer. We found that the intramolecular β-sheet structure with more than four β-bridges of the polyQ monomer with arginine is more unstable than without any ligand and with lysine. We also found that arginine has 1.6-2.1 times more contact with polyQ than lysine. In addition, we revealed that arginine forms more hydrogen bonds with the main chain of the polyQ monomer than lysine. More hydrogen bonds formed between arginine and polyQ inhibit polyQ from forming the long intramolecular β-sheet structure. It is known that intramolecular β-sheet structure enhances intermolecular β-sheet structure between proteins. These effects are thought to be the reason for the inhibition of polyQ aggregation. This study provides insights into the molecular events underlying arginine's inhibition of polyQ-protein aggregation.

Dimerization of Full-Length Aβ-42 Peptide: A Comparison of Different Force Fields and Water Models

Among the two isoforms of amyloid-β i. e., Aβ-40 and Aβ-42, Aβ-42 is more toxic due to its increased aggregation propensity. The oligomerization pathways of amyloid-β may be investigated by studying its dimerization process at an atomic level. Intrinsically disordered proteins (IDPs) lack well-defined structures and are associated with numerous neurodegenerative disorders. Molecular dynamics simulations of these proteins are often limited by the choice of parameters due to inconsistencies in the empirically developed protein force fields and water models. To evaluate the accuracy of recently developed force fields for IDPs, we study the dimerization of full-length Aβ-42 in aqueous solution with three different combinations of AMBER force field parameters and water models such as ff14SB/TIP3P, ff19SB/OPC, and ff19SB/TIP3P using classical MD and Umbrella Sampling method. This work may be used as a benchmark to compare the performance of different force fields for the simulations of IDPs.

Sampling Conformational Ensembles of Highly Dynamic Proteins via Generative Deep Learning

Proteins are inherently dynamic, and their conformational ensembles are functionally important in biology. Large-scale motions may govern protein structure-function relationship, and numerous transient but stable conformations of intrinsically disordered proteins (IDPs) can play a crucial role in biological function. Investigating conformational ensembles to understand regulations and disease-related aggregations of IDPs is challenging both experimentally and computationally. In this paper we first introduced an unsupervised deep learning-based model, termed Internal Coordinate Net (ICoN), which learns the physical principles of conformational changes from molecular dynamics (MD) simulation data. Second, we selected interpolating data points in the learned latent space that rapidly identify novel synthetic conformations with sophisticated and large-scale sidechains and backbone arrangements. Third, with the highly dynamic amyloid-β 1-42 (Aβ42) monomer, our deep learning model provided a comprehensive sampling of Aβ42's conformational landscape. Analysis of these synthetic conformations revealed conformational clusters that can be used to rationalize experimental findings. Additionally, the method can identify novel conformations with important interactions in atomistic details that are not included in the training data. New synthetic conformations showed distinct sidechain rearrangements that are probed by our EPR and amino acid substitution studies. This approach is highly transferable and can be used for any available data for training. The work also demonstrated the ability for deep learning to utilize learned natural atomistic motions in protein conformation sampling.

Sampling Conformational Ensembles of Highly Dynamic Proteins via Generative Deep Learning

Proteins are inherently dynamic, and their conformational ensembles are functionally important in biology. Large-scale motions may govern protein structure-function relationship, and numerous transient but stable conformations of intrinsically disordered proteins (IDPs) can play a crucial role in biological function. Investigating conformational ensembles to understand regulations and disease-related aggregations of IDPs is challenging both experimentally and computationally. In this paper first an unsupervised deep learning-based model, termed Internal Coordinate Net (ICoN), is developed that learns the physical principles of conformational changes from molecular dynamics (MD) simulation data. Second, interpolating data points in the learned latent space are selected that rapidly identify novel synthetic conformations with sophisticated and large-scale sidechains and backbone arrangements. Third, with the highly dynamic amyloid-β1-42 (Aβ42) monomer, our deep learning model provided a comprehensive sampling of Aβ42's conformational landscape. Analysis of these synthetic conformations revealed conformational clusters that can be used to rationalize experimental findings. Additionally, the method can identify novel conformations with important interactions in atomistic details that are not included in the training data. New synthetic conformations showed distinct sidechain rearrangements that are probed by our EPR and amino acid substitution studies. The proposed approach is highly transferable and can be used for any available data for training. The work also demonstrated the ability for deep learning to utilize learned natural atomistic motions in protein conformation sampling.

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.

Numerical and Analytical Simulation of the Growth of Amyloid-β Plaques

Numerical and analytical solutions were employed to calculate the radius of an amyloid-β (Aβ) plaque over time. To the author's knowledge, this study presents the first model simulating the growth of Aβ plaques. Findings indicate that the plaque can attain a diameter of 50 μm after 20 years of growth, provided the Aβ monomer degradation machinery is malfunctioning. A mathematical model incorporates nucleation and autocatalytic growth processes using the Finke-Watzky model. The resulting system of ordinary differential equations was solved numerically, and for the simplified case of infinitely long Aβ monomer half-life, an analytical solution was found. Assuming that Aβ aggregates stick together and using the distance between the plaques as an input parameter of the model, it was possible to calculate the plaque radius from the concentration of Aβ aggregates. This led to the "cube root hypothesis," positing that Aβ plaque size increases proportionally to the cube root of time. This hypothesis helps explain why larger plaques grow more slowly. Furthermore, the obtained results suggest that the plaque size is independent of the kinetic constants governing Aβ plaque agglomeration, indicating that the kinetics of Aβ plaque agglomeration is not a limiting factor for plaque growth. Instead, the plaque growth rate is limited by the rates of Aβ monomer production and degradation.

Exploring Structural Insights of Aβ42 and α-Synuclein Monomers and Heterodimer: A Comparative Study Using Implicit and Explicit Solvent Simulations

Protein misfolding, aggregation, and fibril formation play a central role in the development of severe neurological disorders, including Alzheimer's and Parkinson's diseases. The structural stability of mature fibrils in these diseases is of great importance, as organisms struggle to effectively eliminate amyloid plaques. To address this issue, it is crucial to investigate the early stages of fibril formation when monomers aggregate into small, toxic, and soluble oligomers. However, these structures are inherently disordered, making them challenging to study through experimental approaches. Recently, it has been shown experimentally that amyloid-β 42 (Aβ42) and α-synuclein (α-Syn) can coassemble. This has motivated us to investigate the interaction between their monomers as a first step toward exploring the possibility of forming heterodimeric complexes. In particular, our study involves the utilization of various Amber and CHARMM force-fields, employing both implicit and explicit solvent models in replica exchange and conventional simulation modes. This comprehensive approach allowed us to assess the strengths and weaknesses of these solvent models and force fields in comparison to experimental and theoretical findings, ensuring the highest level of robustness. Our investigations revealed that Aβ42 and α-Syn monomers can indeed form stable heterodimers, and the resulting heterodimeric model exhibits stronger interactions compared to the Aβ42 dimer. The binding of α-Syn to Aβ42 reduces the propensity of Aβ42 to adopt fibril-prone conformations and induces significant changes in its conformational properties. Notably, in AMBER-FB15 and CHARMM36m force fields with the use of explicit solvent, the presence of Aβ42 significantly increases the β-content of α-Syn, consistent with the experiments showing that Aβ42 triggers α-Syn aggregation. Our analysis clearly shows that although the use of implicit solvent resulted in too large compactness of monomeric α-Syn, structural properties of monomeric Aβ42 and the heterodimer were preserved in explicit-solvent simulations. We anticipate that our study sheds light on the interaction between α-Syn and Aβ42 proteins, thus providing the atom-level model required to assess the initial stage of aggregation mechanisms related to Alzheimer's and Parkinson's diseases.

A turn for the worse: Aβ β-hairpins in Alzheimer's disease

Amyloid-β (Aβ) oligomers are a cause of neurodegeneration in Alzheimer's disease (AD). These soluble aggregates of the Aβ peptide have proven difficult to study due to their inherent metastability and heterogeneity. Strategies to isolate and stabilize homogenous Aβ oligomer populations have emerged such as mutations, covalent cross-linking, and protein fusions. These strategies along with molecular dynamics simulations have provided a variety of proposed structures of Aβ oligomers, many of which consist of molecules of Aβ in β-hairpin conformations. β-Hairpins are intramolecular antiparallel β-sheets composed of two β-strands connected by a loop or turn. Three decades of research suggests that Aβ peptides form several different β-hairpin conformations, some of which are building blocks of toxic Aβ oligomers. The insights from these studies are currently being used to design anti-Aβ antibodies and vaccines to treat AD. Research suggests that antibody therapies designed to target oligomeric Aβ may be more successful at treating AD than antibodies designed to target linear epitopes of Aβ or fibrillar Aβ. Aβ β-hairpins are good epitopes to use in antibody development to selectively target oligomeric Aβ. This review summarizes the research on β-hairpins in Aβ peptides and discusses the relevance of this conformation in AD pathogenesis and drug development.

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.

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

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

Identification of Molecular Correlations of GSDMD with Pyroptosis inAlzheimer's Disease

AIM

An analysis of bioinformatics and cell experiments was performed to verify the relationship between gasdermin D (GSDMD), an executive protein of pyroptosis, and Alzheimer's disease (AD).

METHODS

The training set GSE33000 was utilized to identify differentially expressed genes (DEGs) in both the AD group and control group, as well as in the GSDMD protein high/low expression group. Subsequently, the weighted gene co-expression network analysis (WGCNA) and the least absolute shrinkage and selection operator (LASSO) regression analysis were conducted, followed by the selection of the key genes for the subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. The association between GSDMD and AD was assessed and confirmed in the training set GSE33000, as well as in the validation sets GSE5281 and GSE48350. Immunofluorescence (IF) was employed to detect the myelin basic protein (MBP), a distinctive protein found in the rat oligodendrocytes (OLN-93 cells). A range of concentrations (1-15 μmol/L) of β-amyloid 1-42 (Aβ1-42) were exposed to the cells, and the subsequent observations were made regarding cell morphology. Additionally, the assessments were conducted to evaluate the cell viability, the lactate dehydrogenase (LDH) release, the cell membrane permeability, and the GSDMD protein expression.

RESULTS

A total of 7,492 DEGs were screened using GSE33000. Subsequently, WGCNA analysis identified 19 genes that exhibited the strongest correlation with clinical traits in AD. Additionally, LASSO regression analysis identified 13 key genes, including GSDMD, AFF1, and ATOH8. Furthermore, the investigation revealed that the key genes were associated with cellular inflammation based on GO and KEGG analyses. Moreover, the area under the curve (AUC) values for the key genes in the training and validation sets were determined to be 0.95 and 0.70, respectively. Significantly, GSDMD demonstrated elevated levels of expression in AD across both datasets. The positivity of MBP expression in cells exceeded 95%. As the concentration of Aβ1-42 action gradually escalated, the detrimental effects on cells progressively intensified, resulting in a gradual decline in cell survival rate, accompanied by an increase in lactate dehydrogenase release, cell membrane permeability, and GSDMD protein expression.

CONCLUSION

The association between GSDMD and AD has been observed, and it has been found that Aβ1-42 can induce a significant upregulation of GSDMD in OLN-93 cells. This suggests that Aβ1-42 has the potential to induce cellular pyroptosis and can serve as a valuable cellular pyroptosis model for the study of AD.

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.

Programming co-assembled peptide nanofiber morphology via anionic amino acid type: Insights from molecular dynamics simulations

Co-assembling peptides can be crafted into supramolecular biomaterials for use in biotechnological applications, such as cell culture scaffolds, drug delivery, biosensors, and tissue engineering. Peptide co-assembly refers to the spontaneous organization of two different peptides into a supramolecular architecture. Here we use molecular dynamics simulations to quantify the effect of anionic amino acid type on co-assembly dynamics and nanofiber structure in binary CATCH(+/-) peptide systems. CATCH peptide sequences follow a general pattern: CQCFCFCFCQC, where all C's are either a positively charged or a negatively charged amino acid. Specifically, we investigate the effect of substituting aspartic acid residues for the glutamic acid residues in the established CATCH(6E-) molecule, while keeping CATCH(6K+) unchanged. Our results show that structures consisting of CATCH(6K+) and CATCH(6D-) form flatter β-sheets, have stronger interactions between charged residues on opposing β-sheet faces, and have slower co-assembly kinetics than structures consisting of CATCH(6K+) and CATCH(6E-). Knowledge of the effect of sidechain type on assembly dynamics and fibrillar structure can help guide the development of advanced biomaterials and grant insight into sequence-to-structure relationships.

Dissociation process of polyalanine aggregates by free electron laser irradiation

Polyalanine (polyA) disease-causative proteins with an expansion of alanine repeats can be aggregated. Although curative treatments for polyA diseases have not been explored, the dissociation of polyA aggregates likely reduces the cytotoxicity of polyA. Mid-infrared free electron laser (FEL) successfully dissociated multiple aggregates. However, whether the FEL dissociates polyA aggregates like other aggregates has not been tested. Here, we show that FEL at 6.1 μm experimentally weakened the extent of aggregation of a peptide with 13 alanine repeats (13A), and the irradiated 13A exerted lesser cytotoxicity to neuron-like cells than non-irradiated 13A. Then, we applied molecular dynamics (MD) simulation to follow the dissociation process by FEL. We successfully observed how the intermolecular β-sheet of polyA aggregates was dissociated and separated into monomers with helix structures upon FEL irradiation. After the dissociation by FEL, water molecules inhibited the reformation of polyA aggregates. We recently verified the same dissociation process using FEL-treated amyloid-β aggregates. Thus, a common mechanism underlies the dissociation of different protein aggregates that cause different diseases, polyA disease and Alzheimer's disease. However, MD simulation indicated that polyA aggregates are less easily dissociated than amyloid-β aggregates and require longer laser irradiation due to hydrophobic alanine repeats.

Sugar distributions on gangliosides guide the formation and stability of amyloid-β oligomers

Aggregation of Aβ peptides is a key contributor to the etiology of Alzheimer's disease. Being intrinsically disordered, monomeric Aβ is susceptible to conformational excursions, especially in the presence of important interacting partners such as membrane lipids, to adopt specific aggregation pathways. Furthermore, components such as gangliosides in membranes and lipid rafts are known to play important roles in the adoption of pathways and the generation of discrete neurotoxic oligomers. Yet, what roles do carbohydrates on gangliosides play in this process remains unknown. Here, using GM1, GM3, and GD3 ganglioside micelles as models, we show that the sugar distributions and cationic amino acids within Aβ N-terminal region modulate oligomerization of Aβ temporally, and dictate the stability and maturation of oligomers. These results demonstrate the selectivity of sugar distributions on the membrane surface toward oligomerization of Aβ and thus implicate cell-selective enrichment of oligomers.

SEVI Inhibits Aβ Amyloid Aggregation by Capping the β-Sheet Elongation Edges

Inhibiting the aggregation of amyloid peptides with endogenous peptides has broad interest due to their intrinsically high biocompatibility and low immunogenicity. Here, we investigated the inhibition mechanism of the prostatic acidic phosphatase fragment SEVI (semen-derived enhancer of viral infection) against Aβ42 fibrillization using atomistic discrete molecular dynamic simulations. Our result revealed that SEVI was intrinsically disordered with dynamic formation of residual helices. With a high positive net charge, the self-aggregation tendency of SEVI was weak. Aβ42 had a strong aggregation propensity by readily self-assembling into β-sheet-rich aggregates. SEVI preferred to interact with Aβ42, rather than SEVI themselves. In the heteroaggregates, Aβ42 mainly adopted β-sheets buried inside and capped by SEVI in the outer layer. SEVI could bind to various Aβ aggregation species─including monomers, dimers, and proto-fibrils─by capping the exposed β-sheet elongation edges. The aggregation processes Aβ42 from the formation of oligomers to conformational nucleation into fibrils and fibril growth should be inhibited as their β-sheet elongation edges are being occupied by the highly charged SEVI. Overall, our computational study uncovered the molecular mechanism of experimentally observed inhibition of SEVI against Aβ42 aggregation, providing novel insights into the development of therapeutic strategies against Alzheimer's disease.

Inhibition Effect and Molecular Mechanisms of Quercetin on the Aβ42 Dimer: A Molecular Dynamics Simulation Study

Amyloid-β (Aβ) dimer as the smallest oligomer has recently been drawing attention due to its neurotoxicity, transient nature, and heterogeneity. The inhibition of Aβ dimer's aggregation is the key to primary intervention of Alzheimer's disease. Previous experimental studies have reported that quercetin, the widespread polyphenolic constituent of multiple fruits and vegetables, can hamper the formation of Aβ protofibrils and disaggregate Aβ fibrils. However, the molecular mechanisms of quercetin in the suppression of the Aβ(1-42) dimer's conformational changes still remain elusive. In this work, to investigate the inhibitory mechanisms of quercetin molecules on the Aβ(1-42) dimer, an Aβ(1-42) dimer based on monomeric the Aβ(1-42) peptide with enriched coil structures is constructed. The early molecular mechanisms of quercetin molecules on inhibiting the Aβ(1-42) dimer at two different Aβ42-to-quercetin molar ratios (1:5 and 1:10) are explored via all-atom molecular dynamics simulations. The results indicate that quercetin molecules can impede the configurational change of the Aβ(1-42) dimer. The interactions and the binding affinity between the Aβ(1-42) dimer and quercetin molecules in the Aβ42 dimer + 20 quercetin system are stronger in comparison with that in the Aβ42 dimer + 10 quercetin system. Our work may be helpful in developing new drug candidates for preventing the conformational transition and further aggregation of the Aβ dimer.

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

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

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.