The truncated Aβ1 - 16 peptide containing the metal-binding domain is frequently used in in silico and experimental investigations because it is more soluble and thus more suitable for studies in solution and does not form amyloids. Several spectroscopic studies have shown that the metal binding of Aβ1 - 16 is very similar to that of the full-length Aβ1 - 42. However, since small changes can have a significant impact on aggregation, further experimental and theoretical are needed to elucidate the detailed structures of truncated and full-length Aβ. In this research, the binding of copper ion to the Aβ1 - 16 and Aβ1 - 42 has been studied by molecular dynamics simulation method. To investigate the effect of copper ion on beta-amyloid peptide structure, the simulations were repeated in the copper and zinc ions, copper and iron binary system, and the copper, zinc and iron ions ternary system. The conformation factor was calculated to calculate the binding affinity of copper ion to beta-amyloid peptide residues. The results showed that the initial 16 residues of the beta-amyloid peptide have high binding affinity for copper ions, and histidine 13 and histidine 14 have significantly higher binding affinity for copper ions in all studied systems. Zinc and iron ions were found to reduce the conformational factor of peptide residues in binding to copper ions, and the aggregation tendency was lower in the truncated structure. The SASA results suggest that the side chains of peptide residues are more affected by shortening and the presence of ions.

Intrinsically Disordered Proteins (IDPs) challenge traditional structure-function paradigms by existing as dynamic ensembles rather than stable tertiary structures. Capturing these ensembles is critical to understanding their biological roles, yet Molecular Dynamics (MD) simulations, though accurate and widely used, are computationally expensive and struggle to sample rare, transient states. Artificial intelligence (AI) offers a transformative alternative, with deep learning (DL) enabling efficient and scalable conformational sampling. They leverage large-scale datasets to learn complex, non-linear, sequence-to-structure relationships, allowing for the modeling of conformational ensembles in IDPs without the constraints of traditional physics-based approaches. Such DL approaches have been shown to outperform MD in generating diverse ensembles with comparable accuracy. Most models rely primarily on simulated data for training and experimental data serves a critical role in validation, aligning the generated conformational ensembles with observable physical and biochemical properties. However, challenges remain, including dependence on data quality, limited interpretability, and scalability for larger proteins. Hybrid approaches combining AI and MD can bridge the gaps by integrating statistical learning with thermodynamic feasibility. Future directions include incorporating physics-based constraints and learning experimental observables into DL frameworks to refine predictions and enhance applicability. AI-driven methods hold significant promise in IDP research, offering novel insights into protein dynamics and therapeutic targeting while overcoming the limitations of traditional MD simulations.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by a gradual decline in cognitive function, memory impairment, and alterations in behavior. As the predominant etiology of dementia, AD affects millions of individuals worldwide, with its hallmark pathological feature being the accumulation of amyloid beta (Aβ) plaques, which disrupt neuronal function and progressively compromise brain structure. Early clinical manifestations often include forgetfulness, disorientation, and social withdrawal. Primarily impacting the elderly population, AD significantly impairs daily functioning and diminishes overall quality of life. Current therapeutic approaches for AD mainly focus on symptomatic relief and decelerating the disease's progression. Cholinesterase inhibitors, such as donepezil and rivastigmine, increase acetylcholine (ACh) levels to enhance cognitive function in individuals with mild to moderate AD. For individuals in more advanced stages of the disease, NMDA receptor antagonists modulate glutamate activity to mitigate excitotoxicity. In addition to pharmacological interventions, lifestyle modifications such as adherence to a balanced diet, regular physical activity, and cognitive engagement are advocated to support brain health. Novel therapeutic avenues are being explored to address underlying pathophysiological mechanisms, such as metal ion dysregulation within the brain. Furthermore, non-pharmacological approaches, including cognitive-behavioral therapy and patient support groups, provide essential behavioral and emotional support. Cutting-edge research continues to investigate innovative treatments, such as immunotherapies targeting amyloid plaques and tau tangles and neuroprotective compounds derived from natural sources. The goal of these multifaceted strategies is to alleviate symptoms, enhance quality of life, and offer hope for individuals and families affected by AD. This review provides a comprehensive summary of both established and emerging therapeutic interventions for the management of AD.

Physics-informed machine learning bridges the gap between the high fidelity of mechanistic models and the adaptive insights of artificial intelligence. In chemical reaction network modeling, this synergy proves valuable, addressing the high computational costs of detailed mechanistic models while leveraging the predictive power of machine learning. This study applies this fusion to the biomedical challenge of Aβ fibril aggregation, a key factor in Alzheimer's disease. Central to the research is the introduction of an automatic reaction order model reduction framework, designed to optimize reduced-order kinetic models. This framework represents a shift in model construction, automatically determining the appropriate level of detail for reaction network modeling. The proposed approach significantly improves simulation efficiency and accuracy, particularly in systems like Aβ aggregation, where precise modeling of nucleation and growth kinetics can reveal potential therapeutic targets. Additionally, the automatic model reduction technique has the potential to generalize to other network models. The methodology offers a scalable and adaptable tool for applications beyond biomedical research. Its ability to dynamically adjust model complexity based on system-specific needs ensures that models remain both computationally feasible and scientifically relevant, accommodating new data and evolving understandings of complex phenomena.

Toxic oligomeric species are suspected in the etiology of Alzheimer's disease. The full-length Aβ42 can be studied by the fragment Aβ25-35 as it retains neurotoxicity. According to experimental studies, amidation of the Aβ25-35 carboxyl terminal decreases fibrillation activity while retaining its neurotoxic properties. Our molecular dynamics simulation studied the aggregation of the Aβ25-35 trimer from two initial structures (fibril and randomized helical structures) in their amidated and nonamidated forms. Comparing the amidated and nonamidated systems, the results suggest that antiparallel chains are dominant in nonamidated systems, while the amide group leads to parallel chains. In terms of secondary structures, a higher helix content with a corresponding decrease in β-sheet content is observed as a consequence of amidation. Despite the variation in secondary structures, the chain-chain contacts are still mediated by the Gly motif (GxxxG) and Ile residues in both amidated and nonamidated systems. As neurotoxicity does not change upon amidation, our results imply that clumping of peptides sustained by the Gly motif is a greater contributing factor to toxicity than secondary and quaternary structures.

The amyloid hypothesis is the predominant model of Alzheimer's disease (AD) pathogenesis, suggesting that amyloid beta (Aβ) peptide is the primary driver of neurotoxicity and a cascade of pathological events in the central nervous system. Aβ aggregation into oligomers and deposits triggers various processes, such as vascular damage, inflammation-induced astrocyte and microglia activation, disrupted neuronal ionic homeostasis, oxidative stress, abnormal kinase and phosphatase activity, tau phosphorylation, neurofibrillary tangle formation, cognitive dysfunction, synaptic loss, cell death, and, ultimately, dementia. Molecular dynamics (MD) is a powerful structure-based drug design (SBDD) approach that aids in understanding the properties, functions, and mechanisms of action or inhibition of biomolecules. As the only method capable of simulating atomic-level internal motions, MD provides unique insights that cannot be obtained through other techniques. Integrating experimental data with MD simulations allows for a more comprehensive understanding of biological processes and molecular interactions. This review summarizes and evaluates MD studies from the past decade on small molecules, including endogenous compounds and repurposed drugs, that inhibit amyloid beta. Furthermore, it outlines key considerations for future MD simulations of amyloid inhibitors, offering a potential framework for studies aimed at elucidating the mechanisms of amyloid beta inhibition by small molecules.

Intrinsically disordered proteins (IDPs) are implicated in many human diseases and are increasingly being pursued as drug targets. Conventional structure-based drug design methods that rely on well-defined binding sites are however, largely unsuitable for IDPs. Here, we present computationally efficient ensemble docking approaches to predict the relative affinities of small molecules to IDPs and characterize their dynamic, heterogenous binding mechanisms at atomic resolution. We demonstrate that these ensemble docking protocols accurately predict the relative binding affinities of small molecule α-synuclein ligands measured by NMR spectroscopy and generate conformational ensembles of ligand binding modes in remarkable agreement with experimentally validated long-timescale molecular dynamics simulations. Our results display the potential of ensemble docking approaches for predicting small molecule binding to IDPs and suggest that these methods may be valuable tools for IDP drug discovery campaigns.

Alzheimer's disease, the leading cause of dementia globally, represents an unresolved clinical challenge due to its complex pathogenesis and the absence of effective treatments. Considering the multifactorial etiology of the disease, mainly characterized by the accumulation of amyloid β plaques and neurofibrillary tangles of tau protein, we discuss the A673V mutation in the gene coding for the amyloid precursor protein, which is associated with the familial form of Alzheimer's disease in a homozygous state. The mutation offers new insights into the molecular mechanisms of the disease, particularly regarding the contrasting roles of the A2V and A2T mutations in amyloid β peptide aggregation and toxicity. This review aims to describe relevant studies on A2V-mutated variants of the amyloid β peptide, revealing a protective effect against amyloid-β and tau pathology. Notably, special attention is given to the development of the peptide Aβ1-6A2V(D), which shows significant neuroprotective activity through inhibition of the assembly of amyloid β into amyloid fibrils. The therapeutic potential of this peptide emerges from its ability to reduce amyloid β-induced toxicity, with promising results from studies in human neuroblastoma cells and transgenic animal models.

The driving mechanisms at the base of the clearance of biological wastes in the brain interstitial space (ISS) are still poorly understood and an actively debated subject. A complete comprehension of the processes that lead to the aggregation of amyloid proteins in such environment, hallmark of the onset and progression of Alzheimer's disease, is of crucial relevance. Here we employ combined computational fluid dynamics and molecular dynamics techniques to uncover the role of fluid flow and proteins transport in the brain ISS. Our work identifies diffusion as the principal mechanism for amyloid-β proteins clearance, whereas fluid advection may lead transport for larger molecular bodies, like amyloid-β aggregates or extracellular vesicles. We also clearly quantify the impact of large nascent prefibrils on the fluid flowing and shearing. Finally, we show that, even in the irregular brain interstitial space (ISS), hydrodynamic interactions enhance amyloid-β aggregation at all stages of the aggregation pathway. Our results are key to understand the role of fluid flow and solvent-solute interplay on therapeutics like antibodies acting in the brain ISS.

Acetylcholinesterase (AChE) is one of the most successful targets for the treatment of Alzheimer's disease (AD). Inhibition of AChE can result in preventing AD. In this context, the machine-learning (ML) model, molecular docking, and molecular dynamics calculations were employed to characterize the potential inhibitors for AChE from MedChemExpress (MCE) database. The trained ML model was initially employed for estimating the inhibitory of MCE compounds. Atomistic simulations including molecular docking and molecular dynamics simulations were then used to confirm ML outcomes. In particular, the physical insights into the ligand binding to AChE were clarified over the calculations. Two compounds, PubChem ID of 130467298 and 132020434, were indicated that they can inhibit AChE.

The review deals with the application of Molecular Dynamics (MD) to the structure modeling of beta-amyloids (Aβ), currently classified as intrinsically disordered proteins (IDPs). In this review, we strive to relate the main advances in this area but specifically focus on the approaches and methodology. All relevant papers on the Aβ modeling are cited in the Tables in Supplementary Data, including a concise description of the applied approaches, sorted according to the types of the studied systems: modeling of the monomeric Aβ and Aβ aggregates. Similar sections focused according to the type of modeled object are present in the review. In the final part of the review, novel methods of general IDP modeling not confined to Aβ are described.

The online version contains supplementary material available at 10.1007/s12551-024-01253-y.

Protein misfolding is a widespread phenomenon that can result in the formation of protein aggregates, which are markers of various disease states, including Alzheimer's disease (AD). In AD, amyloid beta (Aβ) peptides are key players in the disease's progression, particularly the 40- and 42- residue variants, Aβ40 and Aβ42. These peptides aggregate to form amyloid plaques and contribute to neuronal toxicity. Recent research has shifted attention from solely Aβ fibrils to also include Aβ protofibrils and oligomers as potentially critical pathogenic agents. Particularly, oligomers demonstrate more significant toxicity compared to other Aβ specie. Hence, there is an increased interest in studying the correlation between toxicity and their structure and aggregation pathway. The present study investigates the aggregation of a 150 kDa Aβ42 oligomer that does not lead to fibril formation. Using negative stain transmission electron microscopy (TEM), size exclusion chromatography (SEC), dynamic light scattering (DLS), and cryo-electron microscopy (cryo-EM), we demonstrate that 150 kDa Aβ42 oligomers form higher-order string-like assemblies over time. These strings are unique from the classical Aβ fibrils. The significance of our work lies in elucidating molecular behavior of a novel non-fibrillar form of Aβ42 aggregate.

Advances in Alzheimer's disease (AD) are related to the oligomerization of Amyloid β (Aβ) peptides. Therefore, alteration of the process can prevent AD. We investigated the Aβ42 dimerization under the effects of gold nanoparticles using temperature replica-exchange molecular dynamics (REMD) simulations. The structural change of dimers in the presence and absence of the gold nanoparticle, Au55, was monitored over stable intervals. Physical insights into the oligomerization of Aβ were thus clarified. The computed metrics indicate that Au55 affects the progress of oligomerization. Specifically, the presence of the gold nanoparticle significantly modifies the structure of dimeric Aβ42. The β-content experienced a substantial decrease with the induction of Au55. The turn and coil-contents are also decreased under the effects of the gold nanoparticle. However, the α-content of the dimer exhibited a rigid increase. The influence of gold nanoparticles on the dimeric Aβ42 differs significantly from that of silver nanoparticles, which reduce β-content but increase coil-, turn-, and α-contents. The nature of inhibition will be discussed, in which the vdW interaction plays a driving force for the interaction between the Aβ42 dimer and the gold nanoparticle.

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.

Aberrant aggregation of amyloid-β (Aβ) and islet amyloid polypeptide (IAPP) into amyloid fibrils underlies the pathogenesis of Alzheimer's disease (AD) and type 2 diabetes (T2D), respectively. T2D significantly increases AD risk, with evidence suggesting that IAPP and Aβ co-aggregation and cross-seeding might contribute to the cross-talk between two diseases. Experimentally, preformed IAPP fibril seeds can accelerate Aβ aggregation, though the cross-seeding mechanism remains elusive. Here, we computationally demonstrated that Aβ monomer preferred to bind to the elongation ends of preformed IAPP fibrils. However, due to sequence mismatch, the Aβ monomer could not directly grow onto IAPP fibrils by forming multiple stable β-sheets with the exposed IAPP peptides. Conversely, in our control simulations of self-seeding, the Aβ monomer could axially grow on the Aβ fibril, forming parallel in-register β-sheets. Additionally, we showed that the IAPP fibril could catalyze Aβ fibril nucleation by promoting the formation of parallel in-register β-sheets in the C-terminus between bound Aβ peptides. This study enhances our understanding of the molecular interplay between Aβ and IAPP, shedding light on the cross-seeding mechanisms potentially linking T2D and AD. Our findings also underscore the importance of clearing IAPP deposits in T2D patients to mitigate AD risk.

The accumulation of amyloid-beta (Aβ) oligomers is recognized as a potential culprit in Alzheimer's disease (AD). Experimental studies show that melatonin, a hormone that mainly regulates circadian rhythm and sleep, can interact with Aβ peptides and disrupt the formation of oligomers. However, how melatonin inhibits the oligomerization of soluble Aβ is unclear. Here, by computational simulations, we investigate the effect of different levels of melatonin on the conformation of the Aβ42 dimer. We find that the conformation of the Aβ42 dimer is dependent on melatonin levels. When melatonin is absent, the dimer mainly forms a parallel β-sheet in the CHC region. When one melatonin molecule is present, the overall conformation of the dimer does not change much, but the N-terminal of the dimer tends to adopt antiparallel β-sheets. When two melatoinin molecules are present, the Aβ42 dimer exhibits significant structural change, especially in its central region, resulting in a more compact conformation, and forms parallel β-sheets in the C-terminal. This conformational difference induced by different levels of melatoinin can shed light on the protective role of melatonin.

Targeting acetylcholinesterase is one of the most important strategies for developing therapeutics against Alzheimer's disease. In this work, we have employed a new approach that combines machine learning models, a multi-step similarity search of the PubChem library and molecular dynamics simulations to investigate potential inhibitors for acetylcholinesterase. Our search strategy has been shown to significantly enrich the set of compounds with strong predicted binding affinity to acetylcholinesterase. Both machine learning prediction and binding free energy calculation, based on linear interaction energy, suggest that the compound CID54414454 would bind strongly to acetylcholinesterase and hence is a promising inhibitor.

Pathological aggregation of α-synuclein (α-syn) into amyloid fibrils is a major feature of Parkinson's disease (PD). The self-assembly of α-syn is mainly governed by a non-amyloid-β component core (NACore). However, the effects of concentrations and temperatures on their conformational transition remain unclear. To answer this question, we investigated the aggregation kinetics of NACore oligomers in silico by performing several independent all-atom molecular dynamics simulations. The simulation results show that tetramers are more prone to form β-sheets at 300 K than dimers and octamers. We also found that the NACore oligomers had higher β-sheet and β-barrel contents at 310 K. The inter-chain hydrophobic interactions, the backbone hydrogen bonding, the residue-residue interactions between V70-V77 as well as V77-V77 play important roles in the aggregation tendency of NACore octamers at 310 K. Interestingly, the energy gap analysis revealed that the conformational transition of NACore oligomers from intermediate states (β-barrel conformation) to stable structures (β-sheet layers) was dependent on the temperatures. In short, our study provides insight into the kinetic and thermodynamic mechanisms of the conformational transition of NACore at different concentrations and temperatures, contributing to a better understanding of the aggregation process of α-syn in Parkinson's disease.

The histidine behavior plays a crucial role in the structural and aggregation properties of protein folding and misfolding. Understanding the histidine behavior at the edge of the protein structure is critical for finding ways to disrupt fibril elongation and growth, but this impact remains poorly understood. In the current study, we used molecular dynamics simulations to investigate the edge substitution effect of histidine protonation on the structural and aggregation properties. Our data showed that ΔG1 contributed the most to binding affinity compared to ΔG2 and ΔG3. The different protonation states at the edge chain significantly impacted the secondary structure properties of the edge chain. Specifically, we found that such protonation behavior significantly affected specific regions, particularly the N-terminus (G9-Q15) and C-terminus (K28-A30). Further analysis confirmed that H6, H13, and H14 were directly involved in H-bonding networks with the C1_H14//C2_H13 interchain interactions critical for maintaining the interchain stability. Furthermore, we confirmed that H6, H13, and H14 were directly involved in the loss of the carbon skeleton contact in the N-terminus. Our findings indicate that the edge condition is more susceptible to changes in structural properties than the middle condition. The current study is helpful for understanding the histidine behavior hypothesis in related misfolding diseases.

Protein misfolding is a widespread phenomenon that can result in the formation of protein aggregates, which are markers of various disease states, including Alzheimer's disease (AD). In AD, amyloid beta (Aβ) peptides, particularly Aβ40 and Aβ42, are key players in the disease's progression, as they aggregate to form amyloid plaques and contribute to neuronal toxicity. Recent research has shifted attention from solely Aβ fibrils to also include Aβ protofibrils and oligomers as potentially critical pathogenic agents. Particularly, oligomers demonstrate greater toxicity compared to other Aβ specie. Hence, there is an increased interest in studying the correlation between toxicity and their structure and aggregation pathway. The present study investigates the aggregation of a 150 kDa Aβ42 oligomer that does not lead to fibril formation over time. Using negative stain transmission electron microscopy (TEM), size exclusion chromatography (SEC), dynamic light scattering (DLS), and cryo-electron microscopy (cryo-EM), we demonstrate that 150 kDa Aβ42 oligomers form higher-order string-like assemblies over time. The strings are unique from the classical Aβ fibril structures. The significance of our work lies in elucidating molecular behavior of a novel non-fibrillar form of Aβ42 aggregate.

Alzheimer's disease (AD) is an age-related neurodegenerative disease with amyloid-β (Aβ) deposition as the main pathological feature. It's an important challenge to find new ways to clear Aβ from the brain. The soluble amyloid precursor protein α (sAPPα) is a neuroprotective protein and can attenuate neuronal damage, including toxic Aβ. However, the regulatory role of sAPPα in non-neuronal cells, such as microglia, is less reported and controversial. Here, we showed that sAPPα promoted the phagocytosis and degradation of Aβ in both normal and damaged microglia. Moreover, the function of damaged microglia was improved by the sAPPα through normalizing mitochondrial function. Furthermore, the results of molecular docking simulation showed that sAPPα had a good affinity with Aβ. We preliminarily reveal that sAPPα is similar to antibodies and can participate in the regulation of microglia phagocytosis and degradation of Aβ after binding to Aβ. sAPPα is expected to be a mild and safe peptide drug or drug carrier for AD.

The coexistence of amyloid-β (Aβ) and human islet amyloid polypeptide (hIAPP) in the brain and pancreas is associated with an increased risk of Alzheimer's disease (AD) and type 2 diabetes (T2D) due to their coaggregation and cross-seeding. Despite this, the molecular mechanisms underlying their interaction remain elusive. Here, we systematically investigated the cross-talk between Aβ and hIAPP using atomistic discrete molecular dynamics (DMD) simulations. Our results revealed that the amyloidogenic core regions of both Aβ (Aβ10-21 and Aβ30-41) and hIAPP (hIAPP8-20 and hIAPP22-29), driving their self-aggregation, also exhibited a strong tendency for cross-interaction. This propensity led to the formation of β-sheet-rich heterocomplexes, including potentially toxic β-barrel oligomers. The formation of Aβ and hIAPP heteroaggregates did not impede the recruitment of additional peptides to grow into larger aggregates. Our cross-seeding simulations demonstrated that both Aβ and hIAPP fibrils could mutually act as seeds, assisting each other's monomers in converting into β-sheets at the exposed fibril elongation ends. The amyloidogenic core regions of Aβ and hIAPP, in both oligomeric and fibrillar states, exhibited the ability to recruit isolated peptides, thereby extending the β-sheet edges, with limited sensitivity to the amino acid sequence. These findings suggest that targeting these regions by capping them with amyloid-resistant peptide drugs may hold potential as a therapeutic approach for addressing AD, T2D, and their copathologies.

Microscopy imaging has enabled us to establish the presence of fibrin(ogen) amyloid (fibrinaloid) microclots in a range of chronic, inflammatory diseases. Microclots may also be induced by a variety of purified substances, often at very low concentrations. These molecules include bacterial inflammagens, serum amyloid A, and the S1 spike protein of severe acute respiratory syndrome coronavirus 2. Here, we explore which of the properties of these microclots might be used to contribute to differential clinical diagnoses and prognoses of the various diseases with which they may be associated. Such properties include distributions in their size and number before and after the addition of exogenous thrombin, their spectral properties, the diameter of the fibers of which they are made, their resistance to proteolysis by various proteases, their cross-seeding ability, and the concentration dependence of their ability to bind small molecules including fluorogenic amyloid stains. Measuring these microclot parameters, together with microscopy imaging itself, along with methodologies like proteomics and imaging flow cytometry, as well as more conventional assays such as those for cytokines, might open up the possibility of a much finer use of these microclot properties in generative methods for a future where personalized medicine will be standard procedures in all clotting pathology disease diagnoses.

The influence of metal ions on the structure of amyloid- β (Aβ) protofibril models was studied through molecular dynamics to explore the molecular mechanisms underlying metal-induced Aβ aggregation relevant in Alzheimer's disease (AD). The models included 36-, 48-, and 188-mers of the Aβ42 sequence and two disease-modifying variants. Primary structural effects were observed at the N-terminal domain, as it became susceptible to the presence of cations. Specially when β-sheets predominate, this motif orients N-terminal acidic residues toward one single face of the β-sheet, resulting in the formation of an acidic region that attracts cations from the media and promotes the folding of the N-terminal region, with implications in amyloid aggregation. The molecular phenotype of the protofibril models based on Aβ variants shows that the AD-causative D7N mutation promotes the formation of N-terminal β-sheets and accumulates more Zn2+, in contrast to the non-amyloidogenic rodent sequence that hinders the β-sheets and is more selective for Na+ over Zn2+ cations. It is proposed that forming an acidic β-sheet domain and accumulating cations is a plausible molecular mechanism connecting the elevated affinity and concentration of metals in Aβ fibrils to their high content of β-sheet structure at the N-terminal sequence.

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.

Several studies have shown an inverse correlation between the likelihood of developing a neurodegenerative disorder and cancer. We previously reported that the levels of amyloid beta (Aβ), at the center of Alzheimer's disease pathophysiology, are regulated by acetylcholinesterase (AChE) in non-small cell lung cancer (NSCLC). Here, we examined the effect of Aβ or its fragments on the levels of ACh in A549 (p53 wild-type) and H1299 (p53-null) NSCLC cell media. ACh levels were reduced by cell treatment with Aβ 1-42, Aβ 1-40, Aβ 1-28, and Aβ 25-35. AChE and p53 activities increased upon A549 cell treatment with Aβ, while knockdown of p53 in A549 cells increased ACh levels, decreased AChE activity, and diminished the Aβ effects. Aβ increased the ratio of phospho/total p38 MAPK and decreased the activity of PKC. Inhibiting p38 MAPK reduced the activity of p53 in A549 cells and increased ACh levels in the media of both cell lines, while opposite effects were found upon inhibiting PKC. ACh decreased the activity of p53 in A549 cells, decreased p38 MAPK activity, increased PKC activity, and diminished the effect of Aβ on those activities. Moreover, the negative effect of Aβ on cell viability was diminished by cell co-treatment with ACh.

The aggregation of amyloid beta (Aβ) peptides is associated with the development of Alzheimer's disease (AD). However, there has been a growing belief that the oligomerization of Aβ species in different environments has a neurotoxic effect on the patient's brain, causing damage. It is necessary to comprehend the compositions of Aβ oligomers in order to develop medications that may effectively inhibit these neurotoxic forms that affect the nervous system of AD patients. Thus, dissociation or inhibition of Aβ aggregation may be able to prevent AD. To date, the search for traditional agents and biomolecules has largely been unsuccessful. In this context, nanoparticles have emerged as potential candidates to directly inhibit the formation of Aβ oligomers. The oligomerization of the dimeric Aβ peptides with or without the influence of a silver nanoparticle was thus investigated using temperature replica-exchange molecular dynamics (REMD) simulations. The physical insights into the dimeric Aβ oligomerization were clarified by analyzing intermolecular contact maps, the free energy landscape of the dimeric oligomer, secondary structure terms, etc. The difference in obtained metrics between Aβ with or without a silver nanoparticle provides a picture of the influence of silver nanoparticles on the oligomerization process. The underlying mechanisms that are involved in altering Aβ oligomerization will be discussed. The obtained results may play an important role in searching for Aβ inhibitor pathways.

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.

DeepKa is a deep-learning-based protein pKa predictor proposed in our previous work. In this study, a web server was developed that enables online protein pKa prediction driven by DeepKa. The web server provides a user-friendly interface where a single step of entering a valid PDB code or uploading a PDB format file is required to submit a job. Two case studies have been attached in order to explain how pKa's calculated by the web server could be utilized by users. Finally, combining the web server with post processing as described in case studies, this work suggests a quick workflow of investigating the relationship between protein structure and function that are pH dependent. The web server of DeepKa is freely available at http://www.computbiophys.com/DeepKa/main.

Fibril formation from alpha-synuclein is a key point in Parkinson's disease, multiple system atrophy, and other synucleinopathies. The mechanism of the amyloid-like conversion followed by the formation of pre-fibrillar soluble oligomers and fibrils is not completely clear; furthermore, it is unclear how the Parkinson's disease-related point mutations located in the pre-NAC region enhance fibrillation. In the present paper, atomistic replica exchange molecular dynamics simulations of the full-length alpha-synuclein and its two mutants, A53T and E46K, elucidated amyloid conversion intermediates. Both mutants demonstrated an enhanced tendency for the conversion but in different manners; the main intermediate conformations populated in the WT alpha-synuclein conformational ensemble disappeared due to mutations, indicating a different conversion pathway. Analysis of the preferable beta-hairpin positions and intermediate conformations seems to reflect a tendency to form a particular amyloid fibril polymorph. A strong elevation of amyloid transformation level was shown also for Ser129-phosphorylated alpha-synuclein. Altered intermediate conformations, the most preferable beta-hairpin positions in the NAC region, and prevalent salt bridges propose the formation of so-called polymorph 2 or even a novel type of fibrils. A better understanding of the detailed mechanism of the amyloid conversion sheds light on the effect of Lewy body-related phosphorylation and might help in the development of new therapeutics for synucleinopathies.

Self-assembly of functional branched filaments, such as actin filaments and microtubules, or dysfunctional ones, such as amyloid fibrils, plays important roles in many biological processes. Here, based on the master equation approach, we study the kinetics of the formation of the branched fibrils. In our model, a branched fibril has one mother branch and several daughter branches. A daughter branch grows from the side of a pre-existing mother branch or daughter branch. In our model, we consider five basic processes for the self-assembly of the branched filaments, namely, the nucleation, the dissociation of the primary nucleus of fibrils, the elongation, the fragmentation, and the branching. The elongation of a mother branch from two ends and the elongation of a daughter branch from two ends can, in principle, occur with four different rate constants associated with the corresponding tips. This leads to a pronounced impact of the directionality of growth on the kinetics of the self-assembly. Here, we have unified and generalized our four previously presented models of branched fibrillogenesis in a single model. We have obtained a system of non-linear ordinary differential equations that give the time evolution of the polymer numbers and the mass concentrations along with the higher moments as observable quantities.

Epidemiological studies have revealed a correlation between Alzheimer's disease (AD) and type 2 diabetes mellitus (T2D). Insulin resistance in the brain is a common feature in patients with T2D and AD. KAT7 is a histone acetyltransferase that participates in the modulation of various genes.

To determine the effects of KAT7 on insulin patients with AD.

APPswe/PS1-dE9 double-transgenic and db/db mice were used to mimic AD and diabetes, respectively. An in vitro model of AD was established by Aβ stimulation. Insulin resistance was induced by chronic stimulation with high insulin levels. The expression of microtubule-associated protein 2 (MAP2) was assessed using immunofluorescence. The protein levels of MAP2, Aβ, dual-specificity tyrosine phosphorylation-regulated kinase-1A (DYRK1A), IRS-1, p-AKT, total AKT, p-GSK3β, total GSK3β, DYRK1A, and KAT7 were measured via western blotting. Accumulation of reactive oxygen species (ROS), malondialdehyde (MDA), and SOD activity was measured to determine cellular oxidative stress. Flow cytometry and CCK-8 assay were performed to evaluate neuronal cell death and proliferation, respectively. Relative RNA levels of KAT7 and DYRK1A were examined using quantitative PCR. A chromatin immunoprecipitation assay was conducted to detect H3K14ac in DYRK1A.

KAT7 expression was suppressed in the AD mice. Overexpression of KAT7 decreased Aβ accumulation and MAP2 expression in AD brains. KAT7 overexpression decreased ROS and MDA levels, elevated SOD activity in brain tissues and neurons, and simultaneously suppressed neuronal apoptosis. KAT7 upregulated levels of p-AKT and p-GSK3β to alleviate insulin resistance, along with elevated expression of DYRK1A. KAT7 depletion suppressed DYRK1A expression and impaired H3K14ac of DYRK1A. HMGN1 overexpression recovered DYRK1A levels and reversed insulin resistance caused by KAT7 depletion.

We determined that KAT7 overexpression recovered insulin sensitivity in AD by recruiting HMGN1 to enhance DYRK1A acetylation. Our findings suggest that KAT7 is a novel and promising therapeutic target for the resistance in AD.

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

In this work, we investigate how fluid flows impact the aggregation mechanisms of Aβ40 proteins and Aβ16-22 peptides and mechanically perturb their (pre)fibrillar aggregates. We exploit the OPEP coarse-grained model for proteins and the Lattice Boltzmann Molecular Dynamics technique. We show that beyond a critical shear rate, amyloid aggregation speeds up in Couette flow because of the shorter collisions times between aggregates, following a transition from diffusion limited to advection dominated dynamics. We also characterize the mechanical deformation of (pre)fibrillar states due to the fluid flows (Couette and Poiseuille), confirming the capability of (pre)fibrils to form pathological loop-like structures as detected in experiments. Our findings can be of relevance for microfluidic applications and for understanding aggregation in the interstitial brain space.

L-tryptophan (l-Trp), a vital amino acid for the survival of various organisms, is synthesized by the enzyme tryptophan synthase (TS) in organisms such as eubacteria, archaebacteria, protista, fungi, and plantae. TS, a pyridoxal 5'-phosphate (PLP)-dependent enzyme, comprises α and β subunits that typically form an α2β2 tetramer. The enzyme's activity is regulated by the conformational switching of its α and β subunits between the open (T state) and closed (R state) conformations. Many microorganisms rely on TS for growth and replication, making the enzyme and the l-Trp biosynthetic pathway potential drug targets. For instance, Mycobacterium tuberculosis, Chlamydiae bacteria, Streptococcus pneumoniae, Francisella tularensis, Salmonella bacteria, and Cryptosporidium parasitic protozoa depend on l-Trp synthesis. Antibiotic-resistant salmonella strains have emerged, underscoring the need for novel drugs targeting the l-Trp biosynthetic pathway, especially for salmonella-related infections. A single amino acid mutation can significantly impact enzyme function, affecting stability, conformational dynamics, and active or allosteric sites. These changes influence interactions, catalytic activity, and protein-ligand/protein-protein interactions. This study focuses on the impact of mutating the βGln114 residue on the catalytic and allosteric sites of TS. Extensive molecular dynamics simulations were conducted on E(PLP), E(AEX1), E(A-A), and E(C3) forms of TS using the WT, βQ114A, and βQ114N versions. The results show that both the βQ114A and βQ114N mutations increase protein backbone root mean square deviation fluctuations, destabilizing all TS forms. Conformational and hydrogen bond analyses suggest the significance of βGln114 drifting away from cofactor/intermediates and forming hydrogen bonds with water molecules necessary for l-Trp biosynthesis. The βQ114A mutation creates a gap between βAla114 and cofactor/intermediates, hindering hydrogen bond formation due to short side chains and disrupting β-sites. Conversely, the βQ114N mutation positions βAsn114 closer to cofactor/intermediates, forming hydrogen bonds with O3 of cofactors/intermediates and nearby water molecules, potentially disrupting the l-Trp biosynthetic mechanism.

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

Aβ1-40 peptide and Aβ1-42 peptide are the building units of beta-amyloid plaques present in Alzheimer's disease (AD)-affected brain. The binding affinity of various divalent metal ions such as Cu and Zn present in AD-affected brain with different amino acids available in Aβ-peptide became the focus to explore their role in soluble neurotoxic oligomer formation. Cu2+ metal ions are known to enhance the neurotoxicity of the Aβ1-42 peptide by catalyzing the formation of soluble neurotoxic oligomers. The competitive preference of both Cu2+ and Zn2+ simultaneously to interact with the Aβ-peptide is unknown. The divalent Cu and Zn ions were inserted in explicit aqueous Aβ1-42 peptide configurations to get insights into the binding competence of these metal ions with peptides using classical molecular dynamics (MD) simulations. The metal-ion interactions reveal that competitive binding preferences of various peptide sites become metal-ion-specific and differ significantly. For Cu2+, interactions are found to be more significant with respect to those of Asp-7, His-6, Glu-11, and His-14. Asp-1, Glu-3, Asp-7, His-6, Glu-11, and His-13 amino acid residues show higher affinity toward Zn2+ ions. MD simulations show notable variation in the solvent-accessible surface area in the hydrophobic region of the peptide. Infinitesimal mobility was obtained for Zn2+ compared to Cu2+ in an aqueous solution and Cu2+ diffusivity deviated significantly at different time scales, proving its labile features in aqueous Aβ1-42 peptides.

Phospholipids in biological membranes establish a chemical equilibrium between free phospholipids in the aqueous phase (CMC) and self-assembled phospholipids in vesicles, keeping the CMC constant. The CMC is different for each phospholipid, depends on the amount of cholesterol, and, according to the lipid-chaperone hypothesis, controls the interaction between free phospholipids and amyloidogenic proteins (such as amylin, amyloid-β, and α-synuclein, all of which are, respectively, associated with a different proteinopathy), which governs the formation of a toxic complex between free lipids and proteins that leads to membrane destruction. Here, we provide quantitative measurements of CMCs and bilayer stability of pure phospholipids, lipid rafts, and their mixture with cholesterol by fluorescence methods (using pyrene as a probe) and light scattering techniques (resonance Rayleigh scattering and fixed-angle light scattering) performed on LUVs, as well as AFM to measure LUV dimensions. Also, we test the lipid-chaperone hypothesis on human IAPP interacting with different mixture of POPC cholesterol. Stated the importance of CMC in membrane stability and protein aggregation processes, these results could be a starting point for the development of a quantitative kinetic model for the lipid chaperone hypothesis.

Protein sequencing is crucial for understanding the complex mechanisms driving biological functions. However, proteins are usually folded in their native state and the mechanism of fast protein conformation transitions still remains unclear, which make protein sequencing challenging. Molecular dynamics simulations with accurate force field are now able to observe the entire folding/unfolding process, providing valuable insights into protein folding mechanisms. Given that proteins can be unfolded, nanopore technology shows great potential for protein sequencing. In this study, we proposed to use MoS2/SnS2heterostructures to firstly unfold proteins and then detect them by a nanopore in the heterostructural membrane. All-atom molecular dynamics simulations performed in this work provided rich atomic-level information for a comprehensive understanding of protein unfolding process and mechanism on the MoS2/SnS2heterostructure, it was found that the strong binding of protein to SnS2nanostripe and hydrogen bond breaking were the main reasons for unfolding the protein on the heterostructure. After the protein was fully unfolded, it was restrained on the nanostripe because of the affinity of protein to the SnS2nanostripe. Thus by integrating the proposed unfolding technique with nanopore technology, detection of linear unfolded peptide was realized in this work, allowing for the identification of protein components, which is essential for sequencing proteins in the near future.

The formation of Aβ into amyloid fibrils was closely connected to AD, therefore, the Aβ aggregates were the primary therapeutic targets against AD. Previous studies demonstrated that epicatechin-3-gallate (ECG), which possessed a gallate moiety, exhibited a greater ability to disrupt the preformed Aβ amyloid fibrils than epicatechin (EC), indicating that the gallate moiety was crucial. In the present study, the molecular mechanisms were investigated. Our results demonstrated that ECG had more potent disruptive impacts on the β-sheet structure and K28-A42 salt bridges than EC. We found that ECG significantly interfered the interactions between Peptide-4 and Peptide-5. However, EC could not. The disruption of K28-A42 salt bridges by ECG was mainly due to the interactions between ECG and the hydrophobic residues located at C-terminus. Interestingly, EC disrupted the K28-A42 salt bridges by the interactions with C-terminal hydrophobic residues and the cation-π interactions with K28. Moreover, our results indicated that hydrophobic interactions, H-bonds, π-π interactions and cation-π interactions between ECG and the bend of L-shaped region caused the disaggregation of interactions between Peptide-4 and Peptide-5. Significantly, gallate moiety in ECG had contributed tremendously to the disaggregation. We believed that our findings could be useful for designing prospective drug candidates targeting AD.

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.

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

Amyloid-β peptide with predominant presence in the senile plaques is the most common agent for Alzheimer's disease (AD) incidence. Assembly of the amyloid-β(1-42) (Aβ1-42) isoform is known as the main reason for the AD appearance. Epigallocatechin gallate (EGCG) and 1,4-naphthoquinone-2-yl-L-tryptophan (NQTrp) are two small molecules that inhibit the formation of the Aβ1-42 fibrils. The present study provides molecular insight to clarify the inhibitory mechanisms of the EGCG and NQTrp ligands on the Aβ1-42 assemblies by using molecular dynamics (MD) simulation. Hence, nine different Aβ1-42-containing systems including the monomer, dimer, and hexamer of Aβ1-42 considering each of them in a media with no ligands, in the presence of one EGCG ligand, and in the presence of one EGCG ligand were studied with a simulation time of 1 µs for each system. The precise investigation of the peptide-ligand distance, conformational factor (Pi), solvent accessible surface area (SASA), dictionary of secondary structure (DSSP), and Lys28-Ala42 salt bridge analyses confirmed that the hydroxyl-rich structure of the EGCG ligand applied its inhibitory effect on the aggregation of the peptides indirectly by involving water molecules. While the hydroxyl-free structure of the NQTrp ligand exposed its inhibitory effect through a direct interaction with the Aβ1-42 peptides. Besides, reduced density gradient (RDG) analysis clarified the hydrogen bonding interactions as the dominant ones for the peptide-EGCG systems, and also, steric and van der Waals interactions for the peptide-NQTrp systems.Communicated by Ramaswamy H. Sarma.

The interactions of amyloid proteins with membranes have been subject to many experimental and computational studies, as these interactions contribute in part to neurodegenerative diseases. In this review, we report on recent simulations that have focused on the adsorption and insertion modes of amyloid-β and tau proteins in membranes. The atomistic-resolution characterization of the conformational changes of these amyloid proteins upon lipid cell membrane and free lipid interactions is of interest to rationally design drugs targeting transient oligomers in Alzheimer's disease.

De novo designed peptides that self-assemble into cross-β rich fibrillar biomaterials have been pursued as an innovative platform for the development of adjuvant- and inflammation-free vaccines. However, they share structural and morphological properties similar to amyloid species implicated in neurodegenerative diseases, which has been a long-standing concern for their successful translation. Here, we comprehensively characterize the amyloidogenic character of the amphipathic self-assembling cross-β peptide KFE8, compared to pathological amyloid and amyloid-like proteins α-synuclein (α-syn) and TDP-43. Further, we developed plasmid-based DNA vaccines with the KFE8 backbone serving as a scaffold for delivery of a GFP model antigen. We find that expression of tandem repeats of KFE8 is non-toxic and efficiently cleared by autophagy. We also demonstrate that preformed KFE8 fibrils do not cross-seed amyloid formation of α-syn in mammalian cells compared to α-syn preformed fibrils. In mice, vaccination with plasmids encoding the KFE32-GFP fusion protein elicited robust immune responses, inducing production of significantly higher levels of anti-GFP antibodies compared to soluble GFP. Antigen-specific CD8+T cells were also detected in the spleens of vaccinated mice and cytokine profiles from antigen recall assays indicate a balanced Th1/Th2 response. These findings illustrate that cross-β-rich peptide nanofibers have distinct physicochemical properties from those of pathological amyloidogenic proteins, and are an attractive platform for the development of DNA vaccines with self-adjuvanting properties and improved safety profiles. STATEMENT OF SIGNIFICANCE: Biomaterials comprised of self-assembling peptides hold great promise for the development of new vaccines that do not require use of adjuvants. However, these materials have safety concerns, as they self-assemble into cross-β rich fibrils that are structurally similar to amyloid species implicated in disease. Here, we comprehensively study the properties of these biomaterials. We demonstrate that they have distinct properties from pathological proteins. They are non-toxic and do not trigger amyloidogenesis. Vaccination of these materials in mice elicited a robust immune response. Most excitingly, our work suggests that this platform could be used to develop DNA-based vaccines, which have few storage requirements. Further, due to their genetic encoding, longer sequences can be generated and the vaccines will be amenable to modification.

Rapid growth of amyloid fibrils via a seeded conformational conversion of monomers is a critical step of fibrillization and important for disease transmission and progression. Amyloid fibrils often display diverse morphologies with distinct populations, and yet the molecular mechanisms of fibril elongation and their corresponding morphological dependence remain poorly understood. Here, we computationally investigated the single-molecular growth of two experimentally resolved human islet amyloid polypeptide fibrils of different morphologies. In both cases, the incorporation of monomers into preformed fibrils was observed. The conformational conversion dynamics was characterized by a small number of fibril growth intermediates. Fibril morphology affected monomer binding at fibril elongation and lateral surfaces as well as the seeded conformational conversion dynamics at the fibril ends, resulting in different fibril elongation rates and populations. We also observed an asymmetric fibril growth as in our prior experiments, attributing to differences of two fibril ends in terms of their local surface curvatures and exposed hydrogen-bond donors and acceptors. Together, our mechanistic findings afforded a theoretical basis for delineating different amyloid strains-entailed divergent disease progression.

Before the controversial approval of humanized monoclonal antibody lecanemab, which binds to the soluble amyloid-β protofibrils, all the treatments available earlier, for Alzheimer's disease (AD) were symptomatic. The researchers are still struggling to find a breakthrough in AD therapeutic medicine, which is partially attributable to lack in understanding of the structural information associated with the intrinsically disordered proteins and amyloids. One of the major challenges in this area of research is to understand the structural diversity of intrinsically disordered proteins under in vitro conditions. Therefore, in this review, we have summarized the in vitro applications of biophysical methods, which are aimed to shed some light on the heterogeneity, pathogenicity, structures and mechanisms of the intrinsically disordered protein aggregates associated with proteinopathies including AD. This review will also rationalize some of the strategies in modulating disease-relevant pathogenic protein entities by small molecules using structural biology approaches and biophysical characterization. We have also highlighted tools and techniques to simulate the in vivo conditions for native and cytotoxic tau/amyloids assemblies, urge new chemical approaches to replicate tau/amyloids assemblies similar to those in vivo conditions, in addition to designing novel potential drugs.

Protein aggregation results in an array of different size soluble oligomers and larger insoluble fibrils. Insoluble fibrils were originally thought to cause neuronal cell deaths in neurodegenerative diseases due to their prevalence in tissue samples and disease models. Despite recent studies demonstrating the toxicity associated with soluble oligomers, many therapeutic strategies still focus on fibrils or consider all types of aggregates as one group. Oligomers and fibrils require different modeling and therapeutic strategies, targeting the toxic species is crucial for successful study and therapeutic development. Here, we review the role of different-size aggregates in disease, and how factors contributing to aggregation (mutations, metals, post-translational modifications, and lipid interactions) may promote oligomers opposed to fibrils. We review two different computational modeling strategies (molecular dynamics and kinetic modeling) and how they are used to model both oligomers and fibrils. Finally, we outline the current therapeutic strategies targeting aggregating proteins and their strengths and weaknesses for targeting oligomers versus fibrils. Altogether, we aim to highlight the importance of distinguishing the difference between oligomers and fibrils and determining which species is toxic when modeling and creating therapeutics for protein aggregation in disease.

As a model of self-assembly from disordered monomers to fibrils, the amyloid-β fragment Aβ16-22 was subject to past numerous experimental and computational studies. Because dynamics information between milliseconds and seconds cannot be assessed by both studies, we lack a full understanding of its oligomerization. Lattice simulations are particularly well suited to capture pathways to fibrils. In this study, we explored the aggregation of 10 Aβ16-22 peptides using 65 lattice Monte Carlo simulations, each simulation consisting of 3 × 109 steps. Based on a total of 24 and 41 simulations that converge and do not converge to the fibril state, respectively, we are able to reveal the diversity of the pathways leading to fibril structure and the conformational traps slowing down the fibril formation.

The accumulation of the amyloid-β peptides (Aβ) is central to the development of Alzheimer's disease. The mechanism by which Aβ triggers a cascade of events that leads to dementia is a topic of intense investigation. Aβ self-associates into a series of complex assemblies with different structural and biophysical properties. It is the interaction of these oligomeric, protofibril and fibrillar assemblies with lipid membranes, or with membrane receptors, that results in membrane permeability and loss of cellular homeostasis, a key event in Alzheimer's disease pathology. Aβ can have an array of impacts on lipid membranes, reports have included: a carpeting effect; a detergent effect; and Aβ ion-channel pore formation. Recent advances imaging these interactions are providing a clearer picture of Aβ induced membrane disruption. Understanding the relationship between different Aβ structures and membrane permeability will inform therapeutics targeting Aβ cytotoxicity.