From Aβ Filament to Fibril: Molecular Mechanism of Surface-Activated Secondary Nucleation from All-Atom MD Simulations

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

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

Unlocking novel therapies: cyclic peptide design for amyloidogenic targets through synergies of experiments, simulations, and machine learning

Existing therapies for neurodegenerative diseases like Parkinson's and Alzheimer's address only their symptoms and do not prevent disease onset. Common therapeutic agents, such as small molecules and antibodies struggle with insufficient selectivity, stability and bioavailability, leading to poor performance in clinical trials. Peptide-based therapeutics are emerging as promising candidates, with successful applications for cardiovascular diseases and cancers due to their high bioavailability, good efficacy and specificity. In particular, cyclic peptides have a long in vivo stability, while maintaining a robust antibody-like binding affinity. However, the de novo design of cyclic peptides is challenging due to the lack of long-lived druggable pockets of the target polypeptide, absence of exhaustive conformational distributions of the target and/or the binder, unknown binding site, methodological limitations, associated constraints (failed trials, time, money) and the vast combinatorial sequence space. Hence, efficient alignment and cooperation between disciplines, and synergies between experiments and simulations complemented by popular techniques like machine-learning can significantly speed up the therapeutic cyclic-peptide development for neurodegenerative diseases. We review the latest advancements in cyclic peptide design against amyloidogenic targets from a computational perspective in light of recent advancements and potential of machine learning to optimize the design process. We discuss the difficulties encountered when designing novel peptide-based inhibitors and we propose new strategies incorporating experiments, simulations and machine learning to design cyclic peptides to inhibit the toxic propagation of amyloidogenic polypeptides. Importantly, these strategies extend beyond the mere design of cyclic peptides and serve as template for the de novo generation of (bio)materials with programmable properties.

Nucleation and Growth of Amyloid Fibrils

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

Evolution of large Aβ16-22 aggregates at atomic details and potential of mean force associated to peptide unbinding and fragmentation events

Atomic characterization of large nonfibrillar aggregates of amyloid polypeptides cannot be determined by experimental means. Starting from β-rich aggregates of Y and elongated topologies predicted by coarse-grained simulations and consisting of more than 100 Aβ16-22 peptides, we performed atomistic molecular dynamics (MD), replica exchange with solute scaling (REST2), and umbrella sampling simulations using the CHARMM36m force field in explicit solvent. Here, we explored the dynamics within 3 μs, the free energy landscape, and the potential of mean force associated with either the unbinding of one single peptide in different configurations within the aggregate or fragmentation events of a large number of peptides. Within the time scale of MD and REST2, we find that the aggregates experience slow global conformational plasticity, and remain essentially random coil though we observe slow beta-strand structuring with a dominance of antiparallel beta-sheets over parallel beta-sheets. Enhanced REST2 simulation is able to capture fragmentation events, and the free energy of fragmentation of a large block of peptides is found to be similar to the free energy associated with fibril depolymerization by one chain for longer Aβ sequences.

Early-Stage Oligomerization of Prion-like Polypeptides Reveals the Molecular Mechanism of Amyloid-Disrupting Capacity by Proline Residues

Proline cis/trans isomerization governs protein local conformational changes via its local mechanical rigidity. The amyloid-disrupting capacity of proline is widely acknowledged; however, the molecular mechanism is still not clear. To understand how proline residues in polypeptide chains influence amyloid propensity, we study several truncated sequences of the TDP-43 C-terminal region (287-322) and their triple proline variants (308PPP310). We use coarse-grained molecular simulation to study the time evolution of the process of aggregation in the early stages in an effective high-concentration condition (∼25 mM). This ensures the long time scales for protein association at laboratory concentrations. We use several experimentally determined structure templates as initial structures of monomer conformations. We carry out oligomer size analysis and cluster analysis, along with several structural measures, to characterize the size distributions of oligomers and their morphological/structural properties. We show that average oligomer size is not a good indicator of amyloid propensity. Structural order and/or morphological properties are better alternatives. We show that proline variants can efficiently maintain the formation of large "ordered" oligomers of shorter truncated sequences, i.e., 307-322. This "order" maintenance is weakened when using longer truncated sequences (i.e., 287-322), leading to the formation of "disordered" oligomers. From an energy trade-off perspective, if the entropic effect is weak (short sequence length), the shape-complementarity of proline variants effectively guides the oligomerization process to form "ordered" oligomer intermediates. This leads to a distinct aggregation pathway that promotes amyloid formation (on-pathway). Strong entropic effects (long sequence length), however, would cause the formation of "disordered" oligomers. This in turn will suppress amyloid formation (off-pathway). The proline shape-complementary effects provide a guided morphological restraint to facilitate the pathways of amyloid formation. Our study supports the importance of structure-based kinetic heterogeneity of prion-like sequence fragments in driving different aggregation pathways. This work sheds light on the role of morphological and structural order of early-stage oligomeric species in regulating amyloid-disrupting capacity by prolines.

A guide to studying protein aggregation

Disrupted protein folding or decreased protein stability can lead to the accumulation of (partially) un- or misfolded proteins, which ultimately cause the formation of protein aggregates. Much of the interest in protein aggregation is associated with its involvement in a wide range of human diseases and the challenges it poses for large-scale biopharmaceutical manufacturing and formulation of therapeutic proteins and peptides. On the other hand, protein aggregates can also be functional, as observed in nature, which triggered its use in the development of biomaterials or therapeutics as well as for the improvement of food characteristics. Thus, unmasking the various steps involved in protein aggregation is critical to obtain a better understanding of the underlying mechanism of amyloid formation. This knowledge will allow a more tailored development of diagnostic methods and treatments for amyloid-associated diseases, as well as applications in the fields of new (bio)materials, food technology and therapeutics. However, the complex and dynamic nature of the aggregation process makes the study of protein aggregation challenging. To provide guidance on how to analyse protein aggregation, in this review we summarize the most commonly investigated aspects of protein aggregation with some popular corresponding methods.

Computational models for studying physical instabilities in high concentration biotherapeutic formulations

Computational prediction of the behavior of concentrated protein solutions is particularly advantageous in early development stages of biotherapeutics when material availability is limited and a large set of formulation conditions needs to be explored. This review provides an overview of the different computational paradigms that have been successfully used in modeling undesirable physical behaviors of protein solutions with a particular emphasis on high-concentration drug formulations. This includes models ranging from all-atom simulations, coarse-grained representations to macro-scale mathematical descriptions used to study physical instability phenomena of protein solutions such as aggregation, elevated viscosity, and phase separation. These models are compared and summarized in the context of the physical processes and their underlying assumptions and limitations. A detailed analysis is also given for identifying protein interaction processes that are explicitly or implicitly considered in the different modeling approaches and particularly their relations to various formulation parameters. Lastly, many of the shortcomings of existing computational models are discussed, providing perspectives and possible directions toward an efficient computational framework for designing effective protein formulations.

Single-molecule Observation of Self-Propagating Amyloid Fibrils

The assembly of misfolded proteins into amyloid fibrils is associated with amyloidosis, including neurodegenerative diseases, such as Alzheimer’s, Parkinson’s, and prion diseases. The self-propagation of amyloid fibrils is widely observed in the aggregation pathways of numerous amyloidogenic proteins. This propensity with plasticity in primary nucleation allows amyloid fibril polymorphism, which is correlated with the pathology/phenotypes of patients. Because the interference with the nucleation and replication processes of amyloid fibrils can alter the amyloid structure and the outcome of the disease, these processes can be a target for developing clinical drugs. Single-molecule observation of amyloid fibril replication can be an experimental system to provide the kinetic parameters for simulation studies and confirm the effect of clinical drugs. Here, we review single-molecule observation of the amyloid fibril replication process using fluorescence microscopy and time-lapse atomic force microscopy, including high-speed atomic force microscopy. We discussed the amyloid fibril replication process and combined single-molecule observation results with molecular dynamics simulations.

Mini Abstract Structural dynamics in amyloid aggregation is related with various Alzheimer’s and Parkinson’s disease symptoms. Single-molecule observation using high-speed atomic force microscopy can directly visualize the structural dynamics of individual amyloid aggregate assemblies. Here, we review historical and recent studies of single-molecule observation of amyloid aggregation with supportive molecular dynamics simulation.

Fibril Surface-Dependent Amyloid Precursors Revealed by Coarse-Grained Molecular Dynamics Simulation

Amyloid peptides are known to self-assemble into larger aggregates that are linked to the pathogenesis of many neurodegenerative disorders. In contrast to primary nucleation, recent experimental and theoretical studies have shown that many toxic oligomeric species are generated through secondary processes on a pre-existing fibrillar surface. Nucleation, for example, can also occur along the surface of a pre-existing fibril—secondary nucleation—as opposed to the primary one. However, explicit pathways are still not clear. In this study, we use molecular dynamics simulation to explore the free energy landscape of a free Abeta monomer binding to an existing fibrillar surface. We specifically look into several potential Abeta structural precursors that might precede some secondary events, including elongation and secondary nucleation. We find that the overall process of surface-dependent events can be described at least by the following three stages: 1. Free diffusion 2. Downhill guiding 3. Dock and lock. And we show that the outcome of adding a new monomer onto a pre-existing fibril is pathway-dependent, which leads to different secondary processes. To understand structural details, we have identified several monomeric amyloid precursors over the fibrillar surfaces and characterize their heterogeneity using a probability contact map analysis. Using the frustration analysis (a bioinformatics tool), we show that surface heterogeneity correlates with the energy frustration of specific local residues that form binding sites on the fibrillar structure. We further investigate the helical twisting of protofilaments of different sizes and observe a length dependence on the filament twisting. This work presents a comprehensive survey over the properties of fibril growth using a combination of several openMM-based platforms, including the GPU-enabled openAWSEM package for coarse-grained modeling, MDTraj for trajectory analysis, and pyEMMA for free energy calculation. This combined approach makes long-timescale simulation for aggregation systems as well as all-in-one analysis feasible. We show that this protocol allows us to explore fibril stability, surface binding affinity/heterogeneity, as well as fibrillar twisting. All these properties are important for understanding the molecular mechanism of surface-catalyzed secondary processes of fibril growth.

The role of amyloid oligomers in neurodegenerative pathologies

Many neurodegenerative diseases are rooted in the activities of amyloid-like proteins which possess conformations that spread to healthy proteins. These include Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD) and amyotrophic lateral sclerosis (ALS). While their clinical manifestations vary, their protein-level mechanisms are remarkably similar. Aberrant monomeric proteins undergo conformational shifts, facilitating aggregation and formation of solid fibrils. However, there is growing evidence that intermediate oligomeric stages are key drivers of neuronal toxicity. Analysis of protein dynamics is complicated by the fact that nucleation and growth of amyloid-like proteins is not a linear pathway. Feedback within this pathway results in exponential acceleration of aggregation, but activities exerted by oligomers and fibrils can alter cellular interactions and the cellular environment as a whole. The resulting cascade of effects likely contributes to the late onset and accelerating progression of amyloid-like protein disorders and the widespread effects they have on the body. In this review we explore the amyloid-like proteins associated with AD, PD, HD and ALS, as well as the common mechanisms of amyloid-like protein nucleation and aggregation. From this, we identify core elements of pathological progression which have been targeted for therapies, and which may become future therapeutic targets.

Defining the Neuropathological Aggresome across in Silico, in Vitro, and ex Vivo Experiments

The loss of proteostasis over the life course is associated with a wide range of debilitating degenerative diseases and is a central hallmark of human aging. When left unchecked, proteins that are intrinsically disordered can pathologically aggregate into highly ordered fibrils, plaques, and tangles (termed amyloids), which are associated with countless disorders such as Alzheimer's disease, Parkinson's disease, type II diabetes, cancer, and even certain viral infections. However, despite significant advances in protein folding and solution biophysics techniques, determining the molecular cause of these conditions in humans has remained elusive. This has been due, in part, to recent discoveries showing that soluble protein oligomers, not insoluble fibrils or plaques, drive the majority of pathological processes. This has subsequently led researchers to focus instead on heterogeneous and often promiscuous protein oligomers. Unfortunately, significant gaps remain in how to prepare, model, experimentally corroborate, and extract amyloid oligomers relevant to human disease in a systematic manner. This Review will report on each of these techniques and their successes and shortcomings in an attempt to standardize comparisons between protein oligomers across disciplines, especially in the context of neurodegeneration. By standardizing multiple techniques and identifying their common overlap, a clearer picture of the soluble neuropathological aggresome can be constructed and used as a baseline for studying human disease and aging.

Structural Characteristics of Monomeric Aβ42 on Fibril in the Early Stage of Secondary Nucleation Process

Amyloid-β (Aβ) aggregates are believed to be one of the main causes of Alzheimer's disease. Aβ peptides form fibrils having cross β-sheet structures mainly through primary nucleation, secondary nucleation, and elongation. In particular, self-catalyzed secondary nucleation is of great interest. Here, we investigate the adsorption of Aβ42 peptides to the Aβ42 fibril to reveal a role of adsorption as a part of secondary nucleation. We performed extensive molecular dynamics simulations based on replica exchange with solute tempering 2 (REST2) to two systems: a monomeric Aβ42 in solution and a complex of an Aβ42 peptide and Aβ42 fibril. Results of our simulations show that the Aβ42 monomer is extended on the fibril. Furthermore, we find that the hairpin structure of the Aβ42 monomer decreases but the helix structure increases by adsorption to the fibril surface. These structural changes are preferable for forming fibril-like aggregates, suggesting that the fibril surface serves as a catalyst in the secondary nucleation process. In addition, the stabilization of the helix structure of the Aβ42 monomer on the fibril indicates that the strategy of a secondary nucleation inhibitor design for Aβ40 can also be used for Aβ42.

From monomer to fibril: Abeta-amyloid binding to Aducanumab antibody studied by molecular dynamics simulation

Alzheimer's disease is one of the most common causes of dementia. It is believed that the aggregation of short Aβ-peptides to form oligomeric and protofibrillar amyloid assemblies plays a central role for disease-relevant neurotoxicity. In recent years, passive immunotherapy has been introduced as a potential treatment strategy with anti-amyloid antibodies binding to Aβ-amyloids and inducing their subsequent degradation by the immune system. Although so far mostly unsuccessful in clinical studies, the high-dosed application of the monoclonal antibody Aducanumab has shown therapeutic potential that might be attributed to its much greater affinity to Aβ-aggregates vs monomeric Aβ-peptides. In order to better understand how Aducanumab interacts with aggregated Aβ-forms compared to monomers, we have generated structural model complexes based on the known structure of Aducanumab in complex with an Aβ_2 - 7 -eptitope. Structural models of Aducanumab bound to full-sequence Aβ_1 - 40 -monomers, oligomers, protofilaments and mature fibrils were generated and investigated using extensive molecular dynamics simulations to characterize the flexibility and possible additional interactions. Indeed, an aggregate-specific N-terminal binding motif was found in case of Aducanumab binding to oligomers, protofilaments and fibrils that is located next to but not overlapping with the epitope binding site found in the crystal structure with Aβ_2 - 7 . Analysis of binding energetics indicates that this motif binds weaker than the epitope but likely contributes to Aducanumab's preference for aggregated Aβ-species. The predicted aggregate-specific binding motif could potentially serve as a basis to reengineer Aducanumab for further enhanced preference to bind Aβ-aggregates vs monomers.

Amyloid-β (Aβ42) Peptide Aggregation Rate and Mechanism on Surfaces with Widely Varied Properties: Insights from Brownian Dynamics Simulations

Amyloid-β (Aβ) plaques, which form by aggregation of harmless Aβ peptide monomers into larger fibrils, are characteristic of neurodegenerative disorders such as Alzheimer's disease. Efforts to treat Alzheimer's disease focus on stopping or reversing the aggregation process that leads to fibril formation. However, effective treatments are elusive due to certain unknown aspects of the process. Many hypotheses point to disruption of cell membranes by adsorbed Aβ monomers or oligomers, but how Aβ behaves and aggregates on surfaces of widely varying properties, such as those present in a cell, is unclear. Elucidating the effects of various surfaces on the dynamics of Aβ and the kinetics of the aggregation process from bulk solution to a surface-adsorbed multimer can help identify what drives aggregation, leading to new methods of intervention by inhibitory drugs or other means. In this work, we used all-atom Brownian dynamics simulations to study the association of two distinct Aβ42 monomer conformations with a surface-adsorbed or free-floating Aβ42 dimer. We calculated the association time, surface interaction energy, surface diffusion coefficient, surface residence time, and the mechanism of association on four different surfaces and two different bulk solution scenarios. In the presence of a surface, the majority of monomers underwent a two-dimensional surface-mediated association that depended primarily on an Aβ42 electrostatic interaction with the self-assembled monolayer (SAM) surfaces. Moreover, aggregation could be inhibited greatly by surfaces with high affinity for Aβ42 and heterogeneous charge distribution. Our results can be used to identify new opportunities for disrupting or reversing the Aβ42 aggregation process.

Targeting the Amyloid-β Fibril Surface with a Constrained Helical Peptide Inhibitor

Amyloid-β (Aβ) oligomers are well-known toxic molecular species associated with Alzheimer's disease. Recent discoveries of the ability of amyloid fibril surfaces to convert soluble proteins into toxic oligomers suggested that these surfaces could serve as therapeutic targets for intervention. We have shown previously that a short helical peptide could be a key structural motif that can specifically recognize the K₁₆-E₂₂ region of the Aβ40 fibril surface with an affinity at the level of several micromolar. Here, we demonstrate that in-tether chiral center-induced helical stabilized peptides could also recognize the fibril surfaces, effectively inhibiting the surface-mediated oligomerization of Aβ40. Moreover, through extensive computational sampling, we observed two distinct ways in which the peptide inhibitors recognize the fibril surface. Apart from a binding mode that, in accord with the original design, involves hydrophobic side chains at the binding interface, we observed much more frequently another binding mode in which the hydrophobic staple interacts directly with the fibril surface. The affinity of the peptides for the fibril surface could be adjusted by tuning the hydrophobicity of the staple. The best candidate investigated here exhibits a submicromolar affinity (∼0.75 μM). Collectively, this work opens an avenue for the rational design of candidate drugs with stapled peptides for amyloid-related disease.

Combining molecular dynamics simulations and experimental analyses in protein misfolding

The fold of a protein determines its function and its misfolding can result in loss-of-function defects. In addition, for certain proteins their misfolding can lead to gain-of-function toxicities resulting in protein misfolding diseases such as Alzheimer's, Parkinson's, or the prion diseases. In all of these diseases one or more proteins misfold and aggregate into disease-specific assemblies, often in the form of fibrillar amyloid deposits. Most, if not all, protein misfolding diseases share a fundamental molecular mechanism that governs the misfolding and subsequent aggregation. A wide variety of experimental methods have contributed to our knowledge about misfolded protein aggregates, some of which are briefly described in this review. The misfolding mechanism itself is difficult to investigate, as the necessary timescale and resolution of the misfolding events often lie outside of the observable parameter space. Molecular dynamics simulations fill this gap by virtue of their intrinsic, molecular perspective and the step-by-step iterative process that forms the basis of the simulations. This review focuses on molecular dynamics simulations and how they combine with experimental analyses to provide detailed insights into protein misfolding and the ensuing diseases.

Aggregation of disease-related peptides

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

Steady, Symmetric, and Reversible Growth and Dissolution of Individual Amyloid-β Fibrils

Oligomers and fibrils of the amyloid-β (Aβ) peptide are implicated in the pathology of Alzheimer's disease. Here, we monitor the growth of individual Aβ40 fibrils by time-resolved in situ atomic force microscopy and thereby directly measure fibril growth rates. The measured growth rates in a population of fibrils that includes both single protofilaments and bundles of filaments are independent of the fibril thickness, indicating that cooperation between adjacent protofilaments does not affect incorporation of monomers. The opposite ends of individual fibrils grow at similar rates. In contrast to the "stop-and-go" kinetics that has previously been observed for amyloid-forming peptides, growth and dissolution of the Aβ40 fibrils are relatively steady for peptide concentration of 0-10 μM. The fibrils readily dissolve in quiescent peptide-free solutions at a rate that is consistent with the microscopic reversibility of growth and dissolution. Importantly, the bimolecular rate coefficient for the association of a monomer to the fibril end is significantly smaller than the diffusion limit, implying that the transition state for incorporation of a monomer into a fibril is associated with a relatively high free energy.

The interactions of an Aβ protofibril with a cholesterol-enriched membrane and involvement of neuroprotective carbazolium-based substances

Recent studies have shown that the aggregation of the amyloid-beta peptide (Aβ) in the brain cell membrane is responsible for the emergence of Alzheimer's disease (AD); the exploration of effective factors involved in the extension of the aggregation process and alternatively the examination of an effective inhibitor via theoretical and experimental tools are among the main research topics in the field of AD treatment. Therefore, in this study, we used all-atom molecular dynamics (MD) simulations to clarify the impact of cell membrane cholesterol on the interaction of Aβ with 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) as a membrane model. Moreover, the effect of the P7C3-S243 molecule on the abovementioned process was investigated. The simulation results disclosed the neuroprotective property of the P7C3-S243 molecule. The MD simulation results indicate that the interaction of cholesterol molecules with the Aβ oligomer is negligible and cannot enhance membrane rupture. However, strong hydrogen bonding between the POPC molecules and the oligomers led to membrane perturbation. According to our modellings, the P7C3-S243 molecular layer can protect the cell membrane by inhibiting the direct interaction between the bilayer and Aβ. In addition, free-energy calculations were conducted to determine the possible penetration of Aβ fibrils into the cholesterol-enriched membrane.

Molecular insights into the surface-catalyzed secondary nucleation of amyloid-β40 (Aβ40) by the peptide fragment Aβ16-22

Understanding the structural mechanism by which proteins and peptides aggregate is crucial, given the role of fibrillar aggregates in debilitating amyloid diseases and bioinspired materials. Yet, this is a major challenge as the assembly involves multiple heterogeneous and transient intermediates. Here, we analyze the co-aggregation of Aβ₄₀ and Aβ_16-22, two widely studied peptide fragments of Aβ₄₂ implicated in Alzheimer's disease. We demonstrate that Aβ_16-22 increases the aggregation rate of Aβ₄₀ through a surface-catalyzed secondary nucleation mechanism. Discontinuous molecular dynamics simulations allowed aggregation to be tracked from the initial random coil monomer to the catalysis of nucleation on the fibril surface. Together, the results provide insight into how dynamic interactions between Aβ₄₀ monomers/oligomers on the surface of preformed Aβ_16-22 fibrils nucleate Aβ₄₀ amyloid assembly. This new understanding may facilitate development of surfaces designed to enhance or suppress secondary nucleation and hence to control the rates and products of fibril assembly.

Network-Based Classification and Modeling of Amyloid Fibrils

Amyloid fibrils are locally ordered protein aggregates that self-assemble under a variety of physiological and in vitro conditions. Their formation is of fundamental interest as a physical chemistry problem and plays a central role in Alzheimer's disease, Type II diabetes, and other human diseases. As the number of known amyloid fibril structures has grown, the need has arisen for a nomenclature for describing and classifying fibril types, as well as a theoretical description of the physics that gives rise to the self-assembly of these structures. Here, we introduce a systematic nomenclature and coarse-graining methodology for describing the topology of fibrils and other protein aggregates, along with a computational methodology for simulating protein aggregation. Both have mathematical underpinnings in graph theory and statistical mechanics and are consistent with available experimental data on the fibril structure and aggregation kinetics. Our graph representation of the fibril topology enables us to define a network Hamiltonian based on connectivity patterns among monomers rather than detailed intermolecular interactions, greatly speeding up the simulation of large ensembles. Our simulation strategy is capable of recapitulating the formation of all currently known amyloid fibril topologies found in the Protein Data Bank, as well as the formation kinetics of fibrils and oligomers.

Oxidation destabilizes toxic amyloid beta peptide aggregation

The aggregation of insoluble amyloid beta (Aβ) peptides in the brain is known to trigger the onset of neurodegenerative diseases, such as Alzheimer’s disease. In spite of the massive number of investigations, the underlying mechanisms to destabilize the Aβ aggregates are still poorly understood. Some studies indicate the importance of oxidation to destabilize the Aβ aggregates. In particular, oxidation induced by cold atmospheric plasma (CAP) has demonstrated promising results in eliminating these toxic aggregates. In this paper, we investigate the effect of oxidation on the stability of an Aβ pentamer. By means of molecular dynamics simulations and umbrella sampling, we elucidate the conformational changes of Aβ pentamer in the presence of oxidized residues, and we estimate the dissociation free energy of the terminal peptide out of the pentamer form. The calculated dissociation free energy of the terminal peptide is also found to decrease with increasing oxidation. This indicates that Aβ pentamer aggregation becomes less favorable upon oxidation. Our study contributes to a better insight in one of the potential mechanisms for inhibition of toxic Aβ peptide aggregation, which is considered to be the main culprit to Alzheimer’s disease.

Molecular Determinants of Aβ42 Adsorption to Amyloid Fibril Surfaces

The long lag times and subsequent rapid growth of Alzheimer's Aβ₄₂ fibrils can be explained by a secondary nucleation step, in which existing fibril surfaces are able to nucleate the formation of new fibrils via an autocatalytic process. The molecular mechanism of secondary nucleation, however, is still unknown. Here we investigate the first step, namely, adsorption of the Aβ₄₂ peptide monomers onto the fibril surface. Using long all-atom molecular simulations and an enhanced sampling scheme, we are able to generate a diverse ensemble of binding events. The resulting thermodynamics of adsorption are consistent with experiment as well as with the requirements for effective autocatalysis determined from coarse-grained simulations. We identify the key interactions stabilizing the adsorbed state, which are predominantly polar in nature, and relate them to the effects of known disease-causing mutations.

Secondary nucleation in amyloid formation

Nucleation of new peptide and protein aggregates on the surfaces of amyloid fibrils of the same peptide or protein has emerged in the past two decades as a major pathway for both the generation of molecular species responsible for cellular toxicity and for the autocatalytic proliferation of peptide and protein aggregates. A key question in current research is the molecular mechanism and driving forces governing such processes, known as secondary nucleation. In this context, the analogies with other self-assembling systems for which monomer-dependent secondary nucleation has been studied for more than a century provide a valuable source of inspiration. Here, we present a short overview of this background and then review recent results regarding secondary nucleation of amyloid-forming peptides and proteins, focusing in particular on the amyloid β peptide (Aβ) from Alzheimer's disease, with some examples regarding α-synuclein from Parkinson's disease. Monomer-dependent secondary nucleation of Aβ was discovered using a combination of kinetic experiments, global analysis, seeding experiments and selective isotope-enrichment, which pinpoint the monomer as the origin of new aggregates in a fibril-catalyzed reaction. Insights into driving forces are gained from variations of solution conditions, temperature and peptide sequence. Selective inhibition of secondary nucleation is explored as an effective means to limit oligomer production and toxicity. We also review experiments aimed at finding interaction partners of oligomers generated by secondary nucleation in an ongoing aggregation process. At the end of this feature article we bring forward outstanding questions and testable mechanistic hypotheses regarding monomer-dependent secondary nucleation in amyloid formation.

Amyloid and the origin of life: self-replicating catalytic amyloids as prebiotic informational and protometabolic entities

A crucial stage in the origin of life was the emergence of the first molecular entity that was able to replicate, transmit information, and evolve on the early Earth. The amyloid world hypothesis posits that in the pre-RNA era, information processing was based on catalytic amyloids. The self-assembly of short peptides into β-sheet amyloid conformers leads to extraordinary structural stability and novel multifunctionality that cannot be achieved by the corresponding nonaggregated peptides. The new functions include self-replication, catalytic activities, and information transfer. The environmentally sensitive template-assisted replication cycles generate a variety of amyloid polymorphs on which evolutive forces can act, and the fibrillar assemblies can serve as scaffolds for the amyloids themselves and for ribonucleotides proteins and lipids. The role of amyloid in the putative transition process from an amyloid world to an amyloid-RNA-protein world is not limited to scaffolding and protection: the interactions between amyloid, RNA, and protein are both complex and cooperative, and the amyloid assemblages can function as protometabolic entities catalyzing the formation of simple metabolite precursors. The emergence of a pristine amyloid-based in-put sensitive, chiroselective, and error correcting information-processing system, and the evolvement of mutualistic networks were, arguably, of essential importance in the dynamic processes that led to increased complexity, organization, compartmentalization, and, eventually, the origin of life.

Thermodynamics of Amyloid-β Fibril Elongation: Atomistic Details of the Transition State

Amyloid-β (Aβ) fibrils and plaques are one of the hallmarks of Alzheimer’s disease. While the kinetics of fibrillar growth of Aβ have been extensively studied, several vital questions remain. In particular, the atomistic origins of the Arrhenius barrier observed in experiments have not been elucidated. Employing the familiar thermodynamic integration method, we have directly simulated the dissociation of an Aβ_(15–40) (D23N mutant) peptide from the surface of a filament along its most probable path (MPP) using all-atom molecular dynamics. This allows for a direct calculation of the free energy profile along the MPP, revealing a multipeak energetic barrier between the free peptide state and the aggregated state. By definition of the MPP, this simulated unbinding process represents the reverse of the physical elongation pathway, allowing us to draw biophysically relevant conclusions from the simulation data. Analyzing the detailed atomistic interactions along the MPP, we identify the atomistic origins of these peaks as resulting from the dock-lock mechanism of filament elongation. Careful analysis of the dynamics of filament elongation could prove key to the development of novel therapeutic strategies for amyloid-related diseases.

Energy Landscapes for the Aggregation of Aβ17-42

The aggregation of the Aβ peptide (Aβ_1-42) to form fibrils is a key feature of Alzheimer's disease. The mechanism is thought to be a nucleation stage followed by an elongation process. The elongation stage involves the consecutive addition of monomers to one end of the growing fibril. The aggregation process proceeds in a stop-and-go fashion and may involve off-pathway aggregates, complicating experimental and computational studies. Here we present exploration of a well-defined region in the free and potential energy landscapes for the Aβ_17-42 pentamer. We find that the ideal aggregation process agrees with the previously reported dock-lock mechanism. We also analyze a large number of additional stable structures located on the multifunnel energy landscape, which constitute kinetic traps. The key contributors to the formation of such traps are misaligned strong interactions, for example the stacking of F19 and F20, as well as entropic contributions. Our results suggest that folding templates for aggregation are a necessity and that aggregation studies could employ such species to obtain a more detailed description of the process.

Elongation affinity, activation barrier, and stability of Aβ42 oligomers/fibrils in physiological saline

Amyloid-beta (Aβ) peptides, Aβ40 and the more neurotoxic Aβ42, have been the subject of many research efforts for Alzheimer's disease. In two recent independent investigations, the atomistic structure of Aβ42 fibril has been clearly established in the S-shaped conformation consisting of three β-sheets stabilized by salt bridges formed between the Lys28 sidechain and the C-terminus of Ala42. This structure distinctively differs from the long-known structure of Aβ40 in the β-hairpin shaped conformation consisting of two β-sheets. Recent in silico investigations based on all-atom models have reached closer agreement with the in vitro measurements of Aβ40 thermodynamics. In this study, we present an in silico investigation of Aβ42 thermodynamics. Using the established force field parameters in seven sets of all-atom simulations, we examined the stability of small Aβ42 oligomers in physiological saline. We computed the elongation affinity of the S-shaped Aβ42 fibril, reaching agreement with the experimental data. We also estimated the Arrhenius activation barrier along the elongation pathway (from the disordered conformation of a free Aβ42 peptide to its S-shaped conformation on a fibril) that amounts to about 16 kcal/mol, which is consistent with the experimental data. Based on these quantitative agreements, we conclude that aggregation of Aβ42 peptides into fibrils is thermodynamically slow without precipitation by extrinsic factors such as heparan sulfate proteoglycan and highlight the possibility to prevent Aβ42 aggregation by eliminating some precipitation factors or by increasing competitive agents to capture and transport free Aβ42 peptides from the cerebrospinal fluid.