Fibril elongation by Aβ(17-42): kinetic network analysis of hybrid-resolution molecular dynamics simulations

Insights into the mechanism of peptide fibril growth on gold surface

Understanding the formation of β-fibrils over the gold surface is of paramount interest in nano-bio-medicinal Chemistry. The intricate mechanism of self-assembly of neurofibrillogenic peptides and their growth over the gold surface remains elusive, as experiments are limited in unveiling the microscopic dynamic details, in particular, at the early stage of the peptide aggregation. In this work, we carried out equilibrium molecular dynamics and enhanced sampling simulations to elucidate the underlying mechanism of the growth of an amyloid-forming sequence of tau fragments over the gold surface. Our results disclose that the collective intermolecular interactions between the peptide chains and peptides with the gold surface facilitate the peptide adsorption, followed by integration, finally leading to the fibril formation.

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.

Growth kinetics of amyloid-like fibrils: An integrated atomistic simulation and continuum theory approach

Amyloid fibrils have long been associated with many neurodegenerative diseases. The conventional picture of the formation and proliferation of fibrils from unfolded proteins comprises primary and secondary nucleation of oligomers followed by elongation and fragmentation thereof. In this work, we first employ extensive all-atom molecular dynamics (MD) simulations of short peptides to investigate the governing processes of fibril growth at the molecular scale. We observe that the peptides in the bulk solution can bind onto and subsequently diffuse along the fibril surface, which leads to fibril elongation via either bulk- or surface-mediated docking mechanisms. Then, to guide the quantitative interpretation of these observations and to provide a more comprehensive picture of the growth kinetics of single fibrils, a continuum model which incorporates the key processes observed in the MD simulations is formulated. The model is employed to investigate how relevant physical parameters affect the kinetics of fibril growth and identify distinct growth regimes. In particular, it is shown that fibrils which strongly bind peptides may undergo a transient exponential growth phase in which the entire fibril surface effectively acts as a sink for peptides. We also demonstrate how the relevant model parameters can be estimated from the MD trajectories. Our results provide compelling evidence that the overall fibril growth rates are determined by both bulk and surface peptide fluxes, thereby contributing to a more fundamental understanding of the growth kinetics of amyloid-like fibrils.

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.

Direct Observation of Seeded Conformational Conversion of hIAPP In Silico Reveals the Mechanisms for Morphological Dependence and Asymmetry of Fibril Growth

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.

EGCG-Mediated Protection of Transthyretin Amyloidosis by Stabilizing Transthyretin Tetramers and Disrupting Transthyretin Aggregates

Transthyretin amyloidosis (ATTR) is a progressive and systemic disease caused by the misfolding and amyloid aggregation of transthyretin (TTR). Stabilizing the TTR tetramers and disrupting the formed TTR aggregation are treated as a promising strategy for the treatment of ATTR. Previous studies have reported that epigallocatechin gallate (EGCG) can participate in the whole process of TTR aggregation to prevent ATTR. However, the interaction mechanism of EGCG in this process is still obscure. In this work, we performed molecular dynamics simulations to investigate the interactions between EGCG and TTR tetramers, and between EGCG and TTR aggregates formed by the V30M mutation. The obtained results suggest that EGCG at the binding site of the V30M TTR tetramer can form stable hydrogen bonds with residues in the flexible AB-loop and EF-helix-loop, which reduces the structural mobility of these regions significantly. Additionally, the polyaromatic property of EGCG contributes to the increasement of hydrophobicity at the binding site and thus makes the tetramer difficult to be solvated and dissociated. For V30M-TTR-generated aggregates, EGCG can promote the dissociation of boundary β-strands by destroying key residue interactions of TTR aggregates. Moreover, EGCG is capable of inserting into the side-chain of residues of neighboring β-strands and disrupting the highly structured aggregates. Taken together, this study elucidates the role of EGCG in preventing TTR amyloidosis, which can provide important theoretical support for the future of drug design for ATTR.

The Amphiphilic Property and Structure of β-Amyloid Peptide Contribute to Its Impacts on the Activities of Horseradish Peroxidase and Alkaline Phosphatase

Recent studies have found that β-amyloid (Aβ) oligomers may play much more important roles than amyloid plaques in the pathogenesis of Alzheimer's disease (AD). However, due to the complexity of Aβ, studying the structural basis of Aβ oligomer toxicity is challenging. Here, we assessed the amphiphilic property and β-hairpin structure of Aβ monomer. The potential impacts of Aβ oligomers and three sequence-modifying peptides on the enzyme activities of horseradish peroxidase (HRP) and alkaline phosphatase (ALP) were further evaluated. We demonstrated that Aβ oligomer possesses the ability to alter the activity of two enzymes. Moreover, modifications on the hydrophobic region and β-turn structure of Aβ monomer significantly alter its impacts on the enzyme activities. In addition, these modifications also change the bonding modes of Aβ monomers or oligomers binding to HRP, as assessed by molecular docking. All of these findings provide direct experimental evidence to reveal the critical roles of the amphiphilic property and β-sheet structure of Aβ monomer in its impacts on protein activity.

Learned Reconstruction of Protein Folding Trajectories from Noisy Single-Molecule Time Series

Single-molecule Förster resonance energy transfer (smFRET) is an experimental methodology to track the real-time dynamics of molecules using fluorescent probes to follow one or more intramolecular distances. These distances provide a low-dimensional representation of the full atomistic dynamics. Under mild technical conditions, Takens' Delay Embedding Theorem guarantees that the full three-dimensional atomistic dynamics of a system are diffeomorphic (i.e., related by a smooth and invertible transformation) to a time-delayed embedding of one or more scalar observables. Appealing to these theoretical guarantees, we employ manifold learning, artificial neural networks, and statistical mechanics to learn from molecular simulation training data the a priori unknown transformation between the atomic coordinates and delay-embedded intramolecular distances accessible to smFRET. This learned transformation may then be used to reconstruct atomistic coordinates from smFRET time series data. We term this approach Single-molecule TAkens Reconstruction (STAR). We have previously applied STAR to reconstruct molecular configurations of a C24H50 polymer chain and the mini-protein Chignolin with accuracies better than 0.2 nm from simulated smFRET data under noise free and high time resolution conditions. In the present work, we investigate the role of signal-to-noise ratio, data volume, and time resolution in simulated smFRET data to assess the performance of STAR under conditions more representative of experimental realities. We show that STAR can reconstruct the Chignolin and Villin mini-proteins to accuracies of 0.12 and 0.42 nm, respectively, and place bounds on these conditions for accurate reconstructions. These results demonstrate that it is possible to reconstruct dynamical trajectories of protein folding from time series in noisy, time binned, experimentally measurable observables and lay the foundations for the application of STAR to real experimental data.

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.

The α-Synuclein Monomer May Have Different Misfolding Mechanisms in the Induction of α-Synuclein Fibrils with Different Polymorphs

The aggregation of alpha-synuclein (α-Syn) is closely related to the occurrence of some neurodegenerative diseases such as Parkinson's disease. The misfolding of α-Syn monomer plays a key role in the formation of aggregates and extension of fibril. However, the misfolding mechanism of α-Syn remains elusive. Here, three different α-Syn fibrils (isolated from a diseased human brain, generated by in vitro cofactor-tau induction, and obtained by in vitro cofactor-free induction) were selected for the study. The misfolding mechanisms of α-Syn were uncovered by studying the dissociation of the boundary chains based on the conventional molecular dynamics (MD) and Steered MD simulations. The results showed that the dissociation paths of the boundary chains in the three systems were different. According to the reverse process of dissociation, we concluded that in the human brain system, the binding of the monomer and template starts from the C-terminal and gradually misfolds toward the N-terminal. In the cofactor-tau system, the monomer binding starts from residues 58-66 (contain β3), followed by the C-terminal coil (residues 67-79). Then, the N-terminal coil (residues 36-41) and residues 50-57 (contain β2) bind to the template, followed by residues 42-49 (contain β1). In the cofactor-free system, two misfolding paths were found. One is that the monomer binds to the N/C-terminal (β1/β6) and then binds to the remaining residues. The other one is that the monomer binds sequentially from the C- to N-terminal, similar to the human brain system. Furthermore, in the human brain and cofactor-tau systems, electrostatic interactions (especially from residues 58-66) are the main driving force during the misfolding process, whereas in the cofactor-free system, the contributions of electrostatic and van der Waals interactions are comparable. These results may provide a deeper understanding for the misfolding and aggregation mechanism of α-Syn.

Role of TM3 in claudin-15 strand flexibility: A molecular dynamics study

Claudins are cell-cell adhesion proteins within tight junctions that connect epithelial cells together. Claudins polymerize into a network of strand-like structures within the membrane of adjoining cells and create ion channels that control paracellular permeability to water and small molecules. Tight junction morphology and barrier function is tissue specific and regulated by claudin subtypes. Here, we present a molecular dynamics study of claudin-15 strands within lipid membranes and the role of a single-point mutation (A134P) on the third transmembrane helix (TM3) of claudin-15 in determining the morphology of the strand. Our results indicate that the A134P mutation significantly affects the lateral flexibility of the strands, increasing the persistence length of claudin-15 strands by a factor of three. Analyses of claudin-claudin contact in our μsecond-long trajectories show that the mutation does not alter the intermolecular contacts (interfaces) between claudins. However, the dynamics and frequency of interfacial contacts are significantly affected. The A134P mutation introduces a kink in TM3 of claudin-15 similar to the one observed in claudin-3 crystal structure. The kink on TM3 skews the rotational flexibility of the claudins in the strands and limits their fluctuation in one direction. This asymmetric movement in the context of the double rows reduces the lateral flexibility of the strand and leads to higher persistence lengths of the mutant.

Scan-Find-Scan-Model: Discrete Site-Targeted Suppressor Design Strategy for Amyloid-β

Alzheimer's disease is undoubtedly the most well-studied neurodegenerative disease. Consequently, the amyloid-β (Aβ) protein ranks at the top in terms of getting attention from the scientific community for structural property-based characterization. Even after decades of extensive research, there is existing volatility in terms of understanding and hence the effective tackling procedures against the disease that arises due to the lack of knowledge of both specific target- and site-specific drugs. Here, we develop a multidimensional approach based on the characterization of the common static-dynamic-thermodynamic trait of the monomeric protein, which efficiently identifies a small target sequence that contains an inherent tendency to misfold and consequently aggregate. The robustness of the identification of the target sequence comes with an abundance of a priori knowledge about the length and sequence of the target and hence guides toward effective designing of the target-specific drug with a very low probability of bottleneck and failure. Based on the target sequence information, we further identified a specific mutant that showed the maximum potential to act as a destabilizer of the monomeric protein as well as enormous success as an aggregation suppressor. We eventually tested the drug efficacy by estimating the extent of modulation of binding affinity existing within the fibrillar form of the Aβ protein due to a single-point mutation and hence provided a proof of concept of the entire protocol.

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

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

Mechanistic Kinetic Model Reveals How Amyloidogenic Hydrophobic Patches Facilitate the Amyloid-β Fibril Elongation

Abnormal aggregation of amyloid β (Aβ) peptides into fibrils plays a critical role in the development of Alzheimer's disease. A two-stage "dock-lock" model has been proposed for the Aβ fibril elongation process. However, the mechanisms of the Aβ monomer-fibril binding process have not been elucidated with the necessary molecular-level precision, so it remains unclear how the lock phase dynamics leads to the overall in-register binding of the Aβ monomer onto the fibril. To gain mechanistic insights into this critical step during the fibril elongation process, we used molecular dynamics (MD) simulations with a physics-based coarse-grained UNited-RESidue (UNRES) force field and sampled extensively the dynamics of the lock phase process, in which a fibril-bound Aβ_(9-40) peptide rearranged to establish the native docking conformation. Analysis of the MD trajectories with Markov state models was used to quantify the kinetics of the rearrangement process and the most probable pathways leading to the overall native docking conformation of the incoming peptide. These revealed a key intermediate state in which an intra-monomer hairpin is formed between the central core amyloidogenic patch ₁₈VFFA₂₁ and the C-terminal hydrophobic patch ₃₄LMVG₃₇. This hairpin structure is highly favored as a transition state during the lock phase of the fibril elongation. We propose a molecular mechanism for facilitation of the Aβ fibril elongation by amyloidogenic hydrophobic patches.

Single-molecule fluorescence imaging and deep learning reveal highly heterogeneous aggregation of amyloid-β 42

There are various diseases caused by protein aggregation such as Alzheimer’s, Parkinson’s, and Huntington’s diseases. From the diversity in the fibril structure, aggregation is expected to occur via heterogeneous pathways. However, characterization of this heterogeneity is extremely difficult because it requires following individual fibril formation in a mixture from early oligomerization stages. In this work, we investigated aggregation of the 42-residue isoform of amyloid β (Aβ42) using single-molecule fluorescence imaging and deep learning. We could track the growth of individual fibrils, which allows for a quantitative description of heterogeneous fibril formation and discovery of a new fibril nucleation mechanism. Further characterization of heterogeneity involving Aβ42 will be important for better understanding the disease mechanism.

Polymorphism in the structure of amyloid fibrils suggests the existence of many different assembly pathways. Characterization of this heterogeneity is the key to understanding the aggregation mechanism and toxicity, but in practice it is extremely difficult to probe individual aggregation pathways in a mixture. Here, we present development of a method combining single-molecule fluorescence lifetime imaging and deep learning for monitoring individual fibril formation in real time and their high-throughput analysis. A deep neural network (FNet) separates an image of highly overlapping fibrils into single fibril images, which allows for tracking the growth and changes in characteristics of individual fibrils. Using this method, we investigated aggregation of the 42-residue amyloid-β peptide (Aβ42). We demonstrate that highly heterogeneous fibril formation can be quantitatively characterized in terms of the number of cross-β subunits, elongation speed, growth polarity, and conformation of fibrils. Tracking individual fibril formation and growth also leads to the discovery of a general nucleation mechanism (termed heterogeneous secondary nucleation), where a fibril is formed on the surface of an oligomer with a different structure. Our development will be broadly applicable to characterization of heterogeneous aggregation processes of other proteins.

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.

Replica permutation with solute tempering for molecular dynamics simulation and its application to the dimerization of amyloid-β fragments

We propose the replica permutation with solute tempering (RPST) by combining the replica-permutation method (RPM) and the replica exchange with solute tempering (REST). Temperature permutations are performed among more than two replicas in RPM, whereas temperature exchanges are performed between two replicas in the replica-exchange method (REM). The temperature transition in RPM occurs more efficiently than in REM. In REST, only the temperatures of the solute region, the solute temperatures, are exchanged to reduce the number of replicas compared to REM. Therefore, RPST is expected to be an improved method taking advantage of these methods. For comparison, we applied RPST, REST, RPM, and REM to two amyloid-β(16–22) peptides in explicit water. We calculated the transition ratio and the number of tunneling events in the temperature space and the number of dimerization events of amyloid-β(16–22) peptides. The results indicate that, in RPST, the number of replicas necessary for frequent random walks in the temperature and conformational spaces is reduced compared to the other three methods. In addition, we focused on the dimerization process of amyloid-β(16–22) peptides. The RPST simulation with a relatively small number of replicas shows that the two amyloid-β(16–22) peptides form the intermolecular antiparallel β-bridges due to the hydrophilic side-chain contact between Lys and Glu and hydrophobic side-chain contact between Leu, Val, and Phe, which stabilizes the dimer of the peptides.

Challenges and frontiers of computational modelling of biomolecular recognition

Biomolecular recognition including binding of small molecules, peptides and proteins to their target receptors plays a key role in cellular function and has been targeted for therapeutic drug design. However, the high flexibility of biomolecules and slow binding and dissociation processes have presented challenges for computational modelling. Here, we review the challenges and computational approaches developed to characterise biomolecular binding, including molecular docking, molecular dynamics simulations (especially enhanced sampling) and machine learning. Further improvements are still needed in order to accurately and efficiently characterise binding structures, mechanisms, thermodynamics and kinetics of biomolecules in the future.

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

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

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

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.

Kinetic and thermodynamic stability comparison for the fibrillar form of small amyloid-β(1-42) oligomers using scaled molecular dynamics

Amyloid-β (Aβ) oligomers act as intermediates for several neurodegenerative disease-relevant fibril formations. However, gaining insight into the oligomer to fibril conversion process remains a challenge due to the transient nature of small Aβ. In this study, we probe the kinetic and thermodynamic stabilities of small Aβ(1-42) oligomers in fibrillar conformations to understand from what size these aggregates start forming stable fibrils. With no definite structures available for small Aβ42 aggregates, we have started with oligomers extracted from mature fibrils having four, five, six and nine chains stacked together, and have performed order-to-disorder transition on these systems. Using scaled molecular dynamics (sMD) simulation, the timescale for breaking the native contacts of fibrils has been compared. The results indicate that the kinetic stability of oligomers increases with size, especially at the C-terminus end beyond five-chain oligomers. The free energy of breaking the contacts at the β-sheet regions in the structures has been obtained on an unscaled potential from a free energy extrapolation (FEE) approach. The values show that although stable minima are obtained for larger oligomers due to the enhanced stability of the C-terminus ends, fully stable fibril formation may require aggregates larger than the ones considered in our study. Additionally, dissimilar kinetics for the unbinding of terminal chains across all the oligomers has been observed. The interaction energy values calculated from unscaled MD simulations reveal the crucial role of water in our observations. Our work provides the application of an easy-to-deploy method that sheds light on interactions which could be significant in the early stages of Aβ42 fibril formation.

Insights into Mechanism of Aβ42 Fibril Growth on Surface of Graphene Oxides: Oxidative Degree Matters

The filamentous β-amyloid deposition has been regarded as the hallmark pathology of Alzheimer's disease (AD). Nanomaterials such as graphene oxides (GOs) have achieved significant progress in the therapy of AD, but the molecular pathway of the growth propagation remains challenging to investigate, especially on the surfaces of materials. The thermodynamics and kinetics of fibril elongation on GO surfaces with different oxidative degrees have been investigated by a combination of in vitro experiments and simulations. ThT kinetics, calorimetric measurements, and TEM observations suggest that low oxidative GO-10 promotes the fibril elongation, while both high oxidative GO-20 and GO-40 inhibit the fibril elongation. Computational results reveal that the apparent regulation behaviors of GOs on filament growth depend on the balance between the promoting effect by templating the incoming of monomers and the retarding effect by capturing the monomer during docking and locking phases through hydrogen bonding. This work will promote the understanding of the interplay between biomolecules and materials, thus providing new thoughts for the rational design of novel materials for amyloidosis therapy.

Molecular dynamics study of water channels in natural and synthetic amyloid-β fibrils

We compared all-atom explicit solvent molecular dynamics simulations of three types of Aβ(1-40) fibrils: brain-seeded fibrils (2M4J, with a threefold axial symmetry) and the other two, all-synthetic fibril polymorphs (2LMN and 2LMP, made under different fibrillization conditions). Fibril models were constructed using either a finite or an infinite number of layers made using periodic images. These studies yielded four conclusions. First, finite fibrils tend to unravel in a manner reminiscent of fibril dissolution, while infinite fibrils were more stable during simulations. Second, salt bridges in these fibrils remained stable in those fibrils that contained them initially, and those without salt bridges did not develop them over the time course of the simulations. Third, all fibrils tended to develop a "stagger" or register shift of β-strands along the fibril axis. Fourth and most importantly, the brain-seeded, 2M4J, infinite fibrils allowed bidirectional transport of water in and out of the central longitudinal core of the fibril by rapidly developing gaps at the fibril vertices. 2LMP fibrils also showed this behavior, although to a lesser extent. The diffusion of water molecules in the fibril core region involved two dynamical states: a localized state and directed diffusion in the presence of obstacles. These observations provided support for the hypothesis that Aβ fibrils could act as nanotubes. At least some Aβ oligomers resembled fibrils structurally in having parallel, in-register β-sheets and a sheet-turn-sheet motif. Thus, our findings could have implications for Aβ cytotoxicity, which may occur through the ability of oligomers to form abnormal water and ion channels in cell membranes.

Multiscale Models for Fibril Formation: Rare Events Methods, Microkinetic Models, and Population Balances

Amyloid fibrils are thought to grow by a two-step dock-lock mechanism. However, previous simulations of fibril formation (i) overlook the bi-molecular nature of the docking step and obtain rates with first-order units, or (ii) superimpose the docked and locked states when computing the potential of mean force for association and thereby muddle the docking and locking steps. Here, we developed a simple microkinetic model with separate locking and docking steps and with the appropriate concentration dependences for each step. We constructed a simple model comprised of chiral dumbbells that retains qualitative aspects of fibril formation. We used rare events methods to predict separate docking and locking rate constants for the model. The rate constants were embedded in the microkinetic model, with the microkinetic model embedded in a population balance model for “bottom-up” multiscale fibril growth rate predictions. These were compared to “top-down” results using simulation data with the same model and multiscale framework to obtain maximum likelihood estimates of the separate lock and dock rate constants. We used the same procedures to extract separate docking and locking rate constants from experimental fibril growth data. Our multiscale strategy, embedding rate theories, and kinetic models in conservation laws should help to extract docking and locking rate constants from experimental data or long molecular simulations with correct units and without compromising the molecular description.

Role of Water Molecules and Helix Structure Stabilization in the Laser-Induced Disruption of Amyloid Fibrils Observed by Nonequilibrium Molecular Dynamics Simulations

Water plays a crucial role in the formation and destruction of biomolecular structures. The mechanism for destroying biomolecular structures was thought to be an active breaking of hydrogen bonds by water molecules. However, using nonequilibrium molecular dynamics simulations, in which an amyloid-β amyloid fibril was destroyed via infrared free-electron laser (IR-FEL) irradiation, we discovered a new mechanism, in which water molecules disrupt protein aggregates. The intermolecular hydrogen bonds formed by C═O and N-H in the fibril are broken at each pulse of laser irradiation. These bonds spontaneously re-form after the irradiation in many cases. However, when a water molecule happens to enter the gap between C═O and N-H, it inhibits the re-formation of the hydrogen bonds. Such sites become defects in the regularly aligned hydrogen bonds, from which all hydrogen bonds in the intermolecular β-sheet are broken as the fraying spreads. This role of water molecules is entirely different from other known mechanisms. This new mechanism can explain the recent experiments showing that the amyloid fibrils are not destroyed by laser irradiation under dry conditions. Additionally, we found that helix structures form more after the amyloid disruption; this is because the resonance frequency is different in a helix structure. Our findings provide a theoretical basis for the application of IR-FEL to the future treatment of amyloidosis.

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

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

β-sheet breakers with consecutive phenylalanines: Insights into mechanism of dissolution of β-amyloid fibrils

β-sheet breakers (BSB) constitute a class of peptide inhibitors of amyloidogenesis, a process which is a hallmark of many diseases called amyloidoses, including Alzheimer's disease (AD); however, the molecular details of their action are still not fully understood. Here we describe the results of the computational investigation of the three BSBs, iaβ6 (LPFFFD), iaβ5 (LPFFD), and iaβ6_Gly (LPFGFD), in complex with the fibril model of Aβ42 and propose the kinetically probable mechanism of their action. The mechanism involves the binding of BSB to the central hydrophobic core (CHC) region (LVFFA) of Aβ fibril and the π-stacking of its Phe rings both internally and with the Aβ fibril. In the process, the Aβ fibril undergoes distortion accumulating on the side of chain A (located on the odd tip of the fibril). In a single replica of extended molecular dynamics run of one of the iaβ6 poses, the distortion concludes in a dissociation of chain A from the fibril model of Aβ42. Altogether, we postulate that including consecutive Phe residues into BSBs docked around Phe 20 in the CHC region of Aβ42 improve their potency for dissolution of fibrils.

Structural analysis of the β-sheet edge of peptide self-assembly using a model protein

Peptides and proteins self-assemble into β-sheet-rich fibrils, amyloid, which extends its structure by incorporating peptide/protein molecules from solution. At the elongation edge, the peptide/protein molecule binds to the edge of the amyloid β-sheet. Such processes are transient and elusive when observing molecular details by experimental methods. We used a model protein system, peptide self-assembly mimic (PSAM), which mimics an amyloid-like structure within a globular protein by capping both edges of single-layer β sheet (SLB) with certain domains. We constructed a PSAM variant that lacks the capping domain on the C-terminal side to observe the structure of the β-sheet edge of the peptide self-assembly. This variant, which we termed PSAM-edge, proved to be soluble with a monomeric form. Urea-induced unfolding experiments revealed that PSAM-edge displayed two-state cooperative unfolding, indicating the N-terminal capping domain and extended SLB folded as one unit. The crystal structure showed that SLB was almost completely structured except for a few terminal residues. A molecular dynamics simulation results revealed that the SLB structure was retained while the C-terminal four residues fluctuated, which was consistent with the crystal structure. Our findings indicate that SLB is stable even when one side of the β-sheet edge is exposed to a solvent. This stability may prevent the dissociation of the attached peptide from the peptide self-assembly. Because of the scarcity of SLB proteins with exposed β-sheet edges in nature, successful construction of the PSAM-edge expands our understanding of protein folding and design.

Promotion and Inhibition of Amyloid-β Peptide Aggregation: Molecular Dynamics Studies

Aggregates of amyloid-β (Aβ) peptides are known to be related to Alzheimer’s disease. Their aggregation is enhanced at hydrophilic–hydrophobic interfaces, such as a cell membrane surface and air-water interface, and is inhibited by polyphenols, such as myricetin and rosmarinic acid. We review molecular dynamics (MD) simulation approaches of a full-length Aβ peptide, Aβ40, and Aβ(16–22) fragments in these environments. Since these peptides have both hydrophilic and hydrophobic amino acid residues, they tend to exist at the interfaces. The high concentration of the peptides accelerates the aggregation there. In addition, Aβ40 forms a β-hairpin structure, and this structure accelerates the aggregation. We also describe the inhibition mechanism of the Aβ(16–22) aggregation by polyphenols. The aggregation of Aβ(16–22) fragments is caused mainly by the electrostatic attraction between charged amino acid residues known as Lys16 and Glu22. Since polyphenols form hydrogen bonds between their hydroxy and carboxyl groups and these charged amino acid residues, they inhibit the aggregation.

Effects of Ions and Small Compounds on the Structure of Aβ42 Monomers

Aggregation of amyloid-β (Aβ) proteins in the brain is a hallmark of Alzheimer's disease. This phenomenon can be promoted or inhibited by adding small molecules to the solution where Aβ is embedded. These molecules affect the ensemble of conformations sampled by Aβ monomers even before aggregation starts. Here, we perform extensive all-atom replica exchange molecular dynamics (REMD) simulations to provide a comparative study of the ensemble of conformations sampled by Aβ₄₂ monomers in solutions that promote (i.e., aqueous solution containing NaCl) and inhibit (i.e., aqueous solutions containing scyllo-inositol or 4-aminophenol) aggregation. Simulations performed in pure water are used as our reference. We find that secondary-structure content is only affected in an antagonistic manner by promoters and inhibitors at the C-terminus and the central hydrophilic core. Moreover, the end of the C-terminus binds more favorably to the central hydrophobic core region of Aβ₄₂ in NaCl adopting a type of strand-loop-strand structure that is disfavored by inhibitors. Nonpolar residues that form the dry core of larger aggregates of Aβ₄₂ (e.g., PDB ID 2BEG) are found at close proximity in these strand-loop-strand structures, suggesting that their formation could play an important role in initiating nucleation. In the presence of inhibitors, the C-terminus binds the central hydrophilic core with a higher probability than in our reference simulation. This sensitivity of the C-terminus, which is affected in an antagonistic manner by inhibitors and promoters, provides evidence for its critical role in accounting for aggregation.

Amyloid-Like Peptide Aggregates

Self-assembly of proteins and peptides into the amyloid fold is a widespread phenomenon in the natural world. The structural hallmark of self-assembly into amyloid fibrillar assemblies is the cross-beta motif, which conveys distinct morphological and mechanical properties. The amyloid fibril formation has contrasting results depending on the organism, in the sense that it can bestow an organism with the advantages of mechanical strength and improved functionality or, on the contrary, could give rise to pathological states. In this chapter we review the existing information on amyloid-like peptide aggregates, which could either be derived from protein sequences, but also could be rationally or de novo designed in order to self-assemble into amyloid fibrils under physiological conditions. Moreover, the development of self-assembled fibrillar biomaterials that are tailored for the desired properties towards applications in biomedical or environmental areas is extensively analyzed. We also review computational studies predicting the amyloid propensity of the natural amino acid sequences and the structure of amyloids, as well as designing novel functional amyloid materials.

A simple method for modeling amyloid kinetics featuring position biased fiber breakage

A mathematical model of amyloid fiber formation is described that is able to simply specify different rates of fiber breakage at internal versus end regions. This Note presents the derivation of the relevant equations and provides results showing the dramatic effects of position biased fiber breakage on the kinetics of amyloid growth.

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.

How Does the Mono-Triazole Derivative Modulate Aβ42 Aggregation and Disrupt a Protofibril Structure: Insights from Molecular Dynamics Simulations

Clinical studies have identified that abnormal self-assembly of amyloid-β (Aβ) peptide into toxic fibrillar aggregates is associated with the pathology of Alzheimer's disease (AD). The most acceptable therapeutic approach to stop the progression of AD is to inhibit the formation of β-sheet-rich structures. Recently, we designed and evaluated a series of novel mono-triazole derivatives 4(a-x), where compound 4v was identified as the most potent inhibitor of Aβ₄₂ aggregation and disaggregates preformed Aβ₄₂ fibrils significantly. Moreover, 4v strongly averts the Cu²⁺-induced Aβ₄₂ aggregation and disaggregates the preformed Cu²⁺-induced Aβ₄₂ fibrils, halts the generation of reactive oxygen species, and shows neuroprotective effects in SH-SY5Y cells. However, the underlying molecular mechanism of inhibition of Aβ₄₂ aggregation by 4v and disaggregation of preformed Aβ₄₂ fibrils remains obscure. In this work, molecular dynamics (MD) simulations have been performed to explore the conformational ensemble of the Aβ₄₂ monomer and a pentameric protofibril structure of Aβ₄₂ in the presence of 4v. The MD simulations highlighted that 4v binds preferentially at the central hydrophobic core region of the Aβ₄₂ monomer and chains D and E of the Aβ₄₂ protofibril. The dictionary of secondary structure of proteins analysis indicated that 4v retards the conformational conversion of the helix-rich structure of the Aβ₄₂ monomer into the aggregation-prone β-sheet conformation. The binding free energy calculated by the molecular mechanics Poisson-Boltzmann surface area method revealed an energetically favorable process with ΔG _binding = -44.9 ± 3.3 kcal/mol for the Aβ₄₂ monomer-4v complex. The free energy landscape analysis highlighted that the Aβ₄₂ monomer-4v complex sampled conformations with significantly higher helical contents (35 and 49%) as compared to the Aβ₄₂ monomer alone (17%). Compound 4v displayed hydrogen bonding with Gly37 (chain E) and π-π interactions with Phe19 (chain D) of the Aβ₄₂ protofibril. Further, the per-residue binding free energy analysis also highlighted that Phe19 (chain D) and Gly37 (chain E) of the Aβ₄₂ protofibril showed the maximum contribution in the binding free energy. The decreased binding affinity and residue-residue contacts between chains D and E of the Aβ₄₂ protofibril in the presence of 4v indicate destabilization of the Aβ₄₂ protofibril structure. Overall, the structural information obtained through MD simulations indicated that 4v stabilizes the native helical conformation of the Aβ₄₂ monomer and persuades a destabilization in the protofibril structure of Aβ₄₂. The results of the study will be useful in the rational design of potent inhibitors against amyloid aggregation.

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.

Complete aggregation pathway of amyloid β (1-40) and (1-42) resolved on an atomically clean interface

To visualize amyloid β (Aβ) aggregates requires an uncontaminated and artifact-free interface. This paper demonstrates the interface between graphene and pure water (verified to be atomically clean using tunneling microscopy) as an ideal platform for resolving size, shape, and morphology (measured by atomic force microscopy) of Aβ-40 and Aβ-42 peptide assemblies from 0.5 to 150 hours at a 5-hour time interval with single-particle resolution. After confirming faster aggregation of Aβ-42 in comparison to Aβ-40, a stable set of oligomers with a diameter distribution of ~7 to 9 nm was prevalently observed uniquely for Aβ-42 even after fibril appearance. The interaction energies between a distinct class of amyloid aggregates (dodecamers) and graphene was then quantified using molecular dynamics simulations. Last, differences in Aβ-40 and Aβ-42 networks were resolved, wherein only Aβ-42 fibrils were aligned through lateral interactions over micrometer-scale lengths, a property that could be exploited in the design of biofunctional materials.

Folding dynamics of Aβ42 monomer at pH 4.0–7.5 with and without physiological salt conditions – does the β1 or β2 region fold first?

The seeding region of Aβ42 monomer is jointly affected by the solution acidity, ionic distribution of the salt, and charged residues.

Exploration of the Misfolding Mechanism of Transthyretin Monomer: Insights from Hybrid-Resolution Simulations and Markov State Model Analysis

Misfolding and aggregation of transthyretin (TTR) is widely known to be responsible for a progressive systemic disorder called amyloid transthyretin (ATTR) amyloidosis. Studies suggest that TTR aggregation is initiated by a rate-limiting dissociation of the homo-tetramer into its monomers, which can rapidly misfold and self-assemble into amyloid fibril. Thus, exploring conformational change involved in TTR monomer misfolding is of vital importance for understanding the pathogenesis of ATTR amyloidosis. In this work, microsecond timescale hybrid-resolution molecular dynamics (MD) simulations combined with Markov state model (MSM) analysis were performed to investigate the misfolding mechanism of the TTR monomer. The results indicate that a macrostate with partially unfolded conformations may serve as the misfolded state of the TTR monomer. This misfolded state was extremely stable with a very large equilibrium probability of about 85.28%. With secondary structure analysis, we found the DAGH sheet in this state to be significantly destroyed. The CBEF sheet was relatively stable and sheet structure was maintained. However, the F-strand in this sheet was likely to move away from E-strand and reform a new β-sheet with the H-strand. This observation is consistent with experimental finding that F and H strands in the outer edge drive the misfolding of TTR. Finally, transition pathways from a near native state to this misfolded macrostate showed that the conformational transition can occur either through a native-like β-sheet intermediates or through partially unfolded intermediates, while the later appears to be the main pathway. As a whole, we identified a potential misfolded state of the TTR monomer and elucidated the misfolding pathway for its conformational transition. This work can provide a valuable theoretical basis for understanding of TTR aggregation and the pathogenesis of ATTR amyloidosis at the atomic level.

Why Aβ42 Is Much More Toxic than Aβ40

Amyloid precursor A4 (770 amino acids (aa)) dimerizes and aggregates, as do its C-terminal (99 aa) and amyloid Aβ (40,42 aa Aβ40,Aβ42) fragments. The titled question has been discussed extensively, and here it is addressed further using thermodynamic scaling theory to analyze mutational trends in structural factors and kinetics. Special attention is given to Family Alzheimer's disease mutations in C99 outside Aβ42 centered on Aβ46. The scaling analysis is connected to extensive C99 docking simulations which included membranes ( Sun et al. J. Chem. Inf. Model. 2017 , 57 , 1375 - 1387 ), thereby confirming their C99 results and extending them to A4.

Disclosing the Template-Induced Misfolding Mechanism of Tau Protein by Studying the Dissociation of the Boundary Chain from the Formed Tau Fibril Based on a Steered Molecular Dynamics Simulation

The level of tau aggregation into neurofibrillary tangles, including paired helical filament (PHF) and straight filament (SF), is closely associated with Alzheimer's disease. Despite the pathological importance of misfolding and aggregation of tau, the corresponding mechanism remains unclear. Therefore, to uncover the misfolding mechanism of the tau monomer upon induction of formed PHF and SF, in this study, a conventional molecular dynamics simulation combined with a steered molecular dynamics simulation was performed to study the dissociation of the boundary chain. Interestingly, our results show that the dissociation mechanisms of the boundary chain in PHF and SF are different. In PHF, the boundary chain begins to dissociate from regions β2 and β3 and ends at β8. However, in SF, it is simultaneously dissociated from β1 and β8 and ends at β5. The dissociation of the boundary chain is the reverse of template-induced misfolding of the monomer. Therefore, we can deduce the misfolding mechanism of the monomer upon induction of the template. For PHF, β8 first interacts with the template by hydrophobic interaction. Then β7, β6, β5, β4, and β1 sequentially bind to the template by electrostatic and hydrophobic interactions. After β1 binds to the template, β2 and β3 very quickly bind to the template through hydrophobic interaction. For SF, β5 of the monomer first interacts with the template by electrostatic attraction. Then β4 and β6, β3 and β7, and β2 and β8 bind to the template in turn. Finally, β1 and β8 are fully bound to the template by hydrophobic interaction. The obtained results will be vital for understanding the earlier events during misfolding and aggregation of tau.

On the removal of initial state bias from simulation data

Classical atomistic simulations of biomolecules play an increasingly important role in molecular life science. The structure of current computing architectures favors methods that run multiple trajectories at once without requiring extensive communication between them. Many advanced sampling strategies in the field fit this mold. These approaches often rely on an adaptive logic and create ensembles of comparatively short trajectories whose starting points are not distributed according to the correct Boltzmann weights. This type of bias is notoriously difficult to remove, and Markov state models (MSMs) are one of the few strategies available for recovering the correct kinetics and thermodynamics from these ensembles of trajectories. In this contribution, we analyze the performance of MSMs in the thermodynamic reweighting task for a hierarchical set of systems. We show that MSMs can be rigorous tools to recover the correct equilibrium distribution for systems of sufficiently low dimensionality. This is conditional upon not tampering with local flux imbalances found in the data. For a real-world application, we find that a pure likelihood-based inference of the transition matrix produces the best results. The removal of the bias is incomplete, however, and for this system, all tested MSMs are outperformed by an alternative albeit less general approach rooted in the ideas of statistical resampling. We conclude by formulating some recommendations for how to address the reweighting issue in practice.

Top-down Multiscale Approach To Simulate Peptide Self-Assembly from Monomers

Modeling peptide assembly from monomers on large time and length scales is often intractable at the atomistic resolution. To address this challenge, we present a new approach which integrates coarse-grained (CG), mixed-resolution, and all-atom (AA) modeling in a single simulation. We simulate the initial encounter stage with the CG model, while the further assembly and reorganization stages are simulated with the mixed-resolution and AA models. We have implemented this top-down approach with new tools to automate model transformations and to monitor oligomer formations. Further, a theory was developed to estimate the optimal simulation length for each stage using a model peptide, melittin. The assembly level, the oligomer distribution, and the secondary structures of melittin simulated by the optimal protocol show good agreement with prior experiments and AA simulations. Finally, our approach and theory have been successfully validated with three amyloid peptides (β-amyloid 16-22, GNNQQNY fragment from the yeast prion protein SUP35, and α-synuclein fibril 35-55), which highlight the synergy from modeling at multiple resolutions. This work not only serves as proof of concept for multiresolution simulation studies but also presents practical guidelines for further self-assembly simulations at more physically and chemically relevant scales.

On the Applicability of Force Fields To Study the Aggregation of Amyloidogenic Peptides Using Molecular Dynamics Simulations

Molecular dynamics simulations play an essential role in understanding biomolecular processes such as protein aggregation at temporal and spatial resolutions which are not attainable by experimental methods. For a correct modeling of protein aggregation, force fields must accurately represent molecular interactions. Here, we study the effect of five different force fields on the oligomer formation of Alzheimer's Aβ_16-22 peptide and two of its mutants: Aβ_16-22(F19V,F20V), which does not form fibrils, and Aβ_16-22(F19L) which forms fibrils faster than the wild type. We observe that while oligomer formation kinetics depends strongly on the force field, structural properties, such as the most relevant protein-protein contacts, are similar between them. The oligomer formation kinetics obtained with different force fields differ more from each other than the kinetics between aggregating and nonaggregating peptides simulated with a single force field. We discuss the difficulties in comparing atomistic simulations of amyloid oligomer formation with experimental observables.