Elucidating Important Sites and the Mechanism for Amyloid Fibril Formation by Coarse-Grained Molecular Dynamics

Pragmatic Coarse-Graining of Proteins: Models and Applications

The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role in the field. However, biological processes involving large-scale protein assemblies or long time scale dynamics are still computationally expensive to study in atomistic detail. For these applications, employing coarse-grained (CG) modeling approaches has become a key strategy. In this Review, we provide an overview of what we call pragmatic CG protein models, which are strategies combining, at least in part, a physics-based implementation and a top-down experimental approach to their parametrization. In particular, we focus on CG models in which most protein residues are represented by at least two beads, allowing these models to retain some degree of chemical specificity. A description of the main modern pragmatic protein CG models is provided, including a review of the most recent applications and an outlook on future perspectives in the field.

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.

Early Stages of RNA-Mediated Conversion of Human Prions

Prion diseases are characterized by the conversion of prion proteins from a PrPC fold into a disease-causing PrPSC form that is self-replicating. A possible agent to trigger this conversion is polyadenosine RNA, but both mechanism and pathways of the conversion are poorly understood. Using coarse-grained molecular dynamic simulations we study the time evolution of PrPC over 600 μs. We find that both the D178N mutation and interacting with polyadenosine RNA reduce the helicity of the protein and encourage formation of segments with strand-like motifs. We conjecture that these transient β-strands nucleate the conversion of the protein to the scrapie conformation PrPSC.

Prediction of Aggregation of Biologically-Active Peptides with the UNRES Coarse-Grained Model

The UNited RESidue (UNRES) model of polypeptide chains was applied to study the association of 20 peptides with sizes ranging from 6 to 32 amino-acid residues. Twelve of those were potentially aggregating hexa- or heptapeptides excised from larger proteins, while the remaining eight contained potentially aggregating sequences, functionalized by attaching larger ends rich in charged residues. For 13 peptides, the experimental data of aggregation were used. The remaining seven were synthesized, and their properties were measured in this work. Multiplexed replica-exchange simulations of eight-chain systems were conducted at 12 temperatures from 260 to 370 K at concentrations from 0.421 to 5.78 mM, corresponding to the experimental conditions. The temperature profiles of the fractions of monomers and octamers showed a clear transition corresponding to aggregate dissociation. Low simulated transition temperatures were obtained for the peptides, which did not precipitate after incubation, as well as for the H-GNNQQNY-NH2 prion–protein fragment, which forms small fibrils. A substantial amount of inter-strand β-sheets was found in most of the systems. The results suggest that UNRES simulations can be used to assess peptide aggregation except for glutamine- and asparagine-rich peptides, for which a revision of the UNRES sidechain–sidechain interaction potentials appears necessary.

Wild-Type α-Synuclein and Variants Occur in Different Disordered Dimers and Pre-Fibrillar Conformations in Early Stage of Aggregation

α-Synuclein is a 140 amino-acid intrinsically disordered protein mainly found in the brain. Toxic α-synuclein aggregates are the molecular hallmarks of Parkinson’s disease. In vitro studies showed that α-synuclein aggregates in oligomeric structures of several 10th of monomers and into cylindrical structures (fibrils), comprising hundred to thousands of proteins, with polymorphic cross-β-sheet conformations. Oligomeric species, formed at the early stage of aggregation remain, however, poorly understood and are hypothezised to be the most toxic aggregates. Here, we studied the formation of wild-type (WT) and mutant (A30P, A53T, and E46K) dimers of α-synuclein using coarse-grained molecular dynamics. We identified two principal segments of the sequence with a higher propensity to aggregate in the early stage of dimerization: residues 36–55 and residues 66–95. The transient α-helices (residues 53–65 and 73–82) of α-synuclein monomers are destabilized by A53T and E46K mutations, which favors the formation of fibril native contacts in the N-terminal region, whereas the helix 53–65 prevents the propagation of fibril native contacts along the sequence for the WT in the early stages of dimerization. The present results indicate that dimers do not adopt the Greek key motif of the monomer fold in fibrils but form a majority of disordered aggregates and a minority (9–15%) of pre-fibrillar dimers both with intra-molecular and intermolecular β-sheets. The percentage of residues in parallel β-sheets is by increasing order monomer < disordered dimers < pre-fibrillar dimers. Native fibril contacts between the two monomers are present in the NAC domain for WT, A30P, and A53T and in the N-domain for A53T and E46K. Structural properties of pre-fibrillar dimers agree with rupture-force atomic force microscopy and single-molecule Förster resonance energy transfer available data. This suggests that the pre-fibrillar dimers might correspond to the smallest type B toxic oligomers. The probability density of the dimer gyration radius is multi-peaks with an average radius that is 10 Å larger than the one of the monomers for all proteins. The present results indicate that even the elementary α-synuclein aggregation step, the dimerization, is a complicated phenomenon that does not only involve the NAC region.

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.

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.

Probing Protein Aggregation Using the Coarse-Grained UNRES Force Field

Protein aggregation is the cause of many, often lethal, diseases, including the Alzheimer's, Parkinson's, and Huntington's diseases, and familial amyloidosis. Theoretical investigation of the mechanism of this process, including the structures of the oligomeric intermediates which are the most toxic, is difficult because of long time scale of aggregation. Coarse-grained models, which enable us to extend the simulation time scale by three or more orders of magnitude, are, therefore, of great advantage in such studies. In this chapter, we describe the application of the physics-based UNited RESidue (UNRES) force field developed in our laboratory to study protein aggregation, in both free simulations and simulations of aggregation propagation from an existing template (seed), and illustrate it with the examples of Aβ-peptide aggregation and Aβ-peptide-assisted aggregation of the peptides derived from the repeat domains of tau (TauRD).

Computational Models for the Study of Protein Aggregation

Protein aggregation has been studied by many groups around the world for many years because it can be the cause of a number of neurodegenerative diseases that have no effective treatment. Obtaining the structure of related fibrils and toxic oligomers, as well as describing the pathways and main factors that govern the self-organization process, is of paramount importance, but it is also very difficult. To solve this problem, experimental and computational methods are often combined to get the most out of each method. The effectiveness of the computational approach largely depends on the construction of a reasonable molecular model. Here we discussed different versions of the four most popular all-atom force fields AMBER, CHARMM, GROMOS, and OPLS, which have been developed for folded and intrinsically disordered proteins, or both. Continuous and discrete coarse-grained models, which were mainly used to study the kinetics of aggregation, are also summarized.

An Overview of Several Inhibitors for Alzheimer's Disease: Characterization and Failure

Amyloid beta (Aβ) oligomers are the most neurotoxic aggregates causing neuronal death and cognitive damage. A detailed elucidation of the aggregation pathways from oligomers to fibril formation is crucial to develop therapeutic strategies for Alzheimer's disease (AD). Although experimental techniques rely on the measure of time- and space-average properties, they face severe difficulties in the investigation of Aβ peptide aggregation due to their intrinsically disorder character. Computer simulation is a tool that allows tracing the molecular motion of molecules; hence it complements Aβ experiments, as it allows to explore the binding mechanism between metal ions and Aβ oligomers close to the cellular membrane at the atomic resolution. In this context, integrated studies of experiments and computer simulations can assist in mapping the complete pathways of aggregation and toxicity of Aβ peptides. Aβ oligomers are disordered proteins, and due to a rapid exploration of their intrinsic conformational space in real-time, they are challenging therapeutic targets. Therefore, no good drug candidate could have been identified for clinical use. Our previous investigations identified two small molecules, M30 (2-Octahydroisoquinolin-2(1H)-ylethanamine) and Gabapentin, capable of Aβ binding and inhibiting molecular aggregation, synaptotoxicity, intracellular calcium signaling, cellular toxicity and memory losses induced by Aβ. Thus, we recommend these molecules as novel candidates to assist anti-AD drug discovery in the near future. This review discusses the most recent research investigations about the Aβ dynamics in water, close contact with cell membranes, and several therapeutic strategies to remove plaque formation.

From System Modeling to System Analysis: The Impact of Resolution Level and Resolution Distribution in the Computer-Aided Investigation of Biomolecules

The ever increasing computer power, together with the improved accuracy of atomistic force fields, enables researchers to investigate biological systems at the molecular level with remarkable detail. However, the relevant length and time scales of many processes of interest are still hardly within reach even for state-of-the-art hardware, thus leaving important questions often unanswered. The computer-aided investigation of many biological physics problems thus largely benefits from the usage of coarse-grained models, that is, simplified representations of a molecule at a level of resolution that is lower than atomistic. A plethora of coarse-grained models have been developed, which differ most notably in their granularity; this latter aspect determines one of the crucial open issues in the field, i.e. the identification of an optimal degree of coarsening, which enables the greatest simplification at the expenses of the smallest information loss. In this review, we present the problem of coarse-grained modeling in biophysics from the viewpoint of system representation and information content. In particular, we discuss two distinct yet complementary aspects of protein modeling: on the one hand, the relationship between the resolution of a model and its capacity of accurately reproducing the properties of interest; on the other hand, the possibility of employing a lower resolution description of a detailed model to extract simple, useful, and intelligible information from the latter.

On the Conformational Dynamics of β-Amyloid Forming Peptides: A Computational Perspective

Understanding the conformational dynamics of proteins and peptides involved in important functions is still a difficult task in computational structural biology. Because such conformational transitions in β-amyloid (Aβ) forming peptides play a crucial role in many neurological disorders, researchers from different scientific fields have been trying to address issues related to the folding of Aβ forming peptides together. Many theoretical models have been proposed in the recent years for studying Aβ peptides using mathematical, physicochemical, and molecular dynamics simulation, and machine learning approaches. In this article, we have comprehensively reviewed the developmental advances in the theoretical models for Aβ peptide folding and interactions, particularly in the context of neurological disorders. Furthermore, we have extensively reviewed the advances in molecular dynamics simulation as a tool used for studying the conversions between polymorphic amyloid forms and applications of using machine learning approaches in predicting Aβ peptides and aggregation-prone regions in proteins. We have also provided details on the theoretical advances in the study of Aβ peptides, which would enhance our understanding of these peptides at the molecular level and eventually lead to the development of targeted therapies for certain acute neurological disorders such as Alzheimer's disease in the future.

Scale-consistent approach to the derivation of coarse-grained force fields for simulating structure, dynamics, and thermodynamics of biopolymers

In this chapter the scale-consistent approach to the derivation of coarse-grained force fields developed in our laboratory is presented, in which the effective energy function originates from the potential of mean force of the system under consideration and embeds atomistically detailed interactions in the resulting energy terms through use of Kubo's cluster-cumulant expansion, appropriate selection of the major degrees of freedom to be averaged out in the derivation of analytical approximations to the energy terms, and appropriate expression of the interaction energies at the all-atom level in these degrees of freedom. Our approach enables the developers to find correct functional forms of the effective coarse-grained energy terms, without having to import them from all-atom force fields or deriving them on a heuristic basis. In particular, the energy terms derived in such a way exhibit correct dependence on coarse-grained geometry, in particular on site orientation. Moreover, analytical formulas for the multibody (correlation) terms, which appear to be crucial for coarse-grained modeling of many of the regular structures such as, e.g., protein α-helices and β-sheets, can be derived in a systematic way. Implementation of the developed theory to the UNIfied COarse-gRaiNed (UNICORN) model of biological macromolecules, which consists of the UNRES (for proteins), NARES-2P (for nucleic acids), and SUGRES-1P (for polysaccharides) components, and is being developed in our laboratory is described. Successful applications of UNICORN to the prediction of protein structure, simulating the folding and stability of proteins and nucleic acids, and solving biological problems are discussed.

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.

Recent Advances in Coarse-Grained Models for Biomolecules and Their Applications

Molecular dynamics simulations have emerged as a powerful tool to study biological systems at varied length and timescales. The conventional all-atom molecular dynamics simulations are being used by the wider scientific community in routine to capture the conformational dynamics and local motions. In addition, recent developments in coarse-grained models have opened the way to study the macromolecular complexes for time scales up to milliseconds. In this review, we have discussed the principle, applicability and recent development in coarse-grained models for biological systems. The potential of coarse-grained simulation has been reviewed through state-of-the-art examples of protein folding and structure prediction, self-assembly of complexes, membrane systems and carbohydrates fiber models. The multiscale simulation approaches have also been discussed in the context of their emerging role in unravelling hierarchical level information of biosystems. We conclude this review with the future scope of coarse-grained simulations as a constantly evolving tool to capture the dynamics of biosystems.

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.

Copper(II) complexation by fragment of central part of FBP28 protein from Mus musculus

Steady-state and time-resolved fluorescence spectroscopy, UV spectrophotometry and isothermal titration calorimetry techniques were used to study the coordinating properties of the 17aa peptide fragment (D17) derived from the central part of the mouse formin binding protein (FBP28 with the PDB code: 1E0L) towards Cu²⁺ ions. All the measurements were run in the 2-(N-morpholino)ethanesulfonic acid buffer (20 mM, pH 6.0). Under experimental conditions the formation of the 1:1 complex of Cu²⁺ ions with D17 is an entropy-driven process. Cu²⁺ ions cause the static fluorescence quenching of the peptide studied through the formation of a non-fluorescent complex. Furthermore, the thermal stability of D17 was discussed based on the results obtained from differential scanning fluorimetry (nanoDSF) data.

Dependence of the Formation of Tau and Aβ Peptide Mixed Aggregates on the Secondary Structure of the N-Terminal Region of Aβ

One of the hallmarks of Alzheimer's disease is the formation of aggregates of the tau protein, a process that can be facilitated by the presence of fibrils formed by the amyloid β peptide (Aβ). However, the mechanism that triggers tau aggregation is still a matter of debate. The effect of Aβ₄₀ fibrils on the aggregation of the repeat domain of tau (TauRD) is investigated here by employing coarse-grained molecular dynamics simulations. The results indicate that the repeat domain of tau has a high affinity for Aβ₄₀ fibrils, with the ₂₆₁GSTENLK₂₆₇ fragment of tau driving TauRD toward the ₁₆KLVFFA₂₁ fragment in Aβ₄₀. Monomeric Aβ₄₀, in which the ₁₆KLVFFA₂₁ fragment is rarely found in an extended conformation (as in the fibril), has a low affinity for the TauRD, indicating that the ability of Aβ₄₀ fibrils to bind to the TauRD depends on the ₁₆KLVFFA₂₁ fragment of Aβ adopting an extended conformation.

Conversion between parallel and antiparallel β-sheets in wild-type and Iowa mutant Aβ40 fibrils

Using a variant of Hamilton-replica-exchange, we study for wild type and Iowa mutant Aβ₄₀ the conversion between fibrils with antiparallel β-sheets and such with parallel β-sheets. We show that wild type and mutant form distinct salt bridges that in turn stabilize different fibril organizations. The conversion between the two fibril forms leads to the release of small aggregates that in the Iowa mutant may shift the equilibrium from fibrils to more toxic oligomers.

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.

Out-of-Register Aβ42 Assemblies as Models for Neurotoxic Oligomers and Fibrils

We propose a variant of the recently found S-shaped Aβ_1-42-motif that is characterized by out-of-register C-terminal β-strands. We show that chains with this structure can form not only fibrils that are compatible with the NMR signals but also barrel-shaped oligomers that resemble the ones formed by the much smaller cylindrin peptides. By running long all-atom molecular dynamics simulations at physiological temperatures with an explicit solvent, we study the stability of these constructs and show that they are plausible models for neurotoxic oligomers. After analyzing the transitions between different assemblies, we suggest a mechanism for amyloid formation in Alzheimer's disease.

Lysosomal enzyme tripeptidyl peptidase 1 destabilizes fibrillar Aβ by multiple endoproteolytic cleavages within the β-sheet domain

Accumulation of amyloid-beta (Aβ), which is associated with Alzheimer's disease, can be caused by excess production or insufficient clearance. Because of its β-sheet structure, fibrillar Aβ is resistant to proteolysis, which would contribute to slow degradation of Aβ plaques in vivo. Fibrillar Aβ can be internalized by microglia, which are the scavenger cells of the brain, but the fibrils are degraded only slowly in microglial lysosomes. Cathepsin B is a lysosomal protease that has been shown to proteolyze fibrillar Aβ. Tripeptidyl peptidase 1 (TPP1), a lysosomal serine protease, possesses endopeptidase activity and has been shown to cleave peptides between hydrophobic residues. Herein, we demonstrate that TPP1 is able to proteolyze fibrillar Aβ efficiently. Mass spectrometry analysis of peptides released from fibrillar Aβ digested with TPP1 reveals several endoproteolytic cleavages including some within β-sheet regions that are important for fibril formation. Using molecular dynamics simulations, we demonstrate that these cleavages destabilize fibrillar β-sheet structure. The demonstration that TPP1 can degrade fibrillar forms of Aβ provides insight into the turnover of fibrillar Aβ and may lead to new therapeutic methods to increase degradation of Aβ plaques.

N-Terminal Acetylation Preserves α-Synuclein from Oligomerization by Blocking Intermolecular Hydrogen Bonds

The abnormal aggregation of α-synuclein (α-Syn) is closely associated with Parkinson's disease. Different post-translational modifications of α-Syn have been identified and contribute distinctly in α-Syn aggregation and cytotoxicity. Recently, α-Syn was reported to be N-terminally acetylated in cells, yet the functional implication of this modification, especially in α-Syn oligomerization, remains unclear. By using a solid-state nanopore system, we found that N-terminal acetylation can significantly decrease α-Syn oligomerization. Replica-exchange molecular dynamics simulations further revealed that addition of an acetyl group at the N-terminus disrupts intermolecular hydrogen bonds, which slows down the initial α-Syn oligomerization. Our finding highlights the essential role of N-terminal acetylation of α-Syn in preserving its native conformation against pathological aggregation.