Differences in the free energies between the excited states of Aβ40 and Aβ42 monomers encode their aggregation propensities

Accelerated Missense Mutation Identification in Intrinsically Disordered Proteins Using Deep Learning

We use a combination of Brownian dynamics (BD) simulation results and deep learning (DL) strategies for the rapid identification of large structural changes caused by missense mutations in intrinsically disordered proteins (IDPs). We used ∼6500 IDP sequences from MobiDB database of length 20-300 to obtain gyration radii from BD simulation on a coarse-grained single-bead amino acid model (HPS2 model) used by us and others [Dignon, G. L. PLoS Comput. Biol. 2018, 14, e1005941,Tesei, G. Proc. Natl. Acad. Sci. U.S.A. 2021, 118, e2111696118,Seth, S. J. Chem. Phys. 2024, 160, 014902] to generate the training sets for the DL algorithm. Using the gyration radii ⟨Rg⟩ of the simulated IDPs as the training set, we develop a multilayer perceptron neural net (NN) architecture that predicts the gyration radii of 33 IDPs previously studied by using BD simulation with 97% accuracy from the sequence and the corresponding parameters from the HPS model. We now utilize this NN to predict gyration radii of every permutation of missense mutations in IDPs. Our approach successfully identifies mutation-prone regions that induce significant alterations in the radius of gyration when compared to the wild-type IDP sequence. We further validate the prediction by running BD simulations on the subset of identified mutants. The neural network yields a (104-106)-fold faster computation in the search space for potentially harmful mutations. Our findings have substantial implications for rapid identification and understanding of diseases related to missense mutations in IDPs and for the development of potential therapeutic interventions. The method can be extended to accurate predictions of other mutation effects in disordered proteins.

Delving into the crucial role of the initial structure in the dynamic and self-assembly of amyloid beta

Alzheimer's disease involves the accumulation of amyloid beta (Aβ) monomers that form oligomers and fibrils in the brain. Studying the Aβ monomer is critical for understanding Aβ assembly and peptide behavior and has implications for drug design. Choosing a starting structure with a higher aggregation tendency for cost-effective MD studies and drug design is crucial. Previous studies have utilized distinct initial conformations, leading to varying results. Hence, this study was conducted to compare different initial conformations using the same MD simulation protocol to investigate the behavior and oligomerization propensity of different starting structures of Aβ during 1μs. The behavior of the monomers and their self-assembly systems were studied thoroughly, and the results revealed that highly helical Aβ monomers which used as starting structures retain high helix content during the simulation, and their tautomerization states did not cause significant changes in the structure. On the other hand, the Aβ extended and S-shaped monomers displayed the fingerprints of the fibril structure, which is believed to be more favorable for self-assembly. Self-assembly behaviors were seen for three S-shaped and three Aβ extended peptides. However, both conformations did not show stable β-sheet intermolecular interaction. For the Aβ16-22 monomer as a fragment of the Aβ that can assemble into fibrils, the impacts of capping and uncapping on the initial structure were also investigated. The results displayed that capped and uncapped structures can form oligomers with β-sheet at termini. However, in the capped state, β-sheet interactions were more stable and remained relatively longer than uncapped.

Sizes, conformational fluctuations, and SAXS profiles for intrinsically disordered proteins

The preponderance of intrinsically disordered proteins (IDPs) in the eukaryotic proteome, and their ability to interact with each other, and with folded proteins, RNA, and DNA for functional purposes, have made it important to quantitatively characterize their biophysical properties. Toward this end, we developed the transferable self-organized polymer (SOP-IDP) model to calculate the properties of several IDPs. The values of the radius of gyration (R g $$ {R}_g $$ ) obtained from SOP-IDP simulations are in excellent agreement (correlation coefficient of 0.96) with those estimated from SAXS experiments. For AP180 and Epsin, the predicted values of the hydrodynamic radii (R h s $$ {R}_h\mathrm{s} $$ ) are in nearly quantitative agreement with those from fluorescence correlation spectroscopy (FCS) experiments. Strikingly, the calculated SAXS profiles for 36 IDPs are also nearly superimposable on the experimental profiles. The dependence ofR g $$ {R}_g $$ and the mean end-to-end distance (R ee $$ {R}_{ee} $$ ) on chain length,N $$ N $$ , follows Flory's scaling law,R α ≈ a α N 0.588 $$ {R}_{\alpha}\approx {a}_{\alpha }{N}^{0.588} $$ (α = g , $$ \alpha =g, $$ ande $$ e $$ ), suggesting that globally IDPs behave as synthetic polymers in a good solvent. This finding depends on the solvent quality, which can be altered by changing variables such as pH and salt concentration. The values ofa g $$ {a}_g $$ anda e $$ {a}_e $$ are 0.20 and 0.48 nm, respectively. Surprisingly, finite size corrections to scaling, expected on theoretical grounds, are negligible forR g $$ {R}_g $$ andR ee $$ {R}_{ee} $$ . In contrast, only by accounting for the finite sizes of the IDPs, the dependence of experimentally measurableR h $$ {R}_h $$ onN $$ N $$ can be quantitatively explained usingν = 0.588 $$ \nu =0.588 $$ . Although Flory scaling law captures the estimates forR g $$ {R}_g $$ ,R ee $$ {R}_{ee} $$ , andR h $$ {R}_h $$ accurately, the spread of the simulated data around the theoretical curve is suggestive of of sequence-specific features that emerge through a fine-grained analysis of the conformational ensembles using hierarchical clustering. Typically, the ensemble of conformations partitions into three distinct clusters, having different equilibrium populations and structural properties. Without any further readjustments to the parameters of the SOP-IDP model, we also obtained nearly quantitative agreement with paramagnetic relaxation enhancement (PRE) measurements for α-synuclein. The transferable SOP-IDP model sets the stage for several applications, including the study of phase separation in IDPs and interactions with nucleic acids.

The mechanism of amyloid fibril growth from Φ-value analysis

Amyloid fibrils are highly stable misfolded protein assemblies that play an important role in several neurodegenerative and systemic diseases. Although structural information of the amyloid state is now abundant, mechanistic details about the misfolding process remain elusive. Inspired by the Φ-value analysis of protein folding, we combined experiments and molecular simulations to resolve amino-acid contacts and determine the structure of the transition-state ensemble-the rate-limiting step-for fibril elongation of PI3K-SH3 amyloid fibrils. The ensemble was validated experimentally by Tanford β analysis and computationally by free energy calculations. Although protein folding proceeds on funnel-shaped landscapes, here we find that the energy landscape for the misfolding reaction consists of a large 'golf course' region, defined by a single energy barrier and transition state, accessing a sharply funnelled region. Thus, misfolding occurs by rare, successful monomer-fibril end collisions interspersed by numerous unsuccessful binding attempts. Taken together, these insights provide a quantitative and highly resolved description of a protein misfolding reaction.

Helix-to-sheet transition of the Aβ42 peptide revealed using an enhanced sampling strategy and Markov state model

The self-assembly of Aβ peptides into toxic oligomers and fibrils is the primary cause of Alzheimer's disease. Moreover, the conformational transition from helix to sheet is considered a crucial step in the aggregation of Aβ peptides. However, the structural details of this process still remain unclear due to the heterogeneity and transient nature of the Aβ peptides. In this study, we developed an enhanced sampling strategy that combines artificial neural networks (ANN) with metadynamics to explore the conformational space of the Aβ42 peptides. The strategy consists of two parts: applying ANN to optimize CVs and conducting metadynamics based on the resulting CVs to sample conformations. The results showed that this strategy achieved better sampling performance in terms of the distribution of sampled conformations. The sampling efficiency is increased by 10-fold compared to our previous Hamiltonian Exchange Molecular Dynamics (MD) and by 1000-fold compared to ordinary MD. Based on the sampled conformations, we constructed a Markov state model to understand the detailed transition process. The intermediate states in this process are identified, and the connecting paths are analyzed. The conformational transitions in D23-K28 and M35-V40 are proven to be crucial for aggregation. These results are helpful in clarifying the mechanism and process of Aβ42 peptide aggregation. D23-K28 and M35-V40 can be identified as potential targets for screening and designing inhibitors of Aβ peptide aggregation.

SOP-MULTI: A Self-Organized Polymer-Based Coarse-Grained Model for Multidomain and Intrinsically Disordered Proteins with Conformation Ensemble Consistent with Experimental Scattering Data

Multidomain proteins with long flexible linkers and full-length intrinsically disordered proteins (IDPs) are best defined as an ensemble of conformations rather than a single structure. Determining high-resolution ensemble structures of such proteins poses various challenges by using tools from experimental structural biophysics. Integrative approaches combining available low-resolution ensemble-averaged experimental data and in silico biomolecular reconstructions are now often used for the purpose. However, extensive Boltzmann weighted conformation sampling for large proteins, especially for ones where both the folded and disordered domains exist in the same polypeptide chain, remains a challenge. In this work, we present a 2-site per amino-acid resolution SOP-MULTI force field for simulating coarse-grained models of multidomain proteins. SOP-MULTI combines two well-established self-organized polymer models─: (i) SOP-SC models for folded systems and (ii) SOP-IDP for IDPs. For the SOP-MULTI, we introduce cross-interaction terms between the beads belonging to the folded and disordered regions to generate conformation ensembles for full-length multidomain proteins such as hnRNP A1, TDP-43, G3BP1, hGHR-ECD, TIA1, HIV-1 Gag, polyubiquitin, and FUS. When back-mapped to all-atom resolution, SOP-MULTI trajectories faithfully recapitulate the scattering data over the range of the reciprocal space. We also show that individual folded domains preserve native contacts with respect to solved folded structures, and root-mean-square fluctuations of residues in folded domains match those obtained from all-atom molecular dynamics simulation trajectories of the same folded systems. SOP-MULTI force field is made available as a LAMMPS-compatible user package along with setup codes for generating the required files for any full-length protein with folded and disordered regions.

Heterotypic Seeding Generates Mixed Amyloid Polymorphs

Aggregation of the amyloid β (Aβ) peptide into fibrils represents one of the major biochemical pathways underlying the development of Alzheimer's disease (AD). Extensive studies have been carried out to understand the role of fibrillar seeds on the overall kinetics of amyloid aggregation. However, the precise effect of seeds that are structurally or sequentially different from Aβ on the structure of the resulting amyloid aggregates is yet to be fully understood. Herein, nanoscale infrared spectroscopy is used to probe the spectral facets of individual aggregates formed by aggregating Aβ42 with antiparallel fibrillar seeds of Aβ(16-22) and E22Q Aβ(1-40) Dutch mutant and it is demonstrated that Aβ can form heterotypic or mixed polymorphs that deviate significantly from its expected parallel cross β structure. It is further shown that the formation of heterotypic aggregates is not limited to the coaggregation of Aβ and its isomers, and that the former can form heterotypic fibrils with alpha-synuclein and brain protein lysates. These findings highlight the complexity of Aβ aggregation in AD and underscore the need to explore how Aβ interacts with other brain components, which is crucial for developing better therapeutic strategies for AD.

Origin of Secondary Structure Transitions and Peptide Self-Assembly Propensity in Trifluoroethanol-Water Mixtures

Membrane-peptide interactions are key to the formation of helical intermediates in the early stages of amyloidogenesis. Aqueous solutions of 2,2,2-trifluoroethanol (TFE) provide a membrane-mimetic environment capable of promoting and stabilizing local peptide interactions. Uperin 3.5 (U3.5), a 17-residue and amidated antimicrobial peptide, is unstructured in water but self-assembles into fibrils in the presence of salt. Secondary structure transitions linked to U3.5 self-assembly were investigated in TFE/water mixtures, in both the absence and presence of salt, to assess the role of membrane-peptide interactions on peptide self-assembly and amyloid formation. A 5-to-7-fold increase in fibril yield of U3.5 was observed at low TFE concentrations (10% TFE/water v/v) compared with physiological buffer but only in the presence of salt. No aggregation was observed in salt-free TFE/water mixtures. Circular dichroism spectra showed that partial helical structures, initially stabilized by TFE, transitioned to β-sheet-rich aggregates in a saline buffer. Molecular dynamics simulations confirmed that TFE and salt act synergistically to enhance peptide-peptide interactions, resulting in β-sheet-rich U3.5 oligomers at low TFE concentrations. Specifically, TFE stabilized amphipathic, helical intermediates, leading to increased peptide-peptide attraction through hydrophobic interactions. The presence of salt further enhanced the peptide-peptide interactions by screening positively charged residues. Thus, the study revealed the role of a membrane mimic in stabilizing helical intermediates on the pathway to amyloid formation in the antimicrobial U3.5 peptide.

Design of parallel 𝛽-sheet nanofibrils using Monte Carlo search, coarse-grained simulations, and experimental testing

Peptide self-assembly into amyloid fibrils provides numerous applications in drug delivery and biomedical engineering applications. We augment our previously-established computational screening technique along with experimental biophysical characterization to discover 7-mer peptides that self-assemble into "parallel β-sheets", that is, β-sheets with N-terminus-to-C-terminus 𝛽-strand vectors oriented in parallel. To accomplish the desired β-strand organization, we applied the PepAD amino acid sequence design software to the Class-1 cross-β spine defined by Sawaya et al. This molecular configuration includes two layers of parallel β-sheets stacked such that N-terminus-to-C-terminus vectors are oriented antiparallel for molecules on adjacent β-sheets. The first cohort of PepAD identified peptides were examined for their fibrillation behavior in DMD/PRIME20 simulations, and the top performing sequence was selected as a prototype for a subsequent round of sequence refinement. The two rounds of design resulted in a library of eight 7-mer peptides. In DMD/PRIME20 simulations, five of these peptides spontaneously formed fibril-like structures with a predominantly parallel 𝛽-sheet arrangement, two formed fibril-like structure with <50% in parallel 𝛽-sheet arrangement and one remained a random coil. Among the eight candidate peptides produced by PepAD and DMD/PRIME20, five were synthesized and purified. All five assembled into amyloid fibrils composed of parallel β-sheets based on Fourier transform infrared spectroscopy, circular dichroism, electron microscopy, and thioflavin-T fluorescence spectroscopy measurements.

Molecular Insight into the Effect of HIV-TAT Protein on Amyloid-β Peptides

Increased deposition of amyloid-β (Aβ) plaques in the brain is a frequent pathological feature observed in human immunodeficiency virus (HIV)-positive patients. Emerging evidence indicates that HIV regulatory proteins, particularly the transactivator of transcription (TAT) protein, could interact with Aβ peptide, accelerating the formation of Aβ plaques in the brain and potentially contributing to the onset of Alzheimer's disease in individuals with HIV infection. Nevertheless, the molecular mechanisms underlying these processes remain unclear. In the present study, we have used long all-atom molecular dynamics simulations to probe the direct interactions between the TAT protein and Aβ peptide at the molecular level. Sampling over 28.0 μs, our simulations show that TAT protein induces a shift in the Aβ monomer ensemble toward elongated conformations, exposing aggregation-prone regions on the surface and thereby inducing subsequent aggregation. TAT protein also appears to enhance the stability of preformed Aβ fibrils, while increasing the β-sheet content within these fibrils. Our atomistically detailed simulations qualitatively agree with previous in vitro and in vivo studies. Importantly, our simulations identify key interactions between Aβ and the TAT protein that drive the Aβ aggregation process and stabilize the preformed Aβ aggregates, which are particularly challenging to obtain through current experimental techniques.

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

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

Can local heating and molecular crowders disintegrate amyloid aggregates?

The present study employs a blend of molecular dynamics simulations and a theoretical model to explore the potential disintegration mechanism of a matured Aβ octamer, aiming to offer a strategy to combat Alzheimer's disease. We investigate local heating and crowding effects on Aβ disintegration by selectively heating key Aβ segments and varying the concentration of sodium dodecyl sulphate (SDS), respectively. Despite initiation of disruption, Aβ aggregates resist complete disintegration during local heating due to rapid thermal energy distribution to the surrounding water. Conversely, although SDS molecules effectively inhibit Aβ aggregation at higher concentration through micelle formation, they fail to completely disintegrate the aggregate due to the exceedingly high energy barrier. To address the sampling challenge posed by the formidable energy barrier, we have performed well-tempered metadynamics simulations. Simulations reveal a multi-step disintegration mechanism for the Aβ octamer, suggesting a probable sequence: octamer → pentamer/hexamer ⇌ tetramer → monomer, with a rate-determining step constituting 45 kJ mol-1 barrier during the octamer to pentamer/hexamer transition. Additionally, we have proposed a novel two-state mean-field model based on Ising spins that offers an insight into the kinetics of the Aβ growth process and external perturbation effects on disintegration. Thus, the current simulation study, coupled with the newly introduced mean-field model, offers an insight into the detailed mechanisms underlying the Aβ aggregation process, guiding potential strategies for effective disintegration of Aβ aggregates.

Alpha-synuclein phosphorylation induces amyloid conversion via enhanced electrostatic bridging: Insights from molecular modeling of the full-length protein

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

Hairpin trimer transition state of amyloid fibril

Protein fibril self-assembly is a universal transition implicated in neurodegenerative diseases. Although fibril structure/growth are well characterized, fibril nucleation is poorly understood. Here, we use a computational-experimental approach to resolve fibril nucleation. We show that monomer hairpin content quantified from molecular dynamics simulations is predictive of experimental fibril formation kinetics across a tau motif mutant library. Hairpin trimers are predicted to be fibril transition states; one hairpin spontaneously converts into the cross-beta conformation, templating subsequent fibril growth. We designed a disulfide-linked dimer mimicking the transition state that catalyzes fibril formation, measured by ThT fluorescence and TEM, of wild-type motif - which does not normally fibrillize. A dimer compatible with extended conformations but not the transition-state fails to nucleate fibril at any concentration. Tau repeat domain simulations show how long-range interactions sequester this motif in a mutation-dependent manner. This work implies that different fibril morphologies could arise from disease-dependent hairpin seeding from different loci.

Conformational fluctuations and phases in fused in sarcoma (FUS) low-complexity domain

The well-known phenomenon of phase separation in synthetic polymers and proteins has become a major topic in biophysics because it has been invoked as a mechanism of compartment formation in cells, without the need for membranes. Most of the coacervates (or condensates) are composed of Intrinsically Disordered Proteins (IDPs) or regions that are structureless, often in interaction with RNA and DNA. One of the more intriguing IDPs is the 526-residue RNA-binding protein, Fused in Sarcoma (FUS), whose monomer conformations and condensates exhibit unusual behavior that are sensitive to solution conditions. By focussing principally on the N-terminus low-complexity domain (FUS-LC comprising residues 1-214) and other truncations, we rationalize the findings of solid-state NMR experiments, which show that FUS-LC adopts a non-polymorphic fibril structure (core-1) involving residues 39-95, flanked by fuzzy coats on both the N- and C-terminal ends. An alternate structure (core-2), whose free energy is comparable to core-1, emerges only in the truncated construct (residues 110-214). Both core-1 and core-2 fibrils are stabilized by a Tyrosine ladder as well as hydrophilic interactions. The morphologies (gels, fibrils, and glass-like) adopted by FUS seem to vary greatly, depending on the experimental conditions. The effect of phosphorylation is site-specific. Simulations show that phosphorylation of residues within the fibril has a greater destabilization effect than residues that are outside the fibril region, which accords well with experiments. Many of the peculiarities associated with FUS may also be shared by other IDPs, such as TDP43 and hnRNPA2. We outline a number of problems for which there is no clear molecular explanation.

Emerging Trends in Cryo-EM-based Structural Studies of Neuropathological Amyloids

Tauopathies, synucleinopathies, Aβ amyloidosis, TDP-43 proteinopathies, and prion diseases- these neurodegenerative diseases have in common the formation of amyloid filaments rich in cross-β sheets. Cryo-electron microscopy now permits the visualization of amyloid assemblies at atomic resolution, ushering a wide range of structural studies on several of these poorly understood amyloidogenic proteins. Amyloids are polymorphic with minor modulations in reaction environment affecting the overall architecture of their assembly, making amyloids an extremely challenging venture for structure-based therapeutic intervention. In 2017, the first cryo-EM structure of tau filaments from an Alzheimer's disease-affected brain established that in vitro assemblies might not necessarily reflect the native amyloid fold. Since then, brain-derived amyloid structures for several proteins across many neurodegenerative diseases have uncovered the disease-relevant amyloid folds. It has now been shown for tauopathies, synucleinopathies and TDP-43 proteinopathies, that distinct amyloid folds of the same protein might be related to different diseases. Salient features of each of these brain-derived folds are discussed in detail. It was also recently observed that seeded aggregation does not necessarily replicate the brain-derived structural fold. Owing to high throughput structure determination, some of these native amyloid folds have also been successfully replicated in vitro. In vitro replication of disease-relevant filaments will aid development of imaging ligands and defibrillating drugs. Towards this direction, recent high-resolution structures of tau filaments with positron emission tomography tracers and a defibrillating drug are also discussed. This review summarizes and celebrates the recent advancements in structural understanding of neuropathological amyloid filaments using cryo-EM.

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.

Effect of mutations on the folding and stability of γD-crystallin protein

Interprotein interactions between the partially unfolded states of γD-crystallin (γD-crys) protein are known to cause cataracts. Therefore, understanding the unfolding pathways of native γD-crys is extremely crucial to delineate their aggregation mechanism. In this study, we have performed extensive all-atom Molecular Dynamics simulations with explicit solvent to understand the role of the critical residues that drive the stability of the motifs and domains of γD-crys in its wild type and mutant forms. Our findings show that while the individual motifs of wild type are not stable in the native form, the individual domains remain structurally stable at 425K. This enhanced stability of the domain was attributed to the hydrophobic interactions between the motifs. Single and double point mutations of the domains with negatively charged aspartic and glutamic acid amino acid residues (I3E, W42D, W42E, I3D/W42D, I3E/W42E, and L92D/W157D) decreases the structural stability, leading to unfolding of individual domains of γD-crys. We believe that our study sheds light on the weakest links of γD-crys, along with the role of interactions stabilizing the domains. Further, this study bolsters and provides a better understanding of the domain swapping mechanism of aggregation of γD-crys.Communicated by Ramaswamy H. Sarma.

Recent Computational Advances Regarding Amyloid-β and Tau Membrane Interactions in Alzheimer's Disease

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

Amyloid Aggregation and Liquid-Liquid Phase Separation from the Perspective of Phase Transitions

Amyloid aggregation describes the aberrant self-assembly of peptides into ordered fibrils characterized by cross-β spine cores and is associated with many neurodegenerative diseases and Type 2 diabetes. Oligomers, populated during the early stage of aggregation, are found to be more cytotoxic than mature fibrils. Recently, many amyloidogenic peptides have been reported to undergo liquid-liquid phase separation (LLPS)─a biological process important for the compartmentalization of biomolecules in living cells─prior to fibril formation. Understanding the relationship between LLPS and amyloid aggregation, especially the formation of oligomers, is essential for uncovering disease mechanisms and mitigating amyloid toxicity. In this Perspective, available theories and models of amyloid aggregation and LLPS are first briefly reviewed. By drawing analogies to gas, liquid, and solid phases in thermodynamics, a phase diagram of protein monomer, droplet, and fibril states separated by coexistence lines can be inferred. Due to the high free energy barrier of fibrillization kinetically delaying the formation of fibril seeds out of the droplets, a "hidden" monomer-droplet coexistence line extends into the fibril phase. Amyloid aggregation can then be described as the equilibration process from the initial "out-of-equilibrium" state of a homogeneous solution of monomers to the final equilibrium state of stable amyloid fibrils coexisting with monomers and/or droplets via the formation of metastable or stable droplets as the intermediates. The relationship between droplets and oligomers is also discussed. We suggest that the droplet formation of LLPS should be considered in future studies of amyloid aggregation, which may help to better understand the aggregation process and develop therapeutic strategies to mitigate amyloid toxicity.

Comparative Performance of Computer Simulation Models of Intrinsically Disordered Proteins at Different Levels of Coarse-Graining

Coarse-graining is commonly used to decrease the computational cost of simulations. However, coarse-grained models are also considered to have lower transferability, with lower accuracy for systems outside the original scope of parametrization. Here, we benchmark a bead-necklace model and a modified Martini 2 model, both coarse-grained models, for a set of intrinsically disordered proteins, with the different models having different degrees of coarse-graining. The SOP-IDP model has earlier been used for this set of proteins; thus, those results are included in this study to compare how models with different levels of coarse-graining compare. The sometimes naive expectation of the least coarse-grained model performing best does not hold true for the experimental pool of proteins used here. Instead, it showed the least good agreement, indicating that one should not necessarily trust the otherwise intuitive notion of a more advanced model inherently being better in model choice.

Odd-even disparity in the population of slipped hairpins in RNA repeat sequences with implications for phase separation

Low-complexity nucleotide repeat sequences, which are implicated in several neurological disorders, undergo liquid-liquid phase separation (LLPS) provided the number of repeat units, n, exceeds a critical value. Here, we establish a link between the folding landscapes of the monomers of trinucleotide repeats and their propensity to self-associate. Simulations using a coarse-grained Self-Organized Polymer (SOP) model for (CAG)n repeats in monovalent salt solutions reproduce experimentally measured melting temperatures, which are available only for small n. By extending the simulations to large n, we show that the free-energy gap, ΔGS, between the ground state (GS) and slipped hairpin (SH) states is a predictor of aggregation propensity. The GS for even n is a perfect hairpin (PH), whereas it is a SH when n is odd. The value of ΔGS (zero for odd n) is larger for even n than for odd n. As a result, the rate of dimer formation is slower in (CAG)30 relative to (CAG)31, thus linking ΔGS to RNA-RNA association. The yield of the dimer decreases dramatically, compared to the wild type, in mutant sequences in which the population of the SH decreases substantially. Association between RNA chains is preceded by a transition to the SH even if the GS is a PH. The finding that the excitation spectrum-which depends on the exact sequence, n, and ionic conditions-is a predictor of self-association should also hold for other RNAs (mRNA for example) that undergo LLPS.

Conformational Fluctuations and Phases in Fused in Sarcoma (FUS) Low-Complexity Domain

The well known phenomenon of phase separation in synthetic polymers and proteins has become a major topic in biophysics because it has been invoked as a mechanism of compartment formation in cells, without the need for membranes. Most of the coacervates (or condensates) are composed of Intrinsically Disordered Proteins (IDPs) or regions that are structureless, often in interaction with RNA and DNA. One of the more intriguing IDPs is the 526-residue RNA binding protein, Fused In Sarcoma (FUS), whose monomer conformations and condensates exhibit unusual behavior that are sensitive to solution conditions. By focussing principally on the N-terminus low complexity domain (FUS-LC comprising residues 1-214) and other truncations, we rationalize the findings of solid state NMR experiments, which show that FUS-LC adopts a non-polymorphic fibril (core-1) involving residues 39-95, flanked by fuzzy coats on both the N- and C- terminal ends. An alternate structure (core-2), whose free energy is comparable to core-1, emerges only in the truncated construct (residues 110-214). Both core-1 and core-2 fibrils are stabilized by a Tyrosine ladder as well as hydrophilic interactions. The morphologies (gels, fibrils, and glass-like behavior) adopted by FUS seem to vary greatly, depending on the experimental conditions. The effect of phosphorylation is site specific and affects the stability of the fibril depending on the sites that are phosphorylated. Many of the peculiarities associated with FUS may also be shared by other IDPs, such as TDP43 and hnRNPA2. We outline a number of problems for which there is no clear molecular understanding.

Exploring the aggregation of amyloid-β 42 through Monte Carlo simulations

Coarse-grained Monte Carlo simulations are performed for a disordered protein, amyloid-β 42 to identify the interactions and understand the mechanism of its aggregation. A statistical potential is developed from a selected dataset of intrinsically disordered proteins, which accounts for the respective contributions of the bonded and non-bonded potentials. While, the bonded potential comprises the bond, bend, and dihedral constraints, the nonbonded interactions include van der Waals interactions, hydrogen bonds, and the two-body potential. The two-body potential captures the features of both hydrophobic and electrostatic interactions that brings the chains at a contact distance, while the repulsive van der Waals interactions prevent them from a collapse. Increased two-body hydrophobic interactions facilitate the formation of amorphous aggregates rather than the fibrillar ones. The formation of aggregates is validated from the interchain distances, and the total energy of the system. The aggregate is structurally characterized by the root-mean-square deviation, root-mean-square fluctuation and the radius of gyration. The aggregates are characterized by a decrease in SASA, an increase in the non-local interactions and a distinct free energy minimum relative to that of the monomeric state of amyloid-β 42. The hydrophobic residues help in nucleation, while the charged residues help in oligomerization and aggregation.

Metastable alpha-rich and beta-rich conformations of small Aβ42 peptide oligomers

Probing the structures of amyloid-β (Aβ) peptides in the early steps of aggregation is extremely difficult experimentally and computationally. Yet, this knowledge is extremely important as small oligomers are the most toxic species. Experiments and simulations on Aβ42 monomer point to random coil conformations with either transient helical or β-strand content. Our current conformational description of small Aβ42 oligomers is funneled toward amorphous aggregates with some β-sheet content and rare high energy states with well-ordered assemblies of β-sheets. In this study, we emphasize another view based on metastable α-helix bundle oligomers spanning the C-terminal residues, which are predicted by the machine-learning AlphaFold2 method and supported indirectly by low-resolution experimental data on many amyloid polypeptides. This finding has consequences in developing novel chemical tools and to design potential therapies to reduce aggregation and toxicity.

Interpreting Transient Interactions of Intrinsically Disordered Proteins

The flexible nature of intrinsically disordered proteins (IDPs) gives rise to a conformational ensemble with a diverse set of conformations. The simplest way to describe this ensemble is through a homopolymer model without any specific interactions. However, there has been growing evidence that the conformational properties of IDPs and their relevant functions can be affected by transient interactions between specific and even nonlocal pairs of amino acids. Interpreting these interactions from experimental methods, each of which is most sensitive to a different distance regime referred to as probing length, remains a challenging and unsolved problem. Here, we first show that transient interactions can be realized between short fragments of charged amino acids by generating conformational ensembles using model disordered peptides and coarse-grained simulations. Using these ensembles, we investigate how sensitive different types of experimental measurements are to the presence of transient interactions. We find methods with shorter probing lengths to be more appropriate for detecting these transient interactions, but one experimental method is not sufficient due to the existence of other weak interactions typically seen in IDPs. Finally, we develop an adjusted polymer model with an additional short-distance peak which can robustly reproduce the distance distribution function from two experimental measurements with complementary short and long probing lengths. This new model can suggest whether a homopolymer model is insufficient for describing a specific IDP and meets the challenge of quantitatively identifying specific, transient interactions from a background of nonspecific, weak interactions.

Energy landscapes of Aβ monomers are sculpted in accordance with Ostwald's rule of stages

The transition from a disordered to an assembly-competent monomeric state (N*) in amyloidogenic sequences is a crucial event in the aggregation cascade. Using a well-calibrated model for intrinsically disordered proteins (IDPs), we show that the N* states, which bear considerable resemblance to the polymorphic fibril structures found in experiments, not only appear as excitations in the free energy landscapes of Aβ40 and Aβ42, but also initiate the aggregation cascade. For Aβ42, the transitions to the different N* states are in accord with Ostwald's rule of stages, with the least stable structures forming ahead of thermodynamically favored ones. The Aβ40 and Aβ42 monomer landscapes exhibit different extents of local frustration, which we show have profound implications in dictating subsequent self-assembly. Using kinetic transition networks, we illustrate that the most favored dimerization routes proceed via N* states. We argue that Ostwald's rule also holds for the aggregation of fused in sarcoma and polyglutamine proteins.

Governing dynamics and preferential binding of the AXH domain influence the aggregation pathway of Ataxin-1

The present state of understanding the mechanism of Spinocerebellar Ataxia-1, a fatal neurodegenerative disease linked to the protein Ataxin-1 (ATXN1), is baffled by a set of self-contradictory, and hence, inconclusive observations. This fallacy poses a bottleneck to the effective designing of curable drugs as the field is currently missing the specific druggable site. To understand the fundamentals of pathogenesis, we tried to decipher the intricacies of the extremely complicated landscape by targeting the relevant species that supposedly dictate the structure-function paradigm. The atomic-level description and characterization of the dynamism of the systems reveal the existence of structural polymorphism in all the leading stakeholders of the overall system. The very existence of conformational heterogeneity in every species creates numerous possible combinations of favorable interactions because of the variability in segmental cross-talks and hence claims its role in the choice of routes between functional activity and dysfunctional disease-causing aggregation. Despite this emergent configurational diversity, there is a common mode of operative intermolecular forces that dictates the extent of stability of all the multimeric complexes due to the localized population of a specific type of residue. The present research proposes a dynamic switch mechanism between aggregability and functional activity, based on the logical interpretation of the estimated variables, which is practically dictated by the effective concentration of the interacting species involved in the cell.

On the plasticity of amyloid formation: The impact of destabilizing small to large substitutions on islet amyloid polypeptide amyloid formation

Amyloids are partially ordered, proteinaceous, β-sheet rich deposits that have been implicated in a wide range of diseases. An even larger set of proteins that do not normally form amyloid in vivo can be induced to do so in vitro. A growing number of structures of amyloid fibrils have been reported and a common feature is the presence of a tightly packed core region in which adjacent monomers pack together in extremely tight interfaces, often referred to as steric zippers. A second common feature of many amyloid fibrils is their polymorphous nature. We examine the consequences of disrupting the tight packing in amyloid fibrils on the kinetics of their formation using the 37 residue polypeptide hormone islet amyloid polypeptide (IAPP, amylin) as a model system. IAPP forms islet amyloid in vivo and is aggressively amyloidogenic in vitro. Six Cryo-EM structures of IAPP amyloid fibrils are available and in all Gly24 is in the core of the structured region and makes tight contacts with other residues. Calculations using the ff14SBonlysc forcefield in Amber20 show that substitutions with larger amino acids significantly disrupt close packing and are predicted to destabilize the various fibril structures. However, Gly to 2-amino butyric acid (2-carbon side chain) and Gly to Leu substitutions actually enhance the rate of amyloid formation. A Pro substitution slows, but does not prevent amyloid formation.

Protein aggregates thermodynamically order regardless of sequence

Proteins can aggregate into disordered aggregates or ordered assemblies such as amyloid fibrils. These two distinct phases serve differing roles in function and disease. How protein sequence determines the preferred phase is unknown. Here we establish a statistical mechanical disorder-to-order transition condition for compact polymer aggregates, including proteins. The theory produces a simple universal equation determining the favored phase as a function of temperature, polymer length, and interaction energy variance. We show that the sequence-dependent energy variance is efficiently calculated using atomistic simulations, so that the theory has no adjustable parameters. The equation accurately predicts experimental length-dependent crystallization temperatures of synthetic polymers. The equation also predicts that all protein sequences that aggregate will also favor ordering. Consequently, energy must be expended to maintain the steady-state disordered phase if it is not kinetically metastable on physiological timescales. More broadly, the theory suggests that aggregates of organic polymers will generally tend to order on habitable planets.

Formation of extramembrane β-strands controls dimerization of transmembrane helices in amyloid precursor protein C99

The 99-residue C-terminal domain of amyloid precursor protein (APP-C99), precursor to amyloid beta (Aβ), is a transmembrane (TM) protein containing intrinsically disordered N- and C-terminal extramembrane domains. Using molecular dynamics (MD) simulations, we show that the structural ensemble of the C99 monomer is best described in terms of thousands of states. The C99 monomer has a propensity to form β-strand in the C-terminal extramembrane domain, which explains the slow spin relaxation times observed in paramagnetic probe NMR experiments. Surprisingly, homodimerization of C99 not only narrows the conformational ensemble from thousands to a few states through the formation of metastable β-strands in extramembrane domains but also stabilizes extramembrane α-helices. The extramembrane domain structure is observed to dramatically impact the homodimerization motif, resulting in the modification of TM domain conformations. Our study provides an atomic-level structural basis for communication between the extramembrane domains of the C99 protein and TM homodimer formation. This finding could serve as a general model for understanding the influence of disordered extramembrane domains on TM protein structure.

Modeling structural interconversion in Alzheimers' amyloid beta peptide with classical and intrinsically disordered protein force fields

A comprehensive understanding of the aggregation mechanism in amyloid beta 42 (Aβ42) peptide is imperative for developing therapeutic drugs to prevent or treat Alzheimer's disease. Because of the high flexibility and lack of native tertiary structures of Aβ42, molecular dynamics (MD) simulations may help elucidate the peptide's dynamics with atomic details and collectively improve ensembles not seen in experiments. We applied microsecond-timescale MD simulations to investigate the dynamics and conformational changes of Aβ42 by using a newly developed Amber force field (ff14IDPSFF). We compared the ff14IDPSFF and the regular ff14SB force field by examining the conformational changes of two distinct Aβ42 monomers in explicit solvent. Conformational ensembles obtained by simulations depend on the force field and initial structure, Aβ42^α-helix or Aβ42^β-strand. The ff14IDPSFF sampled a high ratio of disordered structures and diverse β-strand secondary structures; in contrast, ff14SB favored helicity during the Aβ42^α-helix simulations. The conformations obtained from Aβ42^β-strand simulations maintained a balanced content in the disordered and helical structures when simulated by ff14SB, but the conformers clearly favored disordered and β-sheet structures simulated by ff14IDPSFF. The results obtained with ff14IDPSFF qualitatively reproduced the NMR chemical shifts well. In-depth peptide and cluster analysis revealed some characteristic features that may be linked to early onset of the fibril-like structure. The C-terminal region (mainly M35-V40) featured in-registered anti-parallel β-strand (β-hairpin) conformations with tested systems. Our work should expand the knowledge of force field and structure dependency in MD simulations and reveals the underlying structural mechanism-function relationship in Aβ42 peptides. Communicated by Ramaswamy H. Sarma.

Self-Assembly of Amyloid-Beta (Aβ) Peptides from Solution to Near In Vivo Conditions

Understanding the atomistic resolution changes during the self-assembly of amyloid peptides or proteins is important to develop compounds or conditions to alter the aggregation pathways and suppress the toxicity and potentially aid in the development of drugs. However, the complexity of protein aggregation and the transient order/disorder of oligomers along the pathways to fibril are very challenging. In this Perspective, we discuss computational studies of amyloid polypeptides carried out under various conditions, including conditions closely mimicking in vivo and point out the challenges in obtaining physiologically relevant results, focusing mainly on the amyloid-beta Aβ peptides.

pH Induced Switch in the Conformational Ensemble of Intrinsically Disordered Protein Prothymosin-α and Its Implications for Amyloid Fibril Formation

Aggregation of intrinsically disordered proteins (IDPs) can lead to neurodegenerative diseases. Although there is experimental evidence that acidic pH promotes IDP monomer compaction leading to aggregation, the general mechanism is unclear. We studied the pH effect on the conformational ensemble of prothymosin-α (proTα), which is involved in multiple essential functions, and probed its role in aggregation using computer simulations. We show that compaction in the proTα dimension at low pH is due to the protein's collapse in the intermediate region (E41-D80) rich in glutamic acid residues, enhancing its β-sheet content. We observed by performing dimer simulations that the conformations with high β-sheet content could act as aggregation-prone (N*) states and nucleate the aggregation process. The simulations initiated using N* states form dimers within a microsecond time scale, whereas the non-N* states do not form dimers within this time scale. This study contributes to understanding the general principles of pH-induced IDP aggregation.

Salt-Induced Transitions in the Conformational Ensembles of Intrinsically Disordered Proteins

Salts modulate the behavior of intrinsically disordered proteins (IDPs) and influence the formation of membraneless organelles through liquid-liquid phase separation (LLPS). In low ionic strength solutions, IDP conformations are perturbed by the screening of electrostatic interactions, independent of the salt identity. In this regime, insight into the IDP behavior can be obtained using the theory for salt-induced transitions in charged polymers. However, salt-specific interactions with the charged and uncharged residues, known as the Hofmeister effect, influence IDP behavior in high ionic strength solutions. There is a lack of reliable theoretical models in high salt concentration regimes to predict the salt effect on IDPs. We propose a simulation methodology using a coarse-grained IDP model and experimentally measured water to salt solution transfer free energies of various chemical groups that allowed us to study the salt-specific transitions induced in the IDPs conformational ensemble. We probed the effect of three different monovalent salts on five IDPs belonging to various polymer classes based on charged residue content. We demonstrate that all of the IDPs of different polymer classes behave as self-avoiding walks (SAWs) at physiological salt concentration. In high salt concentrations, the transitions observed in the IDP conformational ensembles are dependent on the salt used and the IDP sequence and composition. Changing the anion with the cation fixed can result in the IDP transition from a SAW-like behavior to a collapsed globule. An important implication of these results is that a suitable salt can be identified to induce condensation of an IDP through LLPS.

Conformational Variability of Amyloid-β and the Morphological Diversity of Its Aggregates

Protein folding is the most fundamental and universal example of biomolecular self-organization and is characterized as an intramolecular process. In contrast, amyloidogenic proteins can interact with one another, leading to protein aggregation. The energy landscape of amyloid fibril formation is characterized by many minima for different competing low-energy structures and, therefore, is much more enigmatic than that of multiple folding pathways. Thus, to understand the entire energy landscape of protein aggregation, it is important to elucidate the full picture of conformational changes and polymorphisms of amyloidogenic proteins. This review provides an overview of the conformational diversity of amyloid-β (Aβ) characterized from experimental and theoretical approaches. Aβ exhibits a high degree of conformational variability upon transiently interacting with various binding molecules in an unstructured conformation in a solution, forming an α-helical intermediate conformation on the membrane and undergoing a structural transition to the β-conformation of amyloid fibrils. This review also outlines the structural polymorphism of Aβ amyloid fibrils depending on environmental factors. A comprehensive understanding of the energy landscape of amyloid formation considering various environmental factors will promote drug discovery and therapeutic strategies by controlling the fibril formation pathway and targeting the consequent morphology of aggregated structures.

Possible Co-Evolution of Polyglutamine and Polyproline in Huntingtin Protein: Proline-Rich Domain as Transient Folding Chaperone

Huntington's disease is an inherited neurodegenerative disorder caused by the overduplication of CAG repeats in the Huntingtin gene. Recent findings revealed that among the orthologs, the expansion of CAG repeats (polyQ) in the Huntingtin gene occurs in tandem with the duplication of CCG repeats (polyP). However, the molecular mechanism of this possible co-evolution remains unknown. We examined the structures of Huntingtin exon 1 (HttEx1) from six species along with five designed mutants. We found that the polyP segments "chaperone" the rest of the HttEx1 by forming ad hoc polyP binding grooves. Such a process elongates the otherwise poorly solvated polyQ domain, while modulating its secondary structure propensity from β-strands to α-helices. This chaperoning effect is achieved mostly through transient hydrogen bond interactions between polyP and the rest of HttEx1, resulting in a striking golden ratio of ∼2:1 between the chain lengths of polyQ and polyP.

Global Structure of the Intrinsically Disordered Protein Tau Emerges from Its Local Structure

The paradigmatic disordered protein tau plays an important role in neuronal function and neurodegenerative diseases. To disentangle the factors controlling the balance between functional and disease-associated conformational states, we build a structural ensemble of the tau K18 fragment containing the four pseudorepeat domains involved in both microtubule binding and amyloid fibril formation. We assemble 129-residue-long tau K18 chains with atomic detail from an extensive fragment library constructed with molecular dynamics simulations. We introduce a reweighted hierarchical chain growth (RHCG) algorithm that integrates experimental data reporting on the local structure into the assembly process in a systematic manner. By combining Bayesian ensemble refinement with importance sampling, we obtain well-defined ensembles and overcome the problem of exponentially varying weights in the integrative modeling of long-chain polymeric molecules. The resulting tau K18 ensembles capture nuclear magnetic resonance (NMR) chemical shift and J-coupling measurements. Without further fitting, we achieve very good agreement with measurements of NMR residual dipolar couplings. The good agreement with experimental measures of global structure such as single-molecule Förster resonance energy transfer (FRET) efficiencies is improved further by ensemble refinement. By comparing wild-type and mutant ensembles, we show that pathogenic single-point P301L, P301S, and P301T mutations shift the population from the turn-like conformations of the functional microtubule-bound state to the extended conformations of disease-associated tau fibrils. RHCG thus provides us with an atomically detailed view of the population equilibrium between functional and aggregation-prone states of tau K18, and demonstrates that global structural characteristics of this intrinsically disordered protein emerge from its local structure.

Effects of subchronic dietary exposure to the engineered nanomaterials SiO2 and CeO2 in C57BL/6J and 5xFAD Alzheimer model mice

BACKGROUND

There is an increasing concern about the neurotoxicity of engineered nanomaterials (NMs). To investigate the effects of subchronic oral exposures to SiO2 and CeO2 NMs on Alzheimer's disease (AD)-like pathology, 5xFAD transgenic mice and their C57BL/6J littermates were fed ad libitum for 3 or 14 weeks with control food pellets, or pellets dosed with these respective NMs at 0.1% or 1% (w/w). Behaviour effects were evaluated by X-maze, string suspension, balance beam and open field tests. Brains were analysed for plaque load, beta-amyloid peptide levels, markers of oxidative stress and neuroinflammation.

RESULTS

No marked behavioural impairments were observed in the mice exposed to SiO2 or CeO2 and neither treatment resulted in accelerated plaque formation, increased oxidative stress or inflammation. In contrast, the 5xFAD mice exposed to 1% CeO2 for 14 weeks showed significantly lower hippocampal Aβ plaque load and improved locomotor activity compared to the corresponding controls.

CONCLUSIONS

The findings from the present study suggest that long-term oral exposure to SiO2 or CeO2 NMs has no neurotoxic and AD-promoting effects. The reduced plaque burden observed in the mice following dietary CeO2 exposure warrants further investigation to establish the underlying mechanism, given the easy applicability of this administration method.

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.

Unifying coarse-grained force fields for folded and disordered proteins

Liquid-liquid phase separation drives the formation of biological condensates that play essential roles in transcriptional regulation and signal sensing. Computational modeling could provide high-resolution structural characterizations of these condensates and help uncover physicochemical interactions that dictate their stability. However, many protein molecules involved in phase separation often contain multiple ordered domains connected with flexible, structureless linkers. Simulating such proteins necessitates force fields with consistent accuracy for both folded and disordered proteins. We provide a critical review of existing coarse-grained force fields for disordered proteins and highlight the challenges in their application to folded proteins. After discussing existing algorithms for force field parameterization, we propose an optimization strategy that should lead to computer models with improved transferability across protein types.

Examining the Ensembles of Amyloid-β Monomer Variants and Their Propensities to Form Fibers Using an Energy Landscape Visualization Method

The amyloid-β (Aβ) monomer, an intrinsically disordered peptide, is produced by the cleavage of the amyloid precursor protein, leading to Aβ-40 and Aβ-42 as major products. These two isoforms generate pathological aggregates, whose accumulation correlates with Alzheimer's disease (AD). Experiments have shown that even though the natural abundance of Aβ-42 is smaller than that for Aβ-40, the Aβ-42 is more aggregation-prone compared to Aβ-40. Moreover, several single-point mutations are associated with early onset forms of AD. This work analyzes coarse-grained associative-memory, water-mediated, structure and energy model (AWSEM) simulations of normal Aβ-40 and Aβ-42 monomers, along with six single-point mutations associated with early onset disease. We analyzed the simulations using the energy landscape visualization method (ELViM), a reaction-coordinate-free approach suited to explore the frustrated energy landscapes of intrinsically disordered proteins. ELViM is shown to distinguish the monomer ensembles of variants that rapidly form fibers from those that do not form fibers as readily. It also delineates the amino acid contacts characterizing each ensemble. The results shed light on the potential of ELViM to probe intrinsically disordered proteins.

Small Angle X-ray Scattering Sensing Membrane Composition: The Role of Sphingolipids in Membrane-Amyloid β-Peptide Interaction

Simple Summary

The early impairments in Alzheimer’s disease are related to neuronal membrane damage. Different lipids are present in biological membranes, playing relevant physiological roles. Some of them, such as sphingomyelin, cholesterol, and ganglioside GM1, interact with each other and, importantly, with the Aβ peptide. Here, these interactions are studied using small angle X-ray scattering in model membrane systems, such as large unilamellar liposomes. This technique gives information on the width of the bilayer and reveals structural differences due to the different lipid compositions, as well as some small differences due to the presence of the Aβ peptide. The analysis highlights the concentration-dependent effect of GM1 on membrane thickness and the interaction with the Aβ-peptide, together with the inhibiting effect that the presence of sphingomyelin has on the GM1–Aβ interaction.

Abstract

The early impairments appearing in Alzheimer’s disease are related to neuronal membrane damage. Both aberrant Aβ species and specific membrane components play a role in promoting aggregation, deposition, and signaling dysfunction. Ganglioside GM1, present with cholesterol and sphingomyelin in lipid rafts, preferentially interacts with the Aβ peptide. GM1 at physiological conditions clusters in the membrane, the assembly also involves phospholipids, sphingomyelin, and cholesterol. The structure of large unilamellar vesicles (LUV), made of a basic POPC:POPS matrix in a proportion of 9:1, and containing different amounts of GM1 (1%, 3%, and 4% mol/mol) in the presence of 5% mol/mol sphingomyelin and 15% mol/mol cholesterol, was studied using small angle X-ray scattering (SAXS). The effect of the membrane composition on the LUVs–Aβ-peptide interaction, both for Aβ_1–40 and Aβ_1–42 variants, was, thus, monitored. The presence of GM1 leads to a significant shift of the main peak, towards lower scattering angles, up to 6% of the initial value with SM and 8% without, accompanied by an opposite shift of the first minimum, up to 21% and 24% of the initial value, respectively. The analysis of the SAXS spectra, using a multi-Gaussian model for the electronic density profile, indicated differences in the bilayer of the various compositions. An increase in the membrane thickness, by 16% and 12% when 2% and 3% mol/mol GM1 was present, without and with SM, respectively, was obtained. Furthermore, in these cases, in the presence of Aβ₄₀, a very small decrease of the bilayer thickness, less than 4% and 1%, respectively, was derived, suggesting the inhibiting effect that the presence of sphingomyelin has on the GM1–Aβ interaction.

Sequence Determines the Switch in the Fibril Forming Regions in the Low-Complexity FUS Protein and Its Variants

Residues spanning distinct regions of the low-complexity domain of the RNA-binding protein, Fused in Sarcoma (FUS-LC), form fibril structures with different core morphologies. Solid-state NMR experiments show that the 214-residue FUS-LC forms a fibril with an S-bend (core-1, residues 39-95), while the rest of the protein is disordered. In contrast, the fibrils of the C-terminal variant (FUS-LC-C; residues 111-214) have a U-bend topology (core-2, residues 112-150). Absence of the U-bend in FUS-LC implies that the two fibril cores do not coexist. Computer simulations show that these perplexing findings could be understood in terms of the population of sparsely populated fibril-like excited states in the monomer. The propensity to form core-1 is higher compared to core-2. We predict that core-2 forms only in truncated variants that do not contain the core-1 sequence. At the monomer level, sequence-dependent enthalpic effects determine the relative stabilities of the core-1 and core-2 topologies.

Nanomechanical Stability of Aβ Tetramers and Fibril-like Structures: Molecular Dynamics Simulations

Alzheimer's disease (AD) is a neurodegenerative disorder and one of the main causes of dementia. The disease is associated with amyloid beta (Aβ) peptide aggregation forming initial clusters and then fibril structure and plaques. Other neurodegenerative diseases such as type 2 diabetes, amyotrophic lateral sclerosis, and Parkinson's disease follow a similar mechanism. Therefore, inhibition of Aβ aggregation is considered an effective way to prevent AD. Recent experiments have provided evidence that oligomers are more toxic agents than mature fibrils, prompting researchers to investigate various factors that may influence their properties. One of these factors is nanomechanical stability, which plays an important role in the self-assembly of Aβ and possibly other proteins. This stability is also likely to be related to cell toxicity. In this work, we compare the mechanical stability of Aβ-tetramers and fibrillar structures using a structure-based coarse-grained (CG) approach and all-atom molecular dynamics simulation. Our results support the evidence for an increase in mechanical stability during the Aβ fibrillization process, which is consistent with in vitro AFM characterization of Aβ42 oligomers. Namely, using a CG model, we showed that the Young modulus of tetramers is lower than that of fibrils and, as follows from the experiment, is about 1 GPa. Hydrogen bonds are the dominant contribution to the detachment of one chain from the Aβ fibril fragment. They tend to be more organized along the pulling direction, whereas in the Aβ tetramers no preference is observed.

Improved coarse-grained model for studying sequence dependent phase separation of disordered proteins

We present improvements to the hydropathy scale (HPS) coarse-grained (CG) model for simulating sequence-specific behavior of intrinsically disordered proteins (IDPs), including their liquid-liquid phase separation (LLPS). The previous model based on an atomistic hydropathy scale by Kapcha and Rossky (KR scale) is not able to capture some well-known LLPS trends such as reduced phase separation propensity upon mutations (R-to-K and Y-to-F). Here, we propose to use the Urry hydropathy scale instead, which was derived from the inverse temperature transitions in a model polypeptide with guest residues X. We introduce two free parameters to shift (Δ) and scale (µ) the overall interaction strengths for the new model (HPS-Urry) and use the experimental radius of gyration for a diverse group of IDPs to find their optimal values. Interestingly, many possible (Δ, µ) combinations can be used for typical IDPs, but the phase behavior of a low-complexity (LC) sequence FUS is only well described by one of these models, which highlights the need for a careful validation strategy based on multiple proteins. The CG HPS-Urry model should enable accurate simulations of protein LLPS and provide a microscopically detailed view of molecular interactions.

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.

Molecular simulations of IDPs: From ensemble generation to IDP interactions leading to disorder-to-order transitions

Intrinsically disordered proteins (IDPs) lack a well-defined three-dimensional structure but do exhibit some dynamical and structural ordering. The structural plasticity of IDPs indicates that entropy-driven motions are crucial for their function. Many IDPs undergo function-related disorder-to-order transitions upon by their interaction with specific binding partners. Approaches that are based on both experimental and theoretical tools enable the biophysical characterization of IDPs. Molecular simulations provide insights into IDP structural ensembles and disorder-to-order transition mechanisms. However, such studies depend strongly on the chosen force field parameters and simulation techniques. In this chapter, we provide an overview of IDP characteristics, review all-atom force fields recently developed for IDPs, and present molecular dynamics-based simulation methods that allow IDP ensemble generation as well as the characterization of disorder-to-order transitions. In particular, we introduce metadynamics, replica exchange molecular dynamics simulations, and also kinetic models resulting from Markov State modeling, and provide various examples for the successful application of these simulation methods to IDPs.