Different Force Fields Give Rise to Different Amyloid Aggregation Pathways in Molecular Dynamics Simulations

Effect of Cholesterol Molecules on Aβ1-42 Wild-Type and Mutants Trimers

Alzheimer’s disease displays aggregates of the amyloid-beta (Aβ) peptide in the brain, and there is increasing evidence that cholesterol may contribute to the pathogenesis of the disease. Though many experimental and theoretical studies have focused on the interactions of Aβ oligomers with membrane models containing cholesterol, an understanding of the effect of free cholesterol on small Aβ42 oligomers is not fully established. To address this question, we report on replica exchange with a solute tempering simulation of an Aβ42 trimer with cholesterol and compare it with a previous replica exchange molecular dynamics simulation. We show that the binding hot spots of cholesterol are rather complex, involving hydrophobic residues L17–F20 and L30–M35 with a non-negligible contribution of loop residues D22–K28 and N-terminus residues. We also examine the effects of cholesterol on the trimers of the disease-causing A21G and disease-protective A2T mutations by molecular dynamics simulations. We show that these two mutations moderately impact cholesterol-binding modes. In our REST2 simulations, we find that cholesterol is rarely inserted into aggregates but rather attached as dimers and trimers at the surface of Aβ42 oligomers. We propose that cholesterol acts as a glue to speed up the formation of larger aggregates; this provides a mechanistic link between cholesterol and Alzheimer’s disease.

Multiscale Computational Study of the Conformation of the Full-Length Intrinsically Disordered Protein MeCP2

The malfunction of the methyl-CpG binding protein 2 (MeCP2) is associated with the Rett syndrome, one of the most common causes of cognitive impairment in females. MeCP2 is an intrinsically disordered protein (IDP), making its experimental characterization a challenge. There is currently no structure available for the full-length MeCP2 in any of the databases, and only the structure of its MBD domain has been solved. We used this structure to build a full-length model of MeCP2 by completing the rest of the protein via ab initio modeling. Using a combination of all-atom and coarse-grained simulations, we characterized its structure and dynamics as well as the conformational space sampled by the ID and transcriptional repression domain (TRD) domains in the absence of the rest of the protein. The present work is the first computational study of the full-length protein. Two main conformations were sampled in the coarse-grained simulations: a globular structure similar to the one observed in the all-atom force field and a two-globule conformation. Our all-atom model is in good agreement with the available experimental data, predicting amino acid W104 to be buried, amino acids R111 and R133 to be solvent-accessible, and having a 4.1% α-helix content, compared to the 4% found experimentally. Finally, we compared the model predicted by AlphaFold to our Modeller model. The model was not stable in water and underwent further folding. Together, these simulations provide a detailed (if perhaps incomplete) conformational ensemble of the full-length MeCP2, which is compatible with experimental data and can be the basis of further studies, e.g., on mutants of the protein or its interactions with its biological partners.

Early aggregation mechanism of Aβ16-22 revealed by Markov state models

Aβ_16-22 is believed to have critical role in early aggregation of full length amyloids that are associated with the Alzheimer's disease and can aggregate to form amyloid fibrils. However, the early aggregation mechanism is still unsolved. Here, multiple long-term molecular dynamics simulations combining with Markov state model were used to probe the early oligomerization mechanism of Aβ_16-22 peptides. The identified dimeric form adopted either globular random-coil or extended β-strand like conformations. The observed dimers of these variants shared many overall conformational characteristics but differed in several aspects at detailed level. In all cases, the most common type of secondary structure was intermolecular antiparallel β-sheets. The inter-state transitions were very frequent ranges from few to hundred nanoseconds. More strikingly, those states which contain fraction of β secondary structure and significant amount of extended coiled structures, therefore exposed to the solvent, were majorly participated in aggregation. The assembly of low-energy dimers, in which the peptides form antiparallel β sheets, occurred by multiple pathways with the formation of an obligatory intermediates. We proposed that these states might facilitate the Aβ_16-22 aggregation through a significant component of the conformational selection mechanism, because they might increase the aggregates population by promoting the inter-chain hydrophobic and the hydrogen bond contacts. The formation of early stage antiparallel β sheet structures is critical for oligomerization, and at the same time provided a flat geometry to seed the ordered β-strand packing of the fibrils. Our findings hint at reorganization of this part of the molecule as a potentially critical step in Aβ aggregation and will insight into early oligomerization for large β amyloids.

Conformational Tuning of Amylin by Charged Styrene-Maleic-Acid Copolymers

Human amylin forms structurally heterogeneous amyloids that have been linked to type-2 diabetes. Thus, understanding the molecular interactions governing amylin aggregation can provide mechanistic insights in its pathogenic formation. Here, we demonstrate that fibril formation of amylin is altered by synthetic amphipathic copolymer derivatives of the styrene-maleic-acid (SMAQA and SMAEA). High-speed AFM is used to follow the real-time aggregation of amylin by observing the rapid formation of de novo globular oligomers and arrestment of fibrillation by the positively-charged SMAQA. We also observed an accelerated fibril formation in the presence of the negatively-charged SMAEA. These findings were further validated by fluorescence, SOFAST-HMQC, DOSY and STD NMR experiments. Conformational analysis by CD and FT-IR revealed that the SMA copolymers modulate the conformation of amylin aggregates. While the species formed with SMAQA are α-helical, the ones formed with SMAEA are rich in β-sheet structure. The interacting interfaces between SMAEA or SMAQA and amylin are mapped by NMR and microseconds all-atom MD simulation. SMAEA displayed π-π interaction with Phe23, electrostatic π-cation interaction with His18 and hydrophobic packing with Ala13 and Val17; whereas SMAQA showed a selective interaction with amylin's C terminus (residues 31-37) that belongs to one of the two β-sheet regions (residues 14-19 and 31-36) involved in amylin fibrillation. Toxicity analysis showed both SMA copolymers to be non-toxic in vitro and the amylin species formed with the copolymers showed minimal deformity to zebrafish embryos. Together, this study demonstrates that chemical tools, such as copolymers, can be used to modulate amylin aggregation, alter the conformation of species.

How the Choice of Force-Field Affects the Stability and Self-Assembly Process of Supramolecular CTA Fibers

In recent years, computational methods have become an essential element of studies focusing on the self-assembly process. Although they provide unique insights, they face challenges, from which two are the most often mentioned in the literature: the temporal and spatial scale of the self-assembly. A less often mentioned issue, but not less important, is the choice of the force-field. The repetitive nature of the supramolecular structure results in many similar interactions. Consequently, even a small deviation in these interactions can lead to significant energy differences in the whole structure. However, studies comparing different force-fields for self-assembling systems are scarce. In this article, we compare molecular dynamics simulations for trifold hydrogen-bonded fibers performed with different force-fields, namely GROMOS, CHARMM General Force Field (CGenFF), CHARMM Drude, General Amber Force-Field (GAFF), Martini, and polarized Martini. Briefly, we tested the force-fields by simulating: (i) spontaneous self-assembly (none form a fiber within 500 ns), (ii) stability of the fiber (observed for CHARMM Drude, GAFF, MartiniP), (iii) dimerization (observed for GROMOS, GAFF, and MartiniP), and (iv) oligomerization (observed for CHARMM Drude and MartiniP). This system shows that knowledge of the force-field behavior regarding interactions in oligomer and larger self-assembled structures is crucial for designing efficient simulation protocols for self-assembling systems.

Dynamics of Amyloid Formation from Simplified Representation to Atomistic Simulations

Amyloid fibril formation is an intrinsic property of short peptides, non-disease proteins, and proteins associated with neurodegenerative diseases. Aggregates of the Aβ and tau proteins, the α-synuclein protein, and the prion protein are observed in the brain of Alzheimer's, Parkinson's, and prion disease patients, respectively. Due to the transient short-range and long-range interactions of all species and their high aggregation propensities, the conformational ensemble of these devastating proteins, the exception being for the monomeric prion protein, remains elusive by standard structural biology methods in bulk solution and in lipid membranes. To overcome these limitations, an increasing number of simulations using different sampling methods and protein models have been performed. In this chapter, we first review our main contributions to the field of amyloid protein simulations aimed at understanding the early aggregation steps of short linear amyloid peptides, the conformational ensemble of the Aβ40/42 dimers in bulk solution, and the stability of Aβ aggregates in lipid membrane models. Then we focus on our studies on the interactions of amyloid peptides/inhibitors to prevent aggregation, and long amyloid sequences, including new results on a monomeric tau construct.

Disorder-to-order transition of the amyloid-β peptide upon lipid binding

There is mounting evidence that Alzheimer's disease progression and severity are linked to neuronal membrane damage caused by aggregates of the amyloid-β (Aβ) peptide. However, the detailed mechanism behind the membrane damage is not well understood yet. Recently, the lipid-chaperone hypothesis has been put forward, based on which the formation of complexes between Aβ and free lipids enables an easy insertion of Aβ into membranes. In order to test this hypothesis, we performed numerous all-atom molecular dynamics simulations. We studied the complex formation between individual lipids, considering both POPC and DPPC, and Aβ and examined whether the resulting complexes would be able to insert into lipid membranes. Complex formation at a one-to-one ratio was readily observed, yet with minimal effects on Aβ's characteristics. Most importantly, the peptide remains largely disordered in 1:1 complexes, and the complex does not insert into the membrane; instead, it is adsorbed to the membrane surface. The results change considerably once Aβ forms a complex with a POPC cluster composed of three lipid molecules. The hydrophobic interactions between Aβ and the lipid tails cause the peptide to fold into either a helical or a β-sheet structure. These observations provide atomic insight into the disorder-to-order transition that is needed for membrane insertion or amyloid aggregation to proceed.

From molecular dynamics to quantum mechanics of misfolded proteins and amyloid-like macroaggregates applied to neurodegenerative diseases

A misfolded protein compared with its native state lacks its biological function resulting in cell dysregulations and often death. Outdated hypotheses on protein folding must be revised: More realistic molecular models, focusing not only on classical molecular dynamics (MD) but also on ab initio quantum mechanics (QM) at the molecular orbitals (MOs) scale, which is not experimentally achievable, are presented to improve our understanding of the thermodynamics of the protein-protein interactions leading to misfolding and neurodegenerative diseases for future drug design. Protein misfolding is characterized by the formation of highly reactive beta-sheets oligomers leading to fibrillar macroscopic aggregates, which are studied with the models given herein that can be useful for the development of new immunotherapies against the Alzheimer's disease and prion, e.g. The example of the prion - an intrinsically disordered protein - is studied, but the models can be generalized to other misfolding diseases. The binding free energy and interactions in a complex of a misfolded prion with a native prion are first analyzed by MD and compared to a complex of two native conformers. A conversion of residues to toxic beta-sheets is observed in the optimized misfolded complex. Then, QM is used to compute, with a much better accuracy than that of MD, the binding free energy of the hydrophobic binding site, responsible of the aggregation, between the bound misfolded and native conformers in the misfolded complex. The latter quantity is significantly negative, so that aggregation is strong and fast. The frontier MOs from QM are used for docking to determine how the first repetitive beta-sheets building blocks of the nanofibrils can be assembled from initial cleaved complexes of the native and misfolded proteins. Successive aggregation of multiple monomers leads to an amyloid-like nanofibril that grows along a principal elongation direction, as also observed experimentally.

Effects of All-Atom Molecular Mechanics Force Fields on Amyloid Peptide Assembly: The Case of PHF6 Peptide of Tau Protein

Molecular dynamics (MD) simulations play a vital role in revealing the mechanism of amyloid aggregation that is crucial to the therapeutic agent development for Alzheimer's Disease. However, the accuracy of MD simulation results strongly depends on the force field employed. In our previous benchmark for 17 all-atom force fields on modeling of amyloid aggregation using the Aβ_16-22 dimer, we showed that AMBER14SB and CHARMM36m are suitable force fields for amyloid aggregation simulation, while GROMOS54a7 and OPLSAA are not good for the task. In this work, we continue assessing the applicability of atomistic force fields on amyloid aggregation using the VQIVYK (PHF6) peptide which is essential for tau-protein aggregation. Although, both Aβ_16-22 and PHF6 peptides formed fibrils in vitro, the PHF6 fibrils are parallel β-sheets, while the Aβ_16-22 fibrils are antiparallel β-sheets. We performed an all-atom large-scale MD simulation in explicit water on the PHF6 dimer and octa-peptides systems using five mainstream force fields, including AMBER99SB-disp, AMBER14SB, CHARMM36m, GROMOS54a7, and OPLSAA. The accumulated simulation time is 0.2 ms. Our result showed that the β-sheet structures of PHF6 peptides sampled by AMBER99SB-disp, AMBER14SB, GROMOS54a7, and OPLSAA are in favor of the antiparallel β-sheets, while the dominant type of β-sheet structures is parallel β-sheet by using CHARMM36m. Among the five force fields, CHARMM36m provides the strongest CH-π interaction that was observed in an NMR study. The comparison between our results and experimental observation indicates that CHARMM36m achieved the best performance on modeling the aggregation of PHF6 peptides. In summary, CHARMM36m is currently the most suitable force field for studying the aggregation of both amyloid-β and Tau through MD simulations.

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.

Comparison of the force fields on monomeric and fibrillar PHF6 of tau protein

The hexapeptide 306VQIVYK311 (PHF6) plays an important role in the aggregation of Tau protein, which is a hallmark of the Alzheimer's disease (AD). In this article, we systematically compare the effects of eight popular all-atom force fields on the monomeric and fibrillar PHF6 in the molecular dynamics (MD) simulations, which could be helpful in the computer-aided drug design against PHF6. We show that the fibrillar PHF6 prefers β-strand-like structures in all the force fields while the monomer has different structural preferences depending on the force fields. The interactions for stabilizing the fibril are further investigated. In the end, according to the interactions revealed by NMR and the stability of the fibril in the literature, we benchmark the force fields.

Amyloid-β peptide dimers undergo a random coil to β-sheet transition in the aqueous phase but not at the neuronal membrane

Mounting evidence suggests that the neuronal cell membrane is the main site of oligomer-mediated neuronal toxicity of amyloid-β peptides in Alzheimer's disease. To gain a detailed understanding of the mutual interference of amyloid-β oligomers and the neuronal membrane, we carried out microseconds of all-atom molecular dynamics (MD) simulations on the dimerization of amyloid-β (Aβ)42 in the aqueous phase and in the presence of a lipid bilayer mimicking the in vivo composition of neuronal membranes. The dimerization in solution is characterized by a random coil to β-sheet transition that seems on pathway to amyloid aggregation, while the interactions with the neuronal membrane decrease the order of the Aβ42 dimer by attenuating its propensity to form a β-sheet structure. The main lipid interaction partners of Aβ42 are the surface-exposed sugar groups of the gangliosides GM1. As the neurotoxic activity of amyloid oligomers increases with oligomer order, these results suggest that GM1 is neuroprotective against Aβ-mediated toxicity.

Molecular dynamics study of conformation transition from helix to sheet of Aβ42 peptide

Aβ42 peptides can form helix and sheet structure under different conditions. The conformational conversion is closely associated with Aβ peptides aggregation and their neurotoxicity. But the transition from helix to sheet is not be clearly understood. In this study we performed microsecond timescale MD simulations of Aβ42 peptide to investigate the conformation transition from α-helix to β-sheet. Markov state model (MSM) was built to facilitate identification of crucial intermediate states and possible transition pathway. Based on the analysis, we found that the region Y10-A21 in the middle of Aβ42 peptide plays an initial role in this transition. MSM model revealed that the collapse of helical structure in this region might trigger the formation of sheet structure. Moreover, we further simulated the aggregation of Aβ42 peptides with different conformations. We found that the Aβ42 peptides forming sheet structure have higher aggregation potential compared with peptides with helix structure. These results demonstrate that we can prevent the aggregation of Aβ42 peptides by stabilizing the helix structure in the region of Y10-A21. In addition, this study provides new insight into better understanding the conformational transition and aggregation of Aβ42 peptides.

Molecular dynamic study of alcohol-based deep eutectic solvents

The applicability of deep eutectic solvents is determined by their physicochemical properties. In turn, the properties of eutectic mixtures are the result of the components' molar ratio and chemical composition. Owing to the relatively low viscosities displayed by alcohol-based deep eutectic solvents (DESs), their application in industry is more appealing. Modeling the composition-property relationships established in polyalcohol-based mixtures is crucial for both understanding and predicting their behavior. In this work, a physicochemical property-structure comparison study is made between four choline chloride polyalcohol-based DESs, namely, ethaline, propeline, propaneline, and glyceline. Physicochemical properties obtained from molecular dynamic simulations are compared to experimental data, whenever possible. The simulations cover the temperature range from 298.15 to 348.15 K. The simulated and literature experimental data are generally in good agreement for all the studied DESs. Structural properties, such as radial and spatial distribution functions, coordination numbers, hydrogen bond donor (HBD)-HBD aggregate formation, and hydrogen bonding are analyzed in detail. The higher prevalence of HBD:HBD and HBD:anion hydrogen bonds is likely to be the major reason for the relatively high density and viscosity of glyceline as well as for lower DES self-diffusions.

The Effects of Different Glycosaminoglycans on the Structure and Aggregation of the Amyloid-β (16-22) Peptide

Aggregates of the amyloid-β (Aβ) peptide are implicated as a causative substance in Alzheimer's disease. Molecular dynamics simulations provide valuable contributions for elucidating the conformational transitions of monomeric and aggregated forms of Aβ be it in solution or in the presence of other molecules. Here, we study the effects of four different glycosaminoglycans (GAGs), three sulfated ones and a nonsulfated one, on the aggregation of Aβ_16-22. From experiments, it has been suggested that GAGs, which belong to the main components of the brain's extracellular space, favor amyloid fibril formation. Our simulation results reveal that the binding of Aβ_16-22 to the GAGs is driven by electrostatic attraction between the negative GAG charges and the positively charged K16 of Aβ_16-22. While these interactions have only minor effects on the GAG and Aβ_16-22 conformations at the 1 Aβ_16-22/1 GAG ratio, at the 2:2 stoichiometry the aggregation of Aβ_16-22 is considerably changed. In solution, the aggregation of Aβ_16-22 is strongly influenced by K16-E22 attraction, leading to antiparallel β-sheets. In the presence of GAGs, on the other hand, the interaction of K16 with the GAGs increases the importance of the hydrophobic interactions during Aβ_16-22 aggregation, which in turn yields parallel alignments. A templating and ordering effect of the GAGs on the Aβ_16-22 aggregates is observed. In summary, this study provides new insight at the atomic level on GAG-amyloid interactions, strengthening the view that sulfation of the GAGs plays a major role in this context.

Assessment of transferable forcefields for protein simulations attests improved description of disordered states and secondary structure propensities, and hints at multi-protein systems as the next challenge for optimization

Continuous assessment of transferable forcefields for molecular simulations is essential to identify their weaknesses and direct improvement efforts. The latest efforts focused on better describing disordered proteins while retaining proper description of folded domains, important because forcefields of the previous generations produce overly compact disordered states. Such improvements should additionally alleviate the related problem of over-stabilized protein–protein interactions, which has been largely overlooked. Here we evaluated three state-of-the-art forcefields, current flagships of their respective developers, optimized for ordered and disordered proteins: CHARMM36m with its recommended corrected TIP3P* water, ff19SB with the recommended OPC water, and the 2019 a99SBdisp forcefield by D. E. Shaw Research with its modified TIP4P water; plus ff14SB with TIP3P as an example of the former generation of forcefields. Our evaluation entailed simulations of (i) multiple copies of a protein that is highly soluble yet undergoes weak dimerization, (ii) a disordered peptide with low, well-characterized alpha helical propensity, and (iii) a peptide known to form insoluble β-aggregates. Our results recapitulate ff14SB-TIP3P over-stabilizing aggregates and secondary structures and place a99SBdisp-TIP4PD at the other end i.e. predicting overly weak intermolecular interactions despite reasonably predicting secondary structure propensities. In-between, CHARMM36m-TIP3P* still over-stabilizes aggregates but predicts residue-wise alpha helical propensities in solution slightly better than ff19SB-OPC, while ff19SB-OPC poses the best prediction of weak dimerization of the soluble protein still predicting aggregation of the β-peptides. This independent assessment shows that the claimed forcefield improvements are real, but also that a right balance between noncovalent attraction and repulsion has not yet been reached. We thus propose developers to consider systems like those tested here in their forcefield tuning protocols. Last, the good performance of CHARMM36m-TIP3P* further shows that tuning 3-point water models might still be an alternative to the more costly 4-point models like OPC and TIP4PD.

Potential of ATP toward Prevention of hIAPP Oligomerization and Destabilization of hIAPP Protofibrils: An In Silico Perspective

The aggregation of an intrinsically disordered protein, human islet amyloid polypeptide (hIAPP), leads to one of the most prevalent endocrine disorders, type II diabetes mellitus (T2DM). Hence inhibition of hIAPP aggregation provides a possible therapeutic approach for the treatment of T2DM. In this regard, a new aspect of adenosine triphosphate (ATP), which is widely known as the energy source for biological reactions, has recently been discovered, where it can inhibit the formation of protein aggregates and simultaneously dissolve preformed aggregates at a millimolar concentration scale. In this work, we investigate the effect of ATP on the aggregation of an amyloidogenic segment of hIAPP, hIAPP_22-28, and also of the full length sequence. Using all-atom classical molecular dynamics simulations, we observe that the tendency of hIAPP to oligomerize into β-sheet conformers is inhibited by ATP, due to which the peptides remain distant, loosely packed random monomers. Moreover, it can also disassemble preformed hIAPP protofibrils. ATP preferentially interacts with the hydrophobic residues of hIAPP_22-28 fragment and the terminal and turn residues of the full length peptide. The hydrogen bonding, hydrophobic, π-π, and N-H-π stacking interactions are the driving forces for the ATP induced inhibition of hIAPP aggregation. Interestingly, the hydrophobic adenosine of ATP is found to be more in contact with the peptide residues than the hydrophilic triphosphate moiety. The insight into the inhibitory mechanism of ATP on hIAPP aggregation can prove to be beneficial for the design of novel amyloid inhibitors in the future.

Cholesterol Molecules Alter the Energy Landscape of Small Aβ1-42 Oligomers

Small amyloid-β (Aβ) oligomers are believed to be key pathogenic species in Alzheimer's disease (AD). One suggested toxicity mechanism is the detergent model where oligomers remove lipid molecules from the bilayer. Senile plaques of AD patients also accumulate a 1:1 ratio of cholesterol/Aβ. What are the dominant structures of small Aβ42 oligomers with cholesterol molecules in aqueous solution? Here, we answer this question by performing atomistic replica exchange molecular dynamics simulations of Aβ42 dimers and trimers. Our simulations demonstrate that the interactions with cholesterol molecules change completely the energy landscape of small Aβ42 oligomers. This result shows that simulations in the bulk solution cannot recapitulate aggregation in the brain extracellular space.

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

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

Recent Force Field Strategies for Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDPs) are widely distributed across eukaryotic cells, playing important roles in molecular recognition, molecular assembly, post-translational modification, and other biological processes. IDPs are also associated with many diseases such as cancers, cardiovascular diseases, and neurodegenerative diseases. Due to their structural flexibility, conventional experimental methods cannot reliably capture their heterogeneous structures. Molecular dynamics simulation becomes an important complementary tool to quantify IDP structures. This review covers recent force field strategies proposed for more accurate molecular dynamics simulations of IDPs. The strategies include adjusting dihedral parameters, adding grid-based energy correction map (CMAP) parameters, refining protein-water interactions, and others. Different force fields were found to perform well on specific observables of specific IDPs but also are limited in reproducing all available experimental observables consistently for all tested IDPs. We conclude the review with perspective areas for improvements for future force fields for IDPs.

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.

Amyloid aggregation simulations: challenges, advances and perspectives

In amyloid aggregation diseases soluble proteins coalesce into a wide array of undesirable structures, ranging through oligomers and prefibrillar assemblies to highly ordered amyloid fibrils and plaques. Explicit-solvent all-atom molecular dynamics (MD) simulations of amyloid aggregation have been performed for almost 20 years, revealing valuable information about this phenomenon. However, these simulations are challenged by three main problems. Firstly, current force fields modeling amyloid aggregation are insufficiently accurate. Secondly, the protein concentrations in MD simulations are usually orders of magnitude higher than those used in vitro or found in vivo, which has direct consequences on the aggregates that form. Finally, the third problem is the well-known time-scale limit of MD simulations. In this review I highlight recent approaches to overcome these three limitations.