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

Comprehending the Efficacy of Whitlock's Caffeine-Pincered Molecular Tweezer on β-Amyloid Aggregation

Alzheimer's disease (AD) stands as one of the most prevalent neurodegenerative conditions, leading to cognitive impairment, with no cure and preventive measures. Misfolding and aberrant aggregation of amyloid-β (Aβ) peptides are believed to be the underlying cause of AD. These amyloid aggregates culminate in the development of toxic Aβ oligomers and subsequent accumulation of β-amyloid plaques amidst neuronal cells in the brain, marking the hallmarks of AD. Drug development for the potentially curative treatment of Alzheimer's is, therefore, a tremendous challenge for the scientific community. In this study, we investigate the potency of Whitlock's caffeine-armed molecular tweezer in combating the deleterious effects of Aβ aggregation, with special emphasis on the seven residue Aβ16-22 fragment. Extensive all-atom molecular dynamics simulations are conducted to probe the various structural and conformational transitions of the peptides in an aqueous medium in both the presence and absence of tweezers. To explore the specifics of peptide-tweezer interactions, radial distribution functions, contact number calculations, binding free energies, and 2-D kernel density plots depicting the variation of distance-angle between the aromatic planes of the peptide-tweezer pair are computed. The central hydrophobic core, particularly the aromatic Phe residues, is crucial in the development of harmful amyloid oligomers. Notably, all analyses indicate reduced interpeptide interactions in the presence of the tweezer, which is attributed to the tweezer-Phe aromatic interaction. Upon increasing the tweezer concentration, the residues of the peptide are further encased in a hydrophobic environment created by the self-aggregating tweezer cluster, leading to the segregation of the peptide residues. This is further aided by the weakening of interstrand hydrogen bonding between the peptides, thereby impeding their self-aggregation and preventing the formation of neurotoxic β-amyloid. Furthermore, the study also highlights the efficacy of the molecular tweezer in destabilizing preformed amyloid fibrils as well as hindering the aggregation of the full-length Aβ1-42 peptide.

Tips and Tricks in the Modeling of Supramolecular Peptide Assemblies

Supramolecular peptide assemblies (SPAs) hold promise as materials for nanotechnology and biomedicine. Although their investigation often entails adapting experimental techniques from their protein counterparts, SPAs are fundamentally distinct from proteins, posing unique challenges for their study. Computational methods have emerged as indispensable tools for gaining deeper insights into SPA structures at the molecular level, surpassing the limitations of experimental techniques, and as screening tools to reduce the experimental search space. However, computational studies have grappled with issues stemming from the absence of standardized procedures and relevant crystal structures. Fundamental disparities between SPAs and protein simulations, such as the absence of experimentally validated initial structures and the importance of the simulation size, number of molecules, and concentration, have compounded these challenges. Understanding the roles of various parameters and the capabilities of different models and simulation setups remains an ongoing endeavor. In this review, we aim to provide readers with guidance on the parameters to consider when conducting SPA simulations, elucidating their potential impact on outcomes and validity.

Photocontrolled Reversible Amyloid Fibril Formation of Parathyroid Hormone-Derived Peptides

Peptide fibrillization is crucial in biological processes such as amyloid-related diseases and hormone storage, involving complex transitions between folded, unfolded, and aggregated states. We here employ light to induce reversible transitions between aggregated and nonaggregated states of a peptide, linked to the parathyroid hormone (PTH). The artificial light-switch 3-{[(4-aminomethyl)phenyl]diazenyl}benzoic acid (AMPB) is embedded into a segment of PTH, the peptide PTH25-37, to control aggregation, revealing position-dependent effects. Through in silico design, synthesis, and experimental validation of 11 novel PTH25-37-derived peptides, we predict and confirm the amyloid-forming capabilities of the AMPB-containing peptides. Quantum-chemical studies shed light on the photoswitching mechanism. Solid-state NMR studies suggest that β-strands are aligned parallel in fibrils of PTH25-37, while in one of the AMPB-containing peptides, β-strands are antiparallel. Simulations further highlight the significance of π-π interactions in the latter. This multifaceted approach enabled the identification of a peptide that can undergo repeated phototriggered transitions between fibrillated and defibrillated states, as demonstrated by different spectroscopic techniques. With this strategy, we unlock the potential to manipulate PTH to reversibly switch between active and inactive aggregated states, representing the first observation of a photostimulus-responsive hormone.

The Secret Ballet Inside Multivesicular Bodies

Lipid bilayers possess the capacity for self-assembly due to the amphipathic nature of lipid molecules, which have both hydrophobic and hydrophilic regions. When confined, lipid bilayers exhibit astonishing versatility in their forms, adopting diverse shapes that are challenging to observe through experimental means. Exploiting this adaptability, lipid structures motivate the development of bio-inspired mechanomaterials and integrated nanobio-interfaces that could seamlessly merge with biological entities, ultimately bridging the gap between synthetic and biological systems. In this work, we demonstrate how, in numerical simulations of multivesicular bodies, a fascinating evolution unfolds from an initial semblance of order toward states of higher entropy over time. We observe dynamic rearrangements in confined vesicles that reveal unexpected limit shapes of distinct geometric patterns. We identify five structures as the basic building blocks that systematically repeat under various conditions of size and composition. Moreover, we observe more complex and less frequent shapes that emerge in confined spaces. Our results provide insights into the dynamics of multivesicular systems, offering a richer understanding of how confined lipid bodies spontaneously self-organize.

Molecular Dynamics Insights into the Aggregation Behavior of N-Terminal β-Lactoglobulin Peptides

β-lactoglobulin (BLG) forms amyloid-like aggregates at high temperatures, low pH, and low ionic strengths. At a pH below 2, BLG undergoes hydrolysis into peptides, with N-terminal peptides 1-33 and 1-52 being prone to fibrillization, forming amyloid-like fibrils. Due to their good mechanical properties, BLG amyloids demonstrate great potential for diverse applications, including biosensors, nanocomposites, and catalysts. Consequently, further studies are essential to comprehensively understand the factors governing the formation of BLG amyloid-like morphologies. In this study, all-atom molecular dynamics simulations were employed to explore the aggregation of N-terminal 1-33 and 1-52 BLG peptides under conditions of pH 2 and at 10 mM NaCl concentration. The simulations revealed that the peptides spontaneously assembled into aggregates of varying sizes. The aggregation process was enabled by the low charge of peptides and the presence of hydrophobic residues within them. As the peptides associated into aggregates, there was a concurrent increase in β-sheet structures and the establishment of hydrogen bonds, enhancing the stability of the aggregates. Notably, on average, 1-33 peptides formed larger aggregates compared to their 1-52 counterparts, while the latter exhibited a slightly higher content of β-sheets and higher cluster orderliness. The applied approach facilitated insights into the early stages of amyloid-like aggregation and molecular-level insight into the formation of β-sheets, which serve as nucleation points for further fibril growth.

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

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

Structure Comparison of Beta Amyloid Peptide Aβ 1-42 Isoforms. Molecular Dynamics Modeling

Beta amyloid peptide Aβ 1-42 (Aβ42) has a unique dual role in the human organism, as both the peptide with an important physiological function and one of the most toxic biological compounds provoking Alzheimer's disease (AD). There are several known Aβ42 isoforms that we discuss here that are highly neurotoxic and lead to the early onset of AD. Aβ42 is an intrinsically disordered protein with no experimentally solved structure under physiological conditions. The objective of this research was to establish the appropriate molecular dynamics (MD) methodology and model a uniform set of structures for the Aβ42 isoforms that form the core of this study. For that purpose, force field selection and verification including convergence testing for MD simulations was made. Replica exchange MD and conventional MD modeling of several Aβ42 and Aβ16 isoforms that have neurotoxic and amyloidogenic effects impacting the severity of Alzheimer's disease were carried out with the optimal force field and solvent parameters. A standardized ensemble of structures for the Aβ42 and Aβ16 isoforms covering 30-50% of the conformational ensembles extracted from the free energy minima was calculated from MD trajectories. The resulting data set of modeled structures includes Aβ42 wild type, isoD7, pS8, D7H, and H6R-Aβ42 and Aβ16 wild type, isoD7, pS8, D7H, and H6R-Aβ16. The representative structures are given in the Supporting Information; they are open for public access. In the study, we also evaluated the differences between the structures of Aβ42 isoforms and speculate on their possible relevance to the known functions. Utilizing several representative structures for a single disordered protein for docking, with their subsequent averaging by conformations, would markedly increase the reliability of docking results.

Peptide Power: Mechanistic Insights into the Effect of Mitochondria-Targeted Tetrapeptides on Membrane Electrostatics from Molecular Simulations

Mitochondrial dysfunction is implicated in nine of the ten leading causes of death in the US, yet there are no FDA-approved therapeutics to treat it. Synthetic mitochondria-targeted peptides (MTPs), including the lead compound SS-31, offer promise, as they have been shown to restore healthy mitochondrial function and treat a variety of common diseases. At the cellular level, research has shown that MTPs accumulate strongly at the inner mitochondrial membrane (IMM), slow energy sinks (e.g., proton leaks), and improve ATP production. Modulation of electrostatic fields around the IMM has been implicated as a key aspect in the mechanism of action (MoA) of these peptides; however, molecular and mechanistic details have remained elusive. In this study, we employed all-atom molecular dynamics simulations (MD) to investigate the interactions of four MTPs with lipid bilayers and calculate their effect on structural and electrostatic properties. In agreement with previous experimental findings, we observed the modulation of the membrane surface and dipole potentials by MTPs. The simulations reveal that the MTPs achieve a reduction in the dipole potential by acting to disorder both lipid head groups and water layers proximal to the bilayer surface. We also find that MTPs decrease the bilayer thickness and increase the membrane's capacitance. These changes suggest that MTPs may enhance how much potential energy can be stored across the IMM at a given transmembrane potential difference. The MTPs also displace cations away from the bilayer surface, modulating the surface potential and offering an alternative mechanism for how these MTPs reduce mitochondrial energy sinks like proton leaks and mitigate Ca2+ accumulation stress. In conclusion, this study highlights the therapeutic potential of MTPs and underlines how interactions of MTPs with lipid bilayers serve as a fundamental component of their MoA.

Nucleation and Growth of Amyloid Fibrils

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

The stability and dynamics of the Aβ40/Aβ42 interlaced mixed fibrils

The accumulation of fibrillar amyloid-β (Aβ) aggregates in the brain, predominantly comprising 40- and 42-residue amyloid-β (Aβ40 and Aβ42), is a major pathological hallmark of Alzheimer's disease (AD). Aβ40 and Aβ42 naturally coexist in the brain under normal physiological conditions, and their interplay is generally considered to be a critical factor in the progression of AD. In addition to forming homogeneous oligomers and fibrils, Aβ40 and Aβ42 are also reported to co-assemble into hetero-oligomers and interlaced mixed fibrils, as evidenced by solid-state nuclear magnetic resonance spectroscopy (NMR), high molecular weight mass spectrometry and cross-seeding experiments. However, the exact molecular mechanisms underlying these processes remain unclear. In this study, we have used a recently resolved structurally uniform 1:1 mixture of Aβ40/Aβ42 interlaced mixed fibril as a prototype to gain insights into the molecular-level interactions between Aβ40 and Aβ42. We employed fully atomistic molecular dynamics simulation and compared the results with a homogeneous U-shaped Aβ40 fibrillar model. Our simulations using two different force fields provide conclusive evidence that the Aβ40/Aβ42 interlaced mixed fibril is energetically more favorable than the homogeneous Aβ40 fibrillar model. Furthermore, we also show that the increase in stability observed in the mixed model stems primarily from the packing interfaces and the stacking interfaces between C-termini. Our simulation results provide valuable mechanistic insights that are not readily accessible in experiment and could have significant implications for both the pathogenesis of AD and the development of current therapeutic strategies.Communicated by Ramaswamy H. Sarma.

Effects of ion type and concentration on the structure and aggregation of the amyloid peptide A β 16 - 22 $$ {\boldsymbol{\beta}}_{16-22} $$

Among the various factors controlling the amyloid aggregation process, the influences of ions on the aggregation rate and the resulting structures are important aspects to consider, which can be studied by molecular simulations. There is a wide variety of protein force fields and ion models, raising the question of which model to use in such studies. To address this question, we perform molecular dynamics simulations of Aβ16-22 , a fragment of the Alzheimer's amyloid β peptide, using different protein force fields, AMBER99SB-disp (A99-d) and CHARMM36m (C36m), and different ion parameters. The influences of NaCl and CaCl2 at various concentrations are studied and compared with the systems without the addition of ions. Our results indicate a sensitivity of the peptide-ion interactions to the different ion models. In particular, we observe a strong binding of Ca2+ to residue E22 with C36m and also with the Åqvist ion model used together with A99-d, which slightly affects the monomeric Aβ16-22 structures and the aggregation rate, but significantly affects the oligomer structures formed in the aggregation simulations. For example, at high Ca2+ concentrations, there was a switch from an antiparallel to a parallel β-sheet. Such ionic influences are of biological relevance because local ion concentrations can change in vivo and could help explain the polymorphism of amyloid fibrils.

Complex Conformational Space of the RNA Polymerase II C-Terminal Domain upon Phosphorylation

Intrinsically disordered proteins (IDPs) have been closely studied during the past decade due to their importance in many biological processes. The disordered nature of this group of proteins makes it difficult to observe its full span of the conformational space using either experimental or computational studies. In this article, we explored the conformational space of the C-terminal domain (CTD) of RNA polymerase II (Pol II), which is also an intrinsically disordered low complexity domain, using enhanced sampling methods. We provided a detailed conformational analysis of model systems of CTD with different lengths; first with the last 44 residues of the human CTD sequence and finally the CTD model with 2-heptapeptide repeating units. We then investigated the effects of phosphorylation on CTD conformations by performing simulations at different phosphorylated states. We obtained broad conformational spaces in nonphosphorylated CTD models, and phosphorylation has complex effects on the conformations of the CTD. These complex effects depend on the length of the CTD, spacing between the multiple phosphorylation sites, ion coordination, and interactions with the nearby residues.

Exploring the Barriers in the Aggregation of a Hexadecameric Human Prion Peptide through the Markov State Model

The prefibrillar aggregation kinetics of prion peptides are still an enigma. In this perspective, we employ atomistic molecular dynamics (MD) simulations of the shortest human prion peptide (HPP) (127GYMLGS132) at various temperatures and peptide concentrations and apply the Markov state model to determine the various intermediates and lag phases. Our results reveal that the natural mechanism of prion peptide self-assembly in the aqueous phase is impeded by two significant kinetic barriers with oligomer sizes of 6-9 and 12-13 peptides, respectively. The first one is the aggregation of unstructured lower-order oligomers, and the second is fibril nucleation, which impedes the further growth of prion aggregates. Among these two activation barriers, the second one is found to be dominant irrespective of the increase in temperature and peptide concentration. These lag phases are captured in all three different force-field parameters, namely, GROMOS-54a7, AMBER-99SB-ILDN, and CHARMMS 36m, at different concentrations. The GROMOS-54a7 and AMBER-99SB-ILDN force fields showed a comparatively higher percentage of β-sheet formation in the metastable aggregate that evolved during the aggregation process. In contrast, the CHARMM-36m force field showed mostly coil or turn conformations. The addition of a novel catecholamine derivative (naphthoquinone dopamine (NQDA)) arrests the aggregation process between the lag phases by increasing the activation barrier for the Lag1 and Lag2 phases in all of the force fields, which further validates the existence of these lag phases. The preferential binding of NQDA with the peptides increases the hydration of peptides and eventually disrupts the organized morphology of prefibrillar aggregates. It reduces the dimer dissociation energy by -24.34 kJ/mol.

Exploring the Curvature-Dependence of Boron Nitride Nanoparticles on the Inhibition of hIAPP Aggregation

Nanoparticles, particularly carbon nanoparticles, have gathered significant interest in the field of anti-aggregation research. However, due to their cytotoxicity, the exploration of biocompatible nanoparticles has become a new frontier in the quest for drugs against human amyloid diseases. The application of non-cytotoxic and biocompatible boron nitride (BN) nanoparticles against amyloid aggregation has been probed to tackle this issue. BN nanoparticles displayed inhibitory activity against the aggregation of Aβ and α-syn peptides. In this work, the effect of BN nanoparticles on the dimerization of hIAPP, which is associated with the pathogenesis of type 2 diabetes, is studied. BN nanoparticles prevent the misfolding of hIAPP into β-sheet-rich aggregates. On varying the curvature, the nanoparticles display variation in the interaction preference with hIAPP. Interestingly, as the hydrophobicity of the nanoparticles increases from (5,5) BN nanotube to BN nanosheet, the interaction propensity shifts from N-terminal to the amyloid prone C-terminal of hIAPP. The hydrophobic and aromatic stacking interactions are a contributing factor toward the binding between hIAPP and BN. Due to this, the flat surface of the nanosheet shows better interaction potential toward hIAPP, compared to the nanotubes. Further, the nanoparticles can also disassemble preformed hIAPP fibrils, and the effect is more pronounced for (5,5) nanotube and the nanosheet. This study provides insight into the inhibitory mechanism of hIAPP aggregation by boron nitride nanoparticles and also an understanding of the significance of the curvature of nanoparticles in their interaction with amyloid peptides, which is valuable for the design of antiamyloid drugs.

Conformational Manifold Sampled by Two Short Linear Motif Segments Probed by Circular Dichroism, Vibrational, and Nuclear Magnetic Resonance Spectroscopy

Disordered protein segments called short linear motifs (SLiM) serve as recognition sites for a variety of biological processes and act as targeting signals, modification, and ligand binding sites. While SLiMs do not adopt one of the known regular secondary structures, the conformational distribution might still reflect the structural propensities of their amino acid residues and possible interactions between them. In the past, conformational analyses of short peptides provided compelling evidence for the notion that individual residues are less conformationally flexible than locally expected for a random coil. Here, we combined various spectroscopies (NMR, IR, vibrational, and UV circular dichroism) to determine the Ramachandran plots of two SLiM motifs, i.e., GRRDSG and GRRTSG. They are two representatives of RxxS motifs that are capable of being phosphorylated by protein kinase A, an enzyme that plays a fundamental role in a variety of biological processes. Our results reveal that the nearest and non-nearest interactions between residues cause redistributions between polyproline II and β-strand basins while concomitantly stabilizing extended relative to turn-forming and helical structures. They also cause shifts in basin positions. With increasing temperature, β-strand populations become more populated at the expense of polyproline II. While molecular dynamics simulations with Amber ff14SB and CHARMM 36m force fields indicate residue-residue interactions, they do not account for the observed structural changes.

Location and Concentration of Aromatic-Rich Segments Dictates the Percolating Inter-Molecular Network and Viscoelastic Properties of Ageing Condensates

Maturation of functional liquid-like biomolecular condensates into solid-like aggregates has been linked to the onset of several neurodegenerative disorders. Low-complexity aromatic-rich kinked segments (LARKS) contained in numerous RNA-binding proteins can promote aggregation by forming inter-protein β-sheet fibrils that accumulate over time and ultimately drive the liquid-to-solid transition of the condensates. Here, atomistic molecular dynamics simulations are combined with sequence-dependent coarse-grained models of various resolutions to investigate the role of LARKS abundance and position within the amino acid sequence in the maturation of condensates. Remarkably, proteins with tail-located LARKS display much higher viscosity over time than those in which the LARKS are placed toward the center. Yet, at very long timescales, proteins with a single LARKS-independently of its location-can still relax and form high viscous liquid condensates. However, phase-separated condensates of proteins containing two or more LARKS become kinetically trapped due to the formation of percolated β-sheet networks that display gel-like behavior. Furthermore, as a work case example, they demonstrate how shifting the location of the LARKS-containing low-complexity domain of FUS protein toward its center effectively precludes the accumulation of β-sheet fibrils in FUS-RNA condensates, maintaining functional liquid-like behavior without ageing.

Benchmarking of force fields to characterize the intrinsically disordered R2-FUS-LC region

Intrinsically Disordered Proteins (IDPs) play crucial roles in numerous diseases like Alzheimer's and ALS by forming irreversible amyloid fibrils. The effectiveness of force fields (FFs) developed for globular proteins and their modified versions for IDPs varies depending on the specific protein. This study assesses 13 FFs, including AMBER and CHARMM, by simulating the R2 region of the FUS-LC domain (R2-FUS-LC region), an IDP implicated in ALS. Due to the flexibility of the region, we show that utilizing multiple measures, which evaluate the local and global conformations, and combining them together into a final score are important for a comprehensive evaluation of force fields. The results suggest c36m2021s3p with mTIP3p water model is the most balanced FF, capable of generating various conformations compatible with known ones. In addition, the mTIP3P water model is computationally more efficient than those of top-ranked AMBER FFs with four-site water models. The evaluation also reveals that AMBER FFs tend to generate more compact conformations compared to CHARMM FFs but also more non-native contacts. The top-ranking AMBER and CHARMM FFs can reproduce intra-peptide contacts but underperform for inter-peptide contacts, indicating there is room for improvement.

A Hairpin Motif in the Amyloid-β Peptide Is Important for Formation of Disease-Related Oligomers

The amyloid-β (Aβ) peptide is associated with the development of Alzheimer's disease and is known to form highly neurotoxic prefibrillar oligomeric aggregates, which are difficult to study due to their transient, low-abundance, and heterogeneous nature. To obtain high-resolution information about oligomer structure and dynamics as well as relative populations of assembly states, we here employ a combination of native ion mobility mass spectrometry and molecular dynamics simulations. We find that the formation of Aβ oligomers is dependent on the presence of a specific β-hairpin motif in the peptide sequence. Oligomers initially grow spherically but start to form extended linear aggregates at oligomeric states larger than those of the tetramer. The population of the extended oligomers could be notably increased by introducing an intramolecular disulfide bond, which prearranges the peptide in the hairpin conformation, thereby promoting oligomeric structures but preventing conversion into mature fibrils. Conversely, truncating one of the β-strand-forming segments of Aβ decreased the hairpin propensity of the peptide and thus decreased the oligomer population, removed the formation of extended oligomers entirely, and decreased the aggregation propensity of the peptide. We thus propose that the observed extended oligomer state is related to the formation of an antiparallel sheet state, which then nucleates into the amyloid state. These studies provide increased mechanistic understanding of the earliest steps in Aβ aggregation and suggest that inhibition of Aβ folding into the hairpin conformation could be a viable strategy for reducing the amount of toxic oligomers.

Structure and interaction of therapeutic proteins in solution: a combined simulation and experimental study

The aggregation of therapeutic proteins in solution has attracted significant interest, driving efforts to understand the relationship between microscopic structural changes and protein-protein interactions determining aggregation processes in solution. Additionally, there is substantial interest in being able to predict aggregation based on protein structure as part of molecular developability assessments. Molecular Dynamics provides theoretical tools to complement experimental studies and to interrogate and identify the microscopic mechanisms determining aggregation. Here we perform all-atom MD simulations to study the structure and inter-protein interaction of the Fab and Fc fragments of the monoclonal antibody (mAb) COE3. We unravel the role of ion-protein interactions in building the ionic double layer and determining effective inter-protein interaction. Further, we demonstrate, using various state-of-the-art force fields (charmm, gromos, amber, opls/aa), that the protein solvation, ionic structure and protein-protein interaction depend significantly on the force field parameters. We perform SANS and Static Light Scattering experiments to assess the accuracy of the different forcefields. Comparison of the simulated and experimental results reveal significant differences in the forcefields' performance, particularly in their ability to predict the protein size in solution and inter-protein interactions quantified through the second virial coefficients. In addition, the performance of the forcefields is correlated with the protein hydration structure.

Transition Networks Unveil Disorder-to-Order Transformations in Aβ Caused by Glycosaminoglycans or Lipids

The aggregation of amyloid-β (Aβ) peptides, particularly of Aβ1-42, has been linked to the pathogenesis of Alzheimer's disease. In this study, we focus on the conformational change of Aβ1-42 in the presence of glycosaminoglycans (GAGs) and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) lipids using molecular dynamics simulations. We analyze the conformational changes that occur in Aβ by extracting the key structural features that are then used to generate transition networks. Using the same three features per network highlights the transitions from intrinsically disordered states ubiquitous in Aβ1-42 in solution to more compact states arising from stable β-hairpin formation when Aβ1-42 is in the vicinity of a GAG molecule, and even more compact states characterized by a α-helix or β-sheet structures when Aβ1-42 interacts with a POPC lipid cluster. We show that the molecular mechanisms underlying these transitions from disorder to order are different for the Aβ1-42/GAG and Aβ1-42/POPC systems. While in the latter the hydrophobicity provided by the lipid tails facilitates the folding of Aβ1-42, in the case of GAG there are hardly any intermolecular Aβ1-42-GAG interactions. Instead, GAG removes sodium ions from the peptide, allowing stronger electrostatic interactions within the peptide that stabilize a β-hairpin. Our results contribute to the growing knowledge of the role of GAGs and lipids in the conformational preferences of the Aβ peptide, which in turn influences its aggregation into toxic oligomers and amyloid fibrils.

Dissecting the Effect of ALS Mutation G335D on the Early Aggregation of the TDP-43 Amyloidogenic Core Peptide: Helix-to-β-Sheet Transition and Conformational Shift

The aggregation of TAR DNA-binding protein of 43 kDa (TDP-43) into fibrillary deposits is associated with amyotrophic lateral sclerosis (ALS). The 311-360 fragment of TDP-43 (TDP-43311-360), the amyloidogenic core region, can spontaneously aggregate into fibrils, and the ALS-associated mutation G335D has an enhanced effect on TDP-43311-360 fibrillization. However, the molecular mechanism underlying G335D-enhanced aggregation at atomic level remains largely unknown. By utilizing all-atom molecular dynamics (MD) and replica exchange with solute tempering 2 (REST2) simulations, we investigated influences of G335D on the dimerization (the first step of aggregation) and conformational ensemble of the TDP-43311-360 peptide. Our simulations show that G335D mutation increases inter-peptide interactions, especially inter-peptide hydrogen-bonding interactions in which the mutant site has a relatively large contribution, and enhances the dimerization of TDP-43311-360 peptides. The α-helix regions in the NMR-resolved conformation of the TDP-43311-360 monomer (321-330 and 335-343) play an essential role in the formation of the dimer. G335D mutation induces helix unfolding and promotes α-to-β conversion. G335D mutation alters the conformational distribution of TDP-43311-360 dimers and causes population shift from helix-rich to β-sheet-rich conformations, which facilitates the fibrillization of the TDP-43311-360 peptide. Our MD and REST2 simulation results suggest that the 321-330 region is of paramount importance to α-to-β transition and could be the initiation site for TDP-43311-360 fibrillization. Our work reveals the mechanism underlying the enhanced aggregation propensity of the G335D TDP-43311-360 peptide, which provides atomistic insights into the G335D mutation-caused pathogenicity of TDP-43 protein.

Preventing the amyloid-beta peptides accumulation on the cell membrane by applying GHz electric fields: A molecular dynamic simulation

Alzheimer's disease is associated with accumulating different amyloid peptides on the nerve cell membranes. The non-thermal effects of the GHz electric fields in this topic have yet to be well recognized. Hence, in this study, the impacts of 1 and 5 GHz electric fields on the amyloid peptide proteins accumulation on the cell membrane have been investigated, utilizing molecular dynamics (MD) simulation. The obtained results indicated that this range of electric fields did not significantly affect the peptide structure. Moreover, it was found that the peptide penetration into the membrane was increased as the field frequency was increased when the system was exposed to a 20 mv/nm oscillating electric field. In addition, it was observed that the protein-membrane interaction is reduced significantly in the presence of the 70 mv/nm electric field. The molecular level results reported in this study could be helpful in better understanding Alzheimer's disease.

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

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

Human Amylin in the Presence of SARS-COV-2 Protein Fragments

COVID-19 can lead to the onset of type-II diabetes, which is associated with the aggregation of islet amyloid polypeptides, also called amylin. Using molecular dynamics simulations, we investigate how the equilibrium between amylin monomers in its functional form and fibrils associated with diabetes is altered in the presence of SARS-COV-2 protein fragments. For this purpose, we study the interaction between the fragment SFYVYSRVK of the envelope protein or the fragment FKNIDGYFKI of the spike protein with the monomer and two amylin fibril models. Our results are compared with earlier work studying such interactions for the two different proteins.

Understanding the screening effect of aqueous DES on the IDPs: A molecular dynamics simulation study using amyloid β42 monomer

Deep eutectic solvents (DESs) have emerged as the promising replacement to the ionic liquids in solvent engineering for bio-compatibility. We aim to understand the effect of aqueous deep eutectic solvents on the conformation of intrinsically disordered proteins (IDPs). In this context, we have studied the effect on amyloid beta (Aβ₄₂) monomer in the hydrated DES composed of tetrabutylammonium chloride and ethylene glycol in a 3:1 ratio using all-atom molecular dynamics simulations. DES is found to effectively screen the interaction of four zones of the amyloid beta monomer with water. Water molecules and the DES constituents modulate the local protein-solvent interactions, in the solvation shell of the protein. In addition, the aqueous DES medium conserves the secondary structure of the Aβ₄₂ monomer by increasing the intramolecular hydrogen bonding and D23-K28 salt-bridge interactions when compared to the pure water medium. The current study provides insights into the impact of DES in stabilizing an IDP, at molecular level. We envisage the hindered aggregation of the amyloid beta structures in DES medium over the pure water medium due to the screening of hydrophobic intramolecular interactions.

Structural Insights into ATP-Sensitive Potassium Channel Mechanics: A Role of Intrinsically Disordered Regions

Commonly used techniques, such as CryoEM or X-ray, are not able to capture the structural reorganizations of disordered regions of proteins (IDR); therefore, it is difficult to assess their functions in proteins based exclusively on experiments. To fill this gap, we used computational molecular dynamics (MD) simulation methods to capture IDR dynamics and trace biological function-related interactions in the Kir6.2/SUR1 potassium channel. This ATP-sensitive octameric complex, one of the critical elements in the insulin secretion process in human pancreatic β-cells, has four to five large, disordered fragments. Using unique MD simulations of the full Kir6.2/SUR1 channel complex, we present an in-depth analysis of the dynamics of the disordered regions and discuss the possible functions they could have in this system. Our MD results confirmed the crucial role of the N-terminus of the Kir6.2 fragment and the L0-loop of the SUR1 protein in the transfer of mechanical signals between domains that trigger insulin release. Moreover, we show that the presence of IDRs affects natural ligand binding. Our research takes us one step further toward understanding the action of this vital complex.

Human Amylin in the Presence of SARS-COV-2 Protein Fragments

Covid-19 can lead to the onset of type-II diabetes which is associated with aggregation of islet amyloid polypeptides, also called amylin. Using molecular dynamics simulations, we investigate how the equilibrium, between amylin monomers in its functional form and fibrils associated with diabetes, is altered in presence of SARS-COV-2 protein fragments. For this purpose, we study the interaction between the fragment SFYVYSRVK of the Envelope protein or the fragment FKNIDGYFKI of the Spike protein with the monomer and two amylin fibril models. Our results are compared with earlier work studying such interactions for two different proteins.

Comparative molecular dynamics simulations of pathogenic and non-pathogenic huntingtin protein monomers and dimers

Polyglutamine expansion at the N-terminus of the huntingtin protein exon 1 (Htt-ex1) is closely associated with a number of neurodegenerative diseases, which result from the aggregation of the increased polyQ repeat. However, the underlying structures and aggregation mechanism are still poorly understood. We performed microsecond-long all-atom molecular dynamics simulations to study the folding and dimerization of Htt-ex1 (about 100 residues) with non-pathogenic and pathogenic polyQ lengths, and uncovered substantial differences. The non-pathogenic monomer adopts a long α-helix that includes most of the polyQ residues, which forms the interaction interface for dimerization, and a PPII-turn-PPII motif in the proline-rich region. In the pathogenic monomer, the polyQ region is disordered, leading to compact structures with many intra-protein interactions and the formation of short β-sheets. Dimerization can proceed via different modes, where those involving the N-terminal headpiece bury more hydrophobic residues and are thus more stable. Moreover, in the pathogenic Htt-ex1 dimers the proline-rich region interacts with the polyQ region, which slows the formation of β-sheets.

Disparate Effect of Hybrid Peptidomimetics Containing Isomers of Aminobenzoic Acid on hIAPP Aggregation

The abnormal misfolding of human islet amyloid polypeptide (hIAPP) in pancreatic β-cells is implicated in the progression of type II diabetes (T2D). With the prevalence of T2D increasing worldwide, preventing the aggregation of hIAPP has been recognized as a promising therapeutic strategy to control this disease. Recently, a class of novel conformationally restricted β-sheet breaker hybrid peptidomimetics (BSBHps) was found to demonstrate efficient inhibitory ability toward amyloid formation of hIAPP. One (Ile26) or more (Gly24 and Ile26) residues in these six-membered peptide sequences, which have been extracted from the amyloidogenic core of hIAPP, N₂₂FGAIL₂₇, are substituted by three different isomers of the conformationally restricted aromatic amino acid, i.e., aminobenzoic acid (β, γ, and δ), to generate these BSBHps. The presence of the nonproteinogenic aminobenzoic acid moiety renders the BSBHps to be more stable toward proteolytic degradation. The different isomeric BSBHps exhibit contrasting influence on the self-assembly of hIAPP. The BSBHps containing β- and γ-aminobenzoic acid can sufficiently prevent hIAPP aggregation, but those with the δ-aminobenzoic group stabilize the β-sheet-rich aggregate of hIAPP. The difference in the angle between the amino and carboxyl groups in the isomers of the aminobenzoic moiety causes the BSBHps to attain discrete conformation and hence leads to variation in their binding preference with hIAPP and ultimately their inhibitory potency. This guides the pathway for the dissimilar effect of BSBHps on peptide aggregation and, therefore, provides insights into the design considerations for novel drugs against T2D.

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.

Characterizing Transient Protein-Protein Interactions by Trp-Cys Quenching and Computer Simulations

Transient protein-protein interactions occur frequently under the crowded conditions encountered in biological environments. Tryptophan-cysteine quenching is introduced as an experimental approach with minimal labeling for characterizing such interactions between proteins due to its sensitivity to nano- to microsecond dynamics on subnanometer length scales. The experiments are paired with computational modeling at different resolutions including fully atomistic molecular dynamics simulations for interpretation of the experimental observables and to gain molecular-level insights. This approach is applied to model systems, villin variants and the drkN SH3 domain, in the presence of protein G crowders. It is demonstrated that Trp-Cys quenching experiments can differentiate between overall attractive and repulsive interactions between different proteins, and they can discern variations in interaction preferences at different protein surface locations. The close integration between experiment and simulations also provides an opportunity to evaluate different molecular force fields for the simulation of concentrated protein solutions.

Protein structural transitions critically transform the network connectivity and viscoelasticity of RNA-binding protein condensates but RNA can prevent it

Biomolecular condensates, some of which are liquid-like during health, can age over time becoming gel-like pathological systems. One potential source of loss of liquid-like properties during ageing of RNA-binding protein condensates is the progressive formation of inter-protein β-sheets. To bridge microscopic understanding between accumulation of inter-protein β-sheets over time and the modulation of FUS and hnRNPA1 condensate viscoelasticity, we develop a multiscale simulation approach. Our method integrates atomistic simulations with sequence-dependent coarse-grained modelling of condensates that exhibit accumulation of inter-protein β-sheets over time. We reveal that inter-protein β-sheets notably increase condensate viscosity but does not transform the phase diagrams. Strikingly, the network of molecular connections within condensates is drastically altered, culminating in gelation when the network of strong β-sheets fully percolates. However, high concentrations of RNA decelerate the emergence of inter-protein β-sheets. Our study uncovers molecular and kinetic factors explaining how the accumulation of inter-protein β-sheets can trigger liquid-to-solid transitions in condensates, and suggests a potential mechanism to slow such transitions down.

In this work the authors propose a multiscale computational approach, integrating atomistic and coarse-grained models simulations, to study the thermodynamic and kinetic factors playing a major role in the liquid-to-solid transition of biomolecular condensates. It is revealed how the gradual accumulation of inter-protein β-sheets increases the viscosity of functional liquid-like condensates, transforming them into gel-like pathological aggregates, and it is also shown how high concentrations of RNA can decelerate such transition.

Atomistic Insights into A315E Mutation-Enhanced Pathogenicity of TDP-43 Core Fibrils

The aggregation of TAR DNA-binding protein of 43 kDa (TDP-43) into fibrillary deposits is implicated in amyotrophic lateral sclerosis (ALS), and some hereditary mutations localized in the low complexity domain (LCD) facilitate the formation of pathogenic TDP-43 fibrils. A recent cryo-EM study reported the atomic-level structures of the A315E TDP-43 LCD (residues 288-319, TDP-43_288-319) core fibril in which the protofilaments have R-shaped structures and hypothesized that A315E U-shaped protofilaments can readily convert to R-shaped protofilaments compared to the wild-type (WT) ones. There are no atomic structures of WT protofilaments available yet. Herein, we performed extensive all-atom explicit-solvent molecular dynamics simulations on A315E and WT protofilaments starting from both the cryo-EM-determined R-shaped and our constructed U-shaped structures. Our simulations show that WT protofilaments also adopt the R-shaped structures but are less stable than their A315E counterparts. Except for R293-E315 salt bridges, N312-F316 hydrophobic interactions and F316-F316 π-π stacking interactions are also crucial for the stabilization of the neck region of the R-shaped A315E protofilaments. The loss of R293-E315 salt bridges and the weakened interactions of N312-F316 and F316-F316 result in the reduced stability of the R-shaped WT protofilaments. Simulations starting from U-shaped folds reveal that A315E protofilaments can spontaneously convert to the cryo-EM-derived R-shaped protofilaments, whereas WT protofilaments convert to R-shape-like structures with remodeled neck regions. The R-shape-like WT protofilaments could act as intermediate states slowing down the U-to-R transition. This study reveals that A315E mutation can not only enhance the structural stability of the R-shaped TDP-43_288-319 protofilaments but also promote the U-to-R transition, which provides atomistic insights into the A315E mutation-enhanced TDP-43 pathogenicity in ALS.

Conformation-Dependent Influences of Hydrophobic Amino Acids in Two In-Register Parallel β-Sheet Amyloids, an α-Synuclein Amyloid and a Local Structural Model of PrPSc

Prions are unconventional pathogens that encode the pathogenic information in conformations of the constituent abnormal isoform of prion protein (PrP^Sc), independently of the nucleotide genome. Therefore, conformational diversity of PrP^Sc underlies the existence of many prion strains and species barriers of prions, although the conformational information is extremely limited. Interestingly, differences between polymorphic or species-specific residues responsible for the species/strain barriers are often caused by conservative replacements between hydrophobic amino acids. This implies that subtle differences among hydrophobic amino acids are significant for PrP^Sc structures. Here we analyzed the influence of different hydrophobic residues on the structures of an in-register parallel β-sheet amyloid of α-synuclein (αSyn) using molecular dynamics (MD) simulation and applied the knowledge from the αSyn amyloid to modeling a local structure of human PrP^Sc encompassing residues 107-143. We found that mutations equivalent to polymorphisms that cause transmission barriers substantially affect the stabilities of the local structures; for example, the G127V mutation, which makes the host resistant to various human prion diseases, greatly destabilized the local structure of the model amyloid. Our study indicates that subtle differences among hydrophobic side chains can considerably affect the interaction network, including hydrogen bonds, and demonstrates specifically how and in what structures hydrophobic residues can exert unique effects on in-register parallel β-sheet amyloids.

A New Transfer Free Energy Based Implicit Solvation Model for the Description of Disordered and Folded Proteins

Most biological events occur on time scales that are difficult to access using conventional all-atom molecular dynamics simulations in explicit solvent. Implicit solvent techniques offer a promising solution to this problem, alleviating the computational cost associated with the simulation of large systems and accelerating the sampling compared to explicit solvent models. The substitution of water molecules by a mean field, however, introduces simplifications that may penalize accuracy and impede the prediction of certain physical properties. We demonstrate that existing implicit solvent models developed using a transfer free energy approach, while satisfactory at reproducing the folding behavior of globular proteins, fare less well in characterizing the conformational properties of intrinsically disordered proteins. We develop a new implicit solvent model that maximizes the degree of accuracy for both disordered and folded proteins. We show, by comparing the simulation outputs to experimental data, that in combination with the a99SB-disp force field, the implicit solvent model can describe both disordered (aβ40, PaaA2, and drkN SH3) and folded ((AAQAA)₃, CLN025, Trp-cage, and GTT) peptides. Our implicit solvent model permits a computationally efficient investigation of proteins containing both ordered and disordered regions, as well as the study of the transition between ordered and disordered protein states.

Transferable and Polarizable Coarse Grained Model for Proteins─ProMPT

The application of classical molecular dynamics (MD) simulations at atomic resolution (fine-grained level, FG), to most biomolecular processes, remains limited because of the associated computational complexity of representing all the atoms. This problem is magnified in the presence of protein-based biomolecular systems that have a very large conformational space, and MD simulations with fine-grained resolution have slow dynamics to explore this space. Current transferable coarse grained (CG) force fields in literature are either limited to only peptides with the environment encoded in an implicit form or cannot capture transitions into secondary/tertiary peptide structures from a primary sequence of amino acids. In this work, we present a transferable CG force field with an explicit representation of the environment for accurate simulations with proteins. The force field consists of a set of pseudoatoms representing different chemical groups that can be joined/associated together to create different biomolecular systems. This preserves the transferability of the force field to multiple environments and simulation conditions. We have added electronic polarization that can respond to environmental heterogeneity/fluctuations and couple it to protein's structural transitions. The nonbonded interactions are parametrized with physics-based features such as solvation and partitioning free energies determined by thermodynamic calculations and matched with experiments and/or atomistic simulations. The bonded potentials are inferred from corresponding distributions in nonredundant protein structure databases. We present validations of the CG model with simulations of well-studied aqueous protein systems with specific protein fold types─Trp-cage, Trpzip4, villin, WW-domain, and β-α-β. We also explore the applications of the force field to study aqueous aggregation of Aβ 16-22 peptides.

Aging can transform single-component protein condensates into multiphase architectures

Phase-separated biomolecular condensates that contain multiple coexisting phases are widespread in vitro and in cells. Multiphase condensates emerge readily within multicomponent mixtures of biomolecules (e.g., proteins and nucleic acids) when the different components present sufficient physicochemical diversity (e.g., in intermolecular forces, structure, and chemical composition) to sustain separate coexisting phases. Because such diversity is highly coupled to the solution conditions (e.g., temperature, pH, salt, composition), it can manifest itself immediately from the nucleation and growth stages of condensate formation, develop spontaneously due to external stimuli or emerge progressively as the condensates age. Here, we investigate thermodynamic factors that can explain the progressive intrinsic transformation of single-component condensates into multiphase architectures during the nonequilibrium process of aging. We develop a multiscale model that integrates atomistic simulations of proteins, sequence-dependent coarse-grained simulations of condensates, and a minimal model of dynamically aging condensates with nonconservative intermolecular forces. Our nonequilibrium simulations of condensate aging predict that single-component condensates that are initially homogeneous and liquid like can transform into gel-core/liquid-shell or liquid-core/gel-shell multiphase condensates as they age due to gradual and irreversible enhancement of interprotein interactions. The type of multiphase architecture is determined by the aging mechanism, the molecular organization of the gel and liquid phases, and the chemical makeup of the protein. Notably, we predict that interprotein disorder to order transitions within the prion-like domains of intracellular proteins can lead to the required nonconservative enhancement of intermolecular interactions. Our study, therefore, predicts a potential mechanism by which the nonequilibrium process of aging results in single-component multiphase condensates.

Multi-eGO: An in silico lens to look into protein aggregation kinetics at atomic resolution

Protein aggregation into amyloid fibrils is the archetype of aberrant biomolecular self-assembly processes, with more than 50 associated diseases that are mostly uncurable. Understanding aggregation mechanisms is thus of fundamental importance and goes in parallel with the structural characterization of the transient oligomers formed during the process. Oligomers have been proven elusive to high-resolution structural techniques, while the large sizes and long time scales, typical of aggregation processes, have limited the use of computational methods to date. To surmount these limitations, we here present multi-eGO, an atomistic, hybrid structure-based model which, leveraging the knowledge of monomers conformational dynamics and of fibril structures, efficiently captures the essential structural and kinetics aspects of protein aggregation. Multi-eGO molecular dynamics simulations can describe the aggregation kinetics of thousands of monomers. The concentration dependence of the simulated kinetics, as well as the structural features of the resulting fibrils, are in qualitative agreement with in vitro experiments carried out on an amyloidogenic peptide from Transthyretin, a protein responsible for one of the most common cardiac amyloidoses. Multi-eGO simulations allow the formation of primary nuclei in a sea of transient lower-order oligomers to be observed over time and at atomic resolution, following their growth and the subsequent secondary nucleation events, until the maturation of multiple fibrils is achieved. Multi-eGO, combined with the many experimental techniques deployed to study protein aggregation, can provide the structural basis needed to advance the design of molecules targeting amyloidogenic diseases.

Deciphering the Role of ATP on PHF6 Aggregation

The aggregation of Tau protein, which are involved in Alzheimer's disease, are associated with the self-assembly of the hexapeptide sequence, paired helical filament 6 (PHF6) from repeat 3 of Tau. In order to treat Alzheimer's disease and other such tauopathies, one of the therapeutic strategies is to inhibit aggregation of Tau and its nucleating segments. Therefore, we have studied the effect of adenosine triphosphate (ATP) on the aggregation of PHF6. ATP has, interestingly, demonstrated its ability to inhibit and dissolve protein aggregates. Using classical molecular dynamics simulations, we observed that the hydrophobic core of PHF6 segment displays extended β-sheet conformation, which stabilizes PHF6 aggregates. However, the distribution of ATP around the vicinity of the peptides enables PHF6 to remain discrete and attain random coil conformers. The interpeptide interactions are substituted by PHF6-ATP interactions through hydrogen bonding and hydrophobic interactions (including π-π stacking). Furthermore, the adenosine moiety of ATP contributes more than the triphosphate chain toward PHF6-ATP interaction. Ultimately, this work establishes the inhibitory activity of ATP against Tau aggregation; hence, the therapeutic effect of ATP should be explored further in regard to the effective treatment of Alzheimer's disease.

Insights into the Atomistic Mechanisms of Phosphorylation in Disrupting Liquid-Liquid Phase Separation and Aggregation of the FUS Low-Complexity Domain

Fused in sarcoma (FUS), a nuclear RNA binding protein, can not only undergo liquid-liquid phase separation (LLPS) to form dynamic biomolecular condensates but also aggregate into solid amyloid fibrils which are associated with the pathology of amyotrophic lateral sclerosis and frontotemporal lobar degeneration diseases. Phosphorylation in the FUS low-complexity domain (FUS-LC) inhibits FUS LLPS and aggregation. However, it remains largely elusive what are the underlying atomistic mechanisms of this inhibitory effect and whether phosphorylation can disrupt preformed FUS fibrils, reversing the FUS gel/solid phase toward the liquid phase. Herein, we systematically investigate the impacts of phosphorylation on the conformational ensemble of the FUS_37-97 monomer and dimer and the structure of the FUS_37-97 fibril by performing extensive all-atom molecular dynamics simulations. Our simulations reveal three key findings: (1) phosphorylation shifts the conformations of FUS_37-97 from the β-rich, fibril-competent state toward a helix-rich, fibril-incompetent state; (2) phosphorylation significantly weakens protein-protein interactions and enhances protein-water interactions, which disfavor FUS-LC LLPS as well as aggregation and facilitate the dissolution of the preformed FUS-LC fibril; and (3) the FUS_37-97 peptide displays a high β-strand probability in the region spanning residues 52-67, and phosphorylation at S54 and S61 residues located in this region is crucial for the disruption of LLPS and aggregation of FUS-LC. This study may pave the way for ameliorating phase-separation-related pathologies via site-specific phosphorylation.

Multiscale Exploration of Concentration-Dependent Amyloid-β(16-21) Amyloid Nucleation

Atomic descriptions of peptide aggregation nucleation remain lacking due to the difficulty of exploring complex configurational spaces on long time scales. To elucidate this process, we develop a multiscale approach combining a metadynamics-based method with cluster statistical mechanics to derive concentration-dependent free energy surfaces of nucleation at near-atomic resolution. A kinetic transition network of nucleation is then constructed and employed to systematically explore nucleation pathways and kinetics through stochastic simulations. This approach is applied to describe Aβ_16-21 amyloid nucleation, revealing a two-step mechanism involving disordered aggregates at millimolar concentration, and an unexpected mechanism at submillimolar concentrations that exhibits kinetics reminiscent of classical nucleation but atypical pathways involving growing clusters with structured cores wrapped by disordered surface. When this atypical mechanism is operative, critical nucleus size can be reflected by the nucleation reaction order. Collectively, our approach paves the way for a more quantitative and detailed understanding of peptide aggregation nucleation.

Molecular Dynamics Simulations Indicate Aromaticity as a Key Factor in the Inhibition of IAPP(20-29) Aggregation

Islet amyloid polypeptide (IAPP) is a 37-residue amyloidogenic hormone implicated in the progression of Type II Diabetes (T2D). T2D affects an estimated 422 million people yearly and is a comorbidity with numerous diseases. IAPP forms toxic oligomers and amyloid fibrils that reduce pancreatic β-cell mass and exacerbate the T2D disease state. Toxic oligomer formation is attributed, in part, to the formation of interpeptide β-strands comprised of residues 20-29 (IAPP_(20-29)). Flavonoids, a class of polyphenolic natural products, have been found experimentally to inhibit IAPP aggregate formation. Many of these small flavonoids differ structurally only slightly; the influence of functional group placement on inhibiting the aggregation of the IAPP_(20-29) has yet to be explored. To probe the role of small-molecule structural features that impede IAPP aggregation, molecular dynamics simulations were performed to observe trimer formation on a model fragment of IAPP_(20-29) in the presence of morin, quercetin, dihydroquercetin, epicatechin, and myricetin. Contacts between Phe23 residues were critical to oligomer formation, and small-molecule contacts with Phe23 were a key predictor of β-strand reduction. Structural properties influencing the ability of compounds to disrupt Phe23-Phe23 contacts included aromaticity and carbonyl and hydroxyl group placement. This work provides key information on design considerations for T2D therapeutics that target IAPP aggregation.

Development of a Hybrid-Resolution Force Field for Peptide Self-Assembly Simulations: Optimizing Peptide-Peptide and Peptide-Solvent Interactions

Atomic descriptions of peptide self-assembly are crucial to an understanding of disease-related peptide aggregation and the design of peptide-assembled materials. Obtaining these descriptions through computer simulation is challenging because current force fields, which were not designed for this process and are often unable to describe correctly peptide self-assembly behavior and the sequence dependence. Here, we developed a framework using dipeptide aggregation as a model system to improve force fields for simulations of self-assembly. Aggregation-related structural properties were designed and used to guide the optimization of peptide-peptide and peptide-solvent interactions. With this framework, we developed a self-assembly force field, termed PACE-ASM, by reoptimizing a hybrid-resolution force field that was originally developed for folding simulation. With its applicability in folding simulations, the new PACE was used to simulate the self-assembly of two disease-related short peptides, Aβ_16-21 and PHF6, into β-sheet-rich cross-β amyloids. These simulations reproduced the crystal structures of Aβ_16-21 and PHF6 amyloids at near-atomic resolution and captured the difference in packing orientations between the two sequences, a task which is challenging even with all-atom force fields. Apart from cross-β amyloids, the self-assembly of emerging helix-rich cross-α amyloids by another peptide PSMα3 can also be correctly described with the new PACE, manifesting the versatility of the force field. We demonstrated that the ability of the PACE-ASM to model peptide self-assembly is based largely on its improved description of peptide-peptide and peptide-solvent interactions. This was achieved with our optimization framework that can readily identify and address the deficiency in describing these interactions.

Influencing factors and characterization methods of nanoparticles regulating amyloid aggregation

Human disorders associated with amyloid aggregation, such as Alzheimer's disease and Parkinson's disease, afflict the lives of millions worldwide. When peptides and proteins in the body are converted to amyloids, which have a tendency to aggregate, the toxic oligomers produced during the aggregation process can trigger a range of diseases. Nanoparticles (NPs) have been found to possess surface effects that can modulate the amyloid aggregation process and they have potential application value in the treatment of diseases related to amyloid aggregation and fibrillary tangles. In this review, we discuss recent progress relating to studies of nanoparticles that regulate amyloid aggregation. The review focuses on the factors influencing this regulation, which are important as guidelines for the future design of NPs for the treatment of amyloid aggregation. We describe the characterization methods that have been utilized so far in such studies. This review provides research information and characterization methods for the rational design of NPs, which should result in therapeutic strategies for amyloid diseases.

AlphaFold2: A Role for Disordered Protein/Region Prediction?

The development of AlphaFold2 marked a paradigm-shift in the structural biology community. Herein, we assess the ability of AlphaFold2 to predict disordered regions against traditional sequence-based disorder predictors. We find that AlphaFold2 performs well at discriminating disordered regions, but also note that the disorder predictor one constructs from an AlphaFold2 structure determines accuracy. In particular, a naïve, but non-trivial assumption that residues assigned to helices, strands, and H-bond stabilized turns are likely ordered and all other residues are disordered results in a dramatic overestimation in disorder; conversely, the predicted local distance difference test (pLDDT) provides an excellent measure of residue-wise disorder. Furthermore, by employing molecular dynamics (MD) simulations, we note an interesting relationship between the pLDDT and secondary structure, that may explain our observations and suggests a broader application of the pLDDT for characterizing the local dynamics of intrinsically disordered proteins and regions (IDPs/IDRs).

Modeling the Structure and Interactions of Intrinsically Disordered Peptides with Multiple Replica, Metadynamics-Based Sampling Methods and Force-Field Combinations

Intrinsically disordered proteins play a key role in many biological processes, including the formation of biomolecular condensates within cells. A detailed characterization of their configurational ensemble and structure-function paradigm is crucial for understanding their biological activity and for exploiting them as building blocks in material sciences. In this work, we incorporate bias-exchange metadynamics and parallel-tempering well-tempered metadynamics with CHARMM36m and CHARMM22* to explore the structural and thermodynamic characteristics of a short archetypal disordered sequence derived from a DEAD-box protein. The conformational landscapes emerging from our simulations are largely congruent across methods and force fields. Nevertheless, differences in fine details emerge from varying combinations of force-fields and sampling methods. For this protein, our analysis identifies features that help to explain the low propensity of this sequence to undergo self-association in vitro, which are common to all force-field/sampling method combinations. Overall, our work demonstrates the importance of using multiple force-field and sampling method combinations for accurate structural and thermodynamic information in the study of disordered proteins.

Molecular simulations of proteins: From simplified physical interactions to complex biological phenomena

Molecular dynamics simulation is the most popular computational technique for investigating the structural and dynamical behaviour of proteins, in search of the molecular basis of their function. Far from being a completely settled field of research, simulations are still evolving to best capture the essential features of the atomic interactions that govern a protein's inner motions. Modern force fields are becoming increasingly accurate in providing a physical description adequate to this purpose, and allow us to model complex biological systems under fairly realistic conditions. Furthermore, the use of accelerated sampling techniques is improving our access to the observation of progressively larger molecular structures, longer time scales, and more hidden functional events. In this review, the basic principles of molecular dynamics simulations and a number of key applications in the area of protein science are summarized, and some of the most important results are discussed. Examples include the study of the structure, dynamics and binding properties of 'difficult' targets, such as intrinsically disordered proteins and membrane receptors, and the investigation of challenging phenomena like hydration-driven processes and protein aggregation. The findings described provide an overall picture of the current state of this research field, and indicate new perspectives on the road ahead to the upcoming future of molecular 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.