Search

In order to improve the accuracy of molecular dynamics simulations, classical force fields are supplemented with a kernel-based machine learning method trained on quantum-mechanical fragment energies. As an example application, a potential-energy surface is generalised for a small DNA duplex, taking into account explicit solvation and long-range electron exchange--correlation effects. Study of the corrected potential energy versus extension shows that leading classical DNA models have excessive stiffness with respect to stretching. This discrepancy is found to be common across multiple forcefields. The quantum correction is in qualitative agreement to the experimental thermodynamics for larger DNA double helices, providing a candidate explanation for the general and long-standing discrepancy between single molecule stretching experiments and classical calculations of DNA stretching. The new dataset of quantum calculations and the associated Kernel Modified Molecular Dynamics (KMMD) method should be of general utility in biomolecular simulations. KMMD is made available as part of the AMBER22 simulation software., Comment: Publisher postprint (with minor corrections) is open access at J Chem Phys https://doi.org/10.1063/5.0094727

COVID-19 is primarily known as a respiratory disease caused by the virus SARS-CoV-2. However, neurological symptoms such as memory loss, sensory confusion, cognitive and psychiatric issues, severe headaches, and even stroke are reported in as many as 30% of cases and can persist even after the infection is over (so-called ‘long COVID’). These neurological symptoms are thought to be caused by brain inflammation, triggered by the virus infecting the central nervous system of COVID-19 patients, however we still don’t fully understand the mechanisms for these symptoms. The neurological effects of COVID-19 share many similarities to neurodegenerative diseases such as Alzheimer’s and Parkinson’s in which the presence of cytotoxic protein-based amyloid aggregates is a common etiological feature. Following the hypothesis that some neurological symptoms of COVID-19 may also follow an amyloid etiology we performed a bioinformatic scan of the SARS-CoV-2 proteome, detecting peptide fragments that were predicted to be highly amyloidogenic. We selected two of these peptides and discovered that they do rapidly self-assemble into amyloid. Furthermore, these amyloid assemblies were shown to be highly toxic to a neuronal cell line. We introduce and support the idea that cytotoxic amyloid aggregates of SARS-CoV-2 proteins are causing some of the neurological symptoms commonly found in COVID-19 and contributing to long COVID, especially those symptoms which are novel to long COVID in contrast to other post-viral syndromes.

Nanomechanical properties of amyloid fibrils and nanocrystals depend on their secondary and quaternary structure, and the geometry of intermolecular hydrogen bonds. Advanced imaging methods based on atomic force microscopy (AFM) have unravelled the morphological and mechanical heterogeneity of amyloids, however a full understanding has been hampered by the limited resolution of conventional spectroscopic methods. Here, it is shown that single molecule nanomechanical mapping and infrared nanospectroscopy (AFM‐IR) in combination with atomistic modelling enable unravelling at the single aggregate scale of the morphological, nanomechanical, chemical, and structural transition from amyloid fibrils to amyloid microcrystals in the hexapeptides, ILQINS, IFQINS, and TFQINS. Different morphologies have different Young's moduli, within 2–6 GPa, with amyloid fibrils exhibiting lower Young's moduli compared to amyloid microcrystals. The origins of this stiffening are unravelled and related to the increased content of intermolecular β‐sheet and the increased lengthscale of cooperativity following the transition from twisted fibril to flat nanocrystal. Increased stiffness in Young's moduli is correlated with increased density of intermolecular hydrogen bonding and parallel β‐sheet structure, which energetically stabilize crystals over the other polymorphs. These results offer additional evidence for the position of amyloid crystals in the minimum of the protein folding and aggregation landscape., Atomic force microscopy, infrared nanospectroscopy, and atomistic modelling combined together allow elucidating the molecular origins of the exceptional thermodynamic stability of amyloid crystals, revealing the crucial role of the high density and order of intermolecular β‐sheet associated with their purely translational symmetry and lack of mesoscopic twist of amyloid microcrystals.

Several atomic structures have now been found for micrometer-scale amyloid fibrils or elongated microcrystals using a range of methods, including NMR, electron microscopy, and X-ray crystallography, with parallel β-sheet appearing as the most common secondary structure. The etiology of amyloid disease, however, indicates nanometer-scale assemblies of only tens of peptides as significant agents of cytotoxicity and contagion. By combining solution X-ray with molecular dynamics, we show that antiparallel structure dominates at the first stages of aggregation for a specific set of peptides, being replaced by parallel at large length scales only. This divergence in structure between small and large amyloid aggregates should inform future design of molecular therapeutics against nucleation or intercellular transmission of amyloid. Calculations and an overview from the literature argue that antiparallel order should be the first appearance of structure in many or most amyloid aggregation processes, regardless of the endpoint. Exceptions to this finding should exist, depending inevitably on the sequence and on solution conditions., Biophysical Journal, 118 (10), ISSN:0006-3495, ISSN:1542-0086

Amyloidogenic model peptides are invaluable for investigating assembly mechanisms in disease related amyloids and in protein folding. During aggregation, such peptides can undergo bifurcation leading to fibrils or crystals, however the mechanisms of fibril-to-crystal conversion are unclear. We navigate herein the energy landscape of amyloidogenic peptides by studying a homologous series of hexapeptides found in animal, human and disease related proteins. We observe fibril-to-crystal conversion occurring within single aggregates via untwisting of twisted ribbon fibrils possessing saddle-like curvature and cross-sectional aspect ratios approaching unity. Changing sequence, pH or concentration shifts the growth towards larger aspect ratio species assembling into stable helical ribbons possessing mean-curvature. By comparing atomistic calculations of desolvation energies for association of peptides we parameterise a kinetic model, providing a physical explanation of fibril-to-crystal interconversion. These results shed light on the self-assembly of amyloidogenic peptides, suggesting amyloid crystals, not fibrils, represent the ground state of the protein folding energy landscape., Nature Communications, 8 (1), ISSN:2041-1723

By combining atomistic and higher-level modelling with solution X-ray diffraction we analyse self-assembly pathways for the IFQINS hexapeptide, a bio-relevant amyloid former derived from human lysozyme. We verify that (at least) two metastable polymorphic structures exist for this system which are substantially different at the atomistic scale, and compare the conditions under which they are kinetically accessible. We further examine the higher-level polymorphism for these systems at the nanometre to micrometre scales, which is manifested in kinetic differences and in shape differences between structures instead of or as well as differences in the small-scale contact topology. Any future design of structure based inhibitors of the IFQINS steric zipper, or of close homologues such as TFQINS which are likely to have similar structures, should take account of this polymorphic assembly., Scientific Reports, 9 (1), ISSN:2045-2322

Mixed solvents (i.e., binary or higher order mixtures of ionic or nonionic liquids) play crucial roles in chemical syntheses, separations, and electrochemical devices because they can be tuned for specific reactions and applications. Apart from fully explicit solvation treatments that can be difficult to parameterize or computationally expensive, there is currently no well-established first-principles regimen for reliably modeling atomic-scale chemistry in mixed solvent environments. We offer our perspective on how this process could be achieved in the near future as mixed solvent systems become more explored using theoretical and computational chemistry. We first outline what makes mixed solvent systems far more complex compared to single-component solvents. An overview of current and promising techniques for modeling mixed solvent environments is provided. We focus on so-called hybrid solvation treatments such as the conductor-like screening model for real solvents and the reference interaction site model, which are far less computationally demanding than explicit simulations. We also propose that cluster-continuum approaches rooted in physically rigorous quasi-chemical theory provide a robust, yet practical, route for studying chemical processes in mixed solvents.

We investigate the early part of the crystal nucleation process in the hard sphere fluid using data produced by computer simulation. We find that hexagonal order manifests continuously in the overcompressed liquid, beginning approximately one diffusion time before the appearance of the first `solid-like' particle of the nucleating cluster, and that a collective influx of particles towards the nucleation site occurs simultaneously to the ordering process: the density increases leading to nucleation are generated by the same individual particle displacements as the increases in order. We rule out the presence of qualitative differences in the early nucleation process between medium and low overcompressions, and also provide evidence against any separation of translational and orientational order on the relevant lengthscales.

We present the software package FRESHS ( http://www.freshs.org ) for parallel simulation of rare events using sampling techniques from the ‘splitting’ family of methods. Initially, Forward Flux Sampling (FFS) and Stochastic Process Rare Event Sampling (SPRES) have been implemented. These two methods together make rare event sampling available for both quasi-static and full non-equilibrium regimes. Our framework provides a plugin system for software implementing the underlying physics of the system of interest. At present, example plugins exist for our framework to steer the popular MD packages GROMACS, LAMMPS and ESPResSo, but due to the simple interface of our plugin system, it is also easy to attach other simulation software or self-written code. Use of our framework does not require recompilation of the simulation program. The modular structure allows the flexible implementation of further sampling methods or physics engines and creates a basis for objective comparison of different sampling algorithms. Our code is designed to make optimal use of available compute resources. System states are managed using standard database technology so as to allow checkpointing, scaling and flexible analysis. The communication within the framework uses plain TCP/IP networking and is therefore suited to high-performance parallel hardware as well as to distributed or even heterogeneous networks of inexpensive machines. For FFS we implemented an automatic interface placement that ensures optimal, nearly constant flux through the interfaces. We introduce ‘ghost’ (or ‘look-ahead’) runs that remedy the bottleneck which occurs when progressing to the next interface. FRESHS is open-source, providing a publicly available parallelized rare event sampling system.

Methods for absolute free energy calculation by alchemical transformation of a quantitative model to an analytically tractable one are discussed. These absolute free energy methods are placed in the context of other methods, and an attempt is made to describe the best practice for such calculations given the current state of the art. Calculations of the equilibria between the four free energy basins of the dialanine molecule and the two right- and left-twisted basins of DNA are discussed as examples.

Travelling wave ion mobility spectrometry-mass spectrometry (TWIMS-MS) has the capability to separate ions based on their mobility through a gas-filled travelling wave (T-wave) device in the presence of a train of transient voltage pulses. By calibration of this device using analytes of previously determined cross-sectional area (from conventional IMS experiments), collision cross-sections of ions can be determined based on their drift time through the T-wave device. Comparison of experimentally determined cross-sections with theoretical calculations from structural models has the potential to provide methodology which can be applied to analytes of previously uncharacterised structure; however, this comparison relies on a high degree of confidence in both experimental and theoretical methods. Focussing on small (≤200 Da) molecules, collision cross-sections have been measured by TWIMS-MS employing a calibration procedure that uses both oligo-glycine peptides and human haemoglobin-derived tryptic peptides in order to extend the calibration range for the measurement of high mobility ions. The effect of TWIMS wave height parameters on the calibration is addressed. Theoretical TWIMS cross-section calculations have been performed using a rapid, Windows-based, in-house developed projection approximation algorithm. These estimates were optimised by comparison with experimental values for a series of small molecules with rigid core structures by systematic variation of the interaction radii of the atoms comprising these species until theoretical measurements were in agreement with experimentally derived TWIMS cross-sections. The effect of varying the interaction radius for the buffer gas was subsequently studied by comparison of theoretical collision cross-sections calculated using helium and nitrogen radii with TWIMS-MS cross-section measurements determined in either helium or nitrogen buffer gases. It was found that the buffer gas used in theoretical calculations should ideally match the buffer gas in which the cross-sections of the calibrants were originally determined by conventional IMS. The resolving potential of the experimental methodology was demonstrated by separation of two isomeric amino acids, leucine and isoleucine, which showed

Amyloidogenic model peptides are invaluable for investigating assembly mechanisms in disease related amyloids and in protein folding. During aggregation, such peptides can undergo bifurcation leading to fibrils or crystals, however the mechanisms of fibril-to-crystal conversion are unclear. We navigate herein the energy landscape of amyloidogenic peptides by studying a homologous series of hexapeptides found in animal, human and disease related proteins. We observe fibril-to-crystal conversion occurring within single aggregates via untwisting of twisted ribbon fibrils possessing saddle-like curvature and cross-sectional aspect ratios approaching unity. Changing sequence, pH or concentration shifts the growth towards larger aspect ratio species assembling into stable helical ribbons possessing mean-curvature. By comparing atomistic calculations of desolvation energies for association of peptides we parameterise a kinetic model, providing a physical explanation of fibril-to-crystal interconversion. These results shed light on the self-assembly of amyloidogenic peptides, suggesting amyloid crystals, not fibrils, represent the ground state of the protein folding energy landscape.

Detailed knowledge of the tertiary and quaternary structure of proteins and protein complexes is of immense importance in understanding their functionality. Similarly, variations in the conformational states of proteins form the underlying mechanisms behind many biomolecular processes, numerous of which are disease-related. Thus, the availability of reliable and accurate biophysical techniques that can provide detailed information concerning these issues is of paramount importance. Ion mobility spectrometry (IMS) coupled to mass spectrometry (MS) offers a unique opportunity to separate multi-component biomolecular entities and to measure the molecular mass and collision cross-section of individual components in a single, rapid (≤ 2 min) experiment, providing 3D-architectural information directly. Here we report a method of calibrating a commercially available electrospray ionisation (ESI)-travelling wave ion mobility spectrometry (TWIMS)–mass spectrometer using known cross-sectional areas determined for a range of biomolecules by conventional IMS-MS. Using this method of calibration, we have analysed a range of proteins of differing mass and 3D architecture in their native conformations by ESI-TWIMS-MS and found that the cross-sectional areas measured in this way compare extremely favourably with cross-sectional areas calculated using an in-house computing method based on Protein Data Bank NMR-derived co-ordinates. This not only provides a high degree of confidence in the calibration method, but also suggests that the gas phase ESI-TWIMS-MS measurements relate well to solution-based measurements derived from other biophysical techniques. In order to determine which instrumental parameters affect the ESI-TWIMS-MS cross-sectional area calibration, a systematic study of the parameters used to optimise TWIMS drift time separations has been carried out, observing the effect each parameter has on drift times and IMS resolution. Finally, the ESI-TWIMS-MS cross-sectional area calibration has been applied to the analysis of the amyloidogenic protein β2-microglobulin and measurements for three co-populated conformational families, present under denaturing conditions, have been made: the folded, partially unfolded and unfolded states.

We present a molecular dynamics simulation study of crystal nucleation from undercooled melts of n-alkanes, and we identify the molecular mechanism of homogeneous crystal nucleation under quiescent conditions and under shear flow. We compare results for n-eicosane(C20) and n-pentacontahectane(C150), i.e. one system below the entanglement length and one above. Under quiescent conditions, we observe that entanglement does not have an effect on the nucleation mechanism. For both chain lengths, the chains first align and then straighten locally. Then the local density increases and finally positional ordering sets in. At low shear rates the nucleation mechanism is the same as under quiescent conditions, while at high shear rates the chains align and straighten at the same time. We report on the effects of shear rate and temperature on the nucleation rates and estimate the critical shear rates, beyond which the nucleation rates increase with the shear rate. We show that the viscosity of the system is not affected by the crystalline nuclei., 9 pages

Although many computational methods for rare event sampling exist, this type of calculation is not usually practical for general nonequilibrium conditions, with macroscopically irreversible dynamics and away from both stationary and metastable states. A novel method for calculating the time-series of the probability of a rare event is presented which is designed for these conditions. The method is validated for the cases of the Glauber–Ising model under time-varying shear flow, the Kawasaki–Ising model after a quench into the region between nucleation dominated and spinodal decomposition dominated phase change dynamics, and the parallel open asymmetric exclusion process. The method requires a subdivision of the phase space of the system: it is benchmarked and found to scale well for increasingly fine subdivisions, meaning that it can be applied without detailed foreknowledge of the physically important reaction pathways.

Amyloid fibrils are long, helically symmetric protein aggregates that can display substantial variation (polymorphism), including alterations in twist and structure at the beta-strand and protofilament levels, even when grown under the same experimental conditions. The structural and thermodynamic origins of this behavior are not yet understood. We performed molecular-dynamics simulations to determine the thermodynamic properties of different polymorphs of the peptide GNNQQNY, modeling fibrils containing different numbers of protofilaments based on the structure of amyloid-like cross-beta crystals of this peptide. We also modeled fibrils with new orientations of the side chains, as well as a de novo designed structure based on antiparallel beta-strands. The simulations show that these polymorphs are approximately isoenergetic under a range of conditions. Structural analysis reveals a dynamic reorganization of electrostatics and hydrogen bonding in the main and side chains of the Gln and Asn residues that characterize this peptide sequence. Q/N-rich stretches are found in several amyloidogenic proteins and peptides, including the yeast prions Sup35-N and Ure2p, as well as in the human poly-Q disease proteins, including the ataxins and huntingtin. Based on our results, we propose that these residues imbue a unique structural plasticity to the amyloid fibrils that they comprise, rationalizing the ability of proteins enriched in these amino acids to form prion strains with heritable and different phenotypic traits.

Amyloid fibrils often exhibit polymorphism. Polymorphs are formed when proteins or peptides with identical sequences self-assemble into fibrils containing substantially different arrangements of the β-strands. We used atomistic molecular-dynamics simulation to examine the thermodynamic stability of a amyloid fibrils in different polymorphic forms by performing a systematic investigation of sequence and symmetry space for a series of peptides with a range of physicochemical properties. We show that the stability of fibrils depends on both sequence and the symmetry because these factors determine the availability of favorable interactions between the peptide strands within a sheet and in intersheet packing. By performing a detailed analysis of these interactions as a function of symmetry, we obtained a series of simple design rules that can be used to determine which polymorphs of a given sequence are most likely to form thermodynamically stable fibrils. These rules can potentially be employed to design peptide sequences that aggregate into a preferred polymorphic form for nanotechnological purposes.