Multidimensional View of Amyloid Fibril Nucleation in Atomistic Detail

Molecular Driving Forces in the Self-Association of Silaffin Peptide R5 from MD Simulations

The 19-residue silaffin-R5 peptide has been widely studied for its ability to precipitate uniform SiO2 particles through mild temperature and pH pathways, in the absence of any organic solvents. There is consensus that post-translational modification (PTM) of side chains has a large impact on the biomineralization process. Thus, it is imperative to understand the precise mechanisms that dictate the formation of SiO2 from R5 peptide, including the effects of PTM on peptide aggregation and peptide-surface adsorption. In this work, we use molecular dynamics (MD) simulations to study the aggregation of R5 dimer with multiple PTMs, with the presence of different ions in solution. Since this system has strong interactions with deep metastable states, we use parallel bias metadynamics with partitioned families to efficiently sample the different states of the system. We find that peptide aggregation is a prerequisite for biomineralization. We observe that the electrostatic interactions are essential in the R5 dimer aggregation; for wild type R5 that only has positively charged residues, phosphate ions HPO4 2- in the solution form a bridge between two peptides and are essential for peptide aggregation.

Atomic Scale Structure of Self-Assembled Lipidated Peptide Nanomaterials

β-Peptides have great potential as novel biomaterials and therapeutic agents, due to their unique ability to self-assemble into low dimensional nanostructures, and their resistance to enzymatic degradation in vivo. However, the self-assembly mechanisms of β-peptides, which possess increased flexibility due to the extra backbone methylene groups present within the constituent β-amino acids, are not well understood due to inherent difficulties of observing their bottom-up growth pathway experimentally. A computational approach is presented for the bottom-up modelling of the self-assembled lipidated β3-peptides, from monomers, to oligomers, to supramolecular low-dimensional nanostructures, in all-atom detail. The approach is applied to elucidate the self-assembly mechanisms of recently discovered, distinct structural morphologies of low dimensional nanomaterials, assembled from lipidated β3-peptide monomers. The resultant structures of the nanobelts and the twisted fibrils are stable throughout subsequent unrestrained all-atom molecular dynamics simulations, and these assemblies display good agreement with the structural features obtained from X-ray fiber diffraction and atomic force microscopy data. This is the first reported, fully-atomistic model of a lipidated β3-peptide-based nanomaterial, and the computational approach developed here, in combination with experimental fiber diffraction analysis and atomic force microscopy, will be useful in elucidating the atomic scale structure of self-assembled peptide-based and other supramolecular nanomaterials.

Protein Corona Formation and Aggregation of Amyloid β 1-40-Coated Gold Nanocolloids

Amyloid fibrillogenesis is a pathogenic protein aggregation process that occurs through a highly ordered process of protein-protein interactions. To better understand the protein-protein interactions involved in amyloid fibril formation, we formed nanogold colloid aggregates by stepwise additions of ∼2 nmol of amyloid β 1-40 peptide (Aβ1-40) at pH ∼3.7 and ∼25 °C. The processes of protein corona formation and building of gold colloid [diameters (d) of 20 and 80 nm] aggregates were confirmed by a red-shift of the surface plasmon resonance (SPR) band, λpeak, as the number of Aβ1-40 peptides [N(Aβ1-40)] increased. The normalized red-shift of λpeak, Δλ, was correlated with the degree of protein aggregation, and this process was approximated as the adsorption isotherm explained by the Langmuir-Freundlich model. As the coverage fraction (θ) was analyzed as a function of ϕ, which is the N(Aβ1-40) per total surface area of nanogold colloids available for adsorption, the parameters for explaining the Langmuir-Freundlich model were in good agreement for both 20 and 80 nm gold, indicating that ϕ could define the stage of the aggregation process. Surface-enhanced Raman scattering (SERS) imaging was conducted at designated values of ϕ and suggested that a protein-gold surface interaction during the initial adsorption stage may be dependent on the nanosize. The 20 nm gold case seems to prefer a relatively smaller contacting section, such as a -C-N or C═C bond, but a plane of the benzene ring may play a significant role for 80 nm gold. Regardless of the size of the particles, the β-sheet and random coil conformations were considered to be used to form gold colloid aggregates. The methodology developed in this study allows for new insights into protein-protein interactions at distinct stages of aggregation.

Multistep molecular mechanisms of Aβ16-22 fibril formation revealed by lattice Monte Carlo simulations

As a model of self-assembly from disordered monomers to fibrils, the amyloid-β fragment Aβ16-22 was subject to past numerous experimental and computational studies. Because dynamics information between milliseconds and seconds cannot be assessed by both studies, we lack a full understanding of its oligomerization. Lattice simulations are particularly well suited to capture pathways to fibrils. In this study, we explored the aggregation of 10 Aβ16-22 peptides using 65 lattice Monte Carlo simulations, each simulation consisting of 3 × 109 steps. Based on a total of 24 and 41 simulations that converge and do not converge to the fibril state, respectively, we are able to reveal the diversity of the pathways leading to fibril structure and the conformational traps slowing down the fibril formation.

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

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

Design of short peptides and peptide amphiphiles as collagen mimics and an investigation of their interactions with collagen using molecular dynamics simulations and docking studies

Short peptide sequences and bolaamphiphiles derived from natural proteins are gaining importance due to their ability to form unique nanoscale architectures for a variety of biological applications. In this work, we have designed six short peptides (triplet or monomeric forms) and two peptide bolaamphiphiles that either incorporate the bioactive collagen motif (Gly-X-Y) or sequences where Gly, Pro, or hydroxyproline (Hyp) are replaced by Ala or His. For the bolaamphiphiles, a malate moiety was used as the aliphatic linker for connecting His with Hyp to create collagen mimics. Stability of the assemblies was assessed through molecular dynamics simulations and results indicated that (Pro-Ala-His)₃ and (Ala-His-Hyp)₃ formed the most stable structures, while the amphiphiles and the monomers showed some disintegration over the course of the 200 ns simulation, though most regained structural integrity and formed fibrillar structures, and micelles by the end of the simulation, likely due to the formation of more thermodynamically stable conformations. Multiple replica simulations (REMD) were also conducted where the sequences were simulated at different temperatures. Our results showed excellent convergence in most cases compared to constant temperature molecular dynamics simulation. Furthermore, molecular docking and MD simulations of the sequences bound to collagen triple helix structure revealed that several of the sequences had a high binding affinity and formed stable complexes, particularly (Pro-Ala-His)₃ and (Ala-His-Hyp)₃. Thus, we have designed new hybrid-peptide-based sequences which may be developed for potential applications as biomaterials for tissue engineering or drug delivery.

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.

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.

Computational models for studying physical instabilities in high concentration biotherapeutic formulations

Computational prediction of the behavior of concentrated protein solutions is particularly advantageous in early development stages of biotherapeutics when material availability is limited and a large set of formulation conditions needs to be explored. This review provides an overview of the different computational paradigms that have been successfully used in modeling undesirable physical behaviors of protein solutions with a particular emphasis on high-concentration drug formulations. This includes models ranging from all-atom simulations, coarse-grained representations to macro-scale mathematical descriptions used to study physical instability phenomena of protein solutions such as aggregation, elevated viscosity, and phase separation. These models are compared and summarized in the context of the physical processes and their underlying assumptions and limitations. A detailed analysis is also given for identifying protein interaction processes that are explicitly or implicitly considered in the different modeling approaches and particularly their relations to various formulation parameters. Lastly, many of the shortcomings of existing computational models are discussed, providing perspectives and possible directions toward an efficient computational framework for designing effective protein formulations.

Computer Simulations Aimed at Exploring Protein Aggregation and Dissociation

Protein aggregation can lead to well-defined structures that are functional, but is also the cause of the death of neuron cells in many neurodegenerative diseases. The complexity of the molecular events involved in the aggregation kinetics of amyloid proteins and the transient and heterogeneous characters of all oligomers prevent high-resolution structural experiments. As a result, computer simulations have been used to determine the atomic structures of amyloid proteins at different association stages as well as to understand fibril dissociation. In this chapter, we first review the current computer simulation methods used for aggregation with some atomistic and coarse-grained results aimed at better characterizing the early formed oligomers and amyloid fibril formation. Then we present the applications of non-equilibrium molecular dynamics simulations to comprehend the dissociation of protein assemblies.

Dissection of the key steps of amyloid-β peptide 1-40 fibrillogenesis

The aggregation kinetics of Aβ1-40 peptide was characterized using a synergistic approach by a combination of nuclear magnetic resonance, thioflavin-T fluorescence, transmission electron microscopy and dynamic light scattering. A major finding is the experimental detection of high molecular weight oligomers (HMWO) that converts into fibrils nuclei. Our observations are consistent with a mechanism of Aβ1-40 fibrillogenesis that includes the following key steps: i) slow formation of HMWO (Rh ~ 20 nm); ii) conversion of the HMWO into more compact Rh ~ 10 nm fibrils nuclei; iii) fast formation of additional fibrils nuclei through fibril surface catalysed processes; and iv) growth of fibrils by addition of soluble Aβ species. Moreover, NMR diffusion experiments show that at 37 °C soluble Aβ1-40 remains intrinsically disordered and mostly in monomeric form despite evidences of the presence of dimers and/or other small oligomers. A mathematical model is proposed to simulate the aggregation kinetics of Aβ1-40.

Toward empirical force fields that match experimental observables

Biomolecular force fields have been traditionally derived based on a mixture of reference quantum chemistry data and experimental information obtained on small fragments. However, the possibility to run extensive molecular dynamics simulations on larger systems achieving ergodic sampling is paving the way to directly using such simulations along with solution experiments obtained on macromolecular systems. Recently, a number of methods have been introduced to automatize this approach. Here, we review these methods, highlight their relationship with machine learning methods, and discuss the open challenges in the field.

The hazardous effects of the environmental toxic gases on amyloid beta-peptide aggregation: A theoretical perspective

Alzheimer's disease (AD) is one of the leading causes of dementia in elderly people. It has been well documented that the exposure to environmental toxins such as CO, CO₂, SO₂ and NO₂ that are present in the air is considered as a hallmark for the progression of Alzheimer's disease. However, their actual mechanism by which environmental toxin triggers the aggregation of Aβ42 peptide at the molecular and atomic levels remain unknown. In this study, molecular dynamics simulation was carried out to study the aggregation mechanism of the Aβ₄₂ peptide due to its interaction of toxic gas (CO, CO₂, SO₂ and NO₂). During the 400 ns simulation, all the Aβ₄₂ interacted toxic gas (CO, CO₂, SO_2, and NO₂) complexes have smaller Root Mean Square Deviation values when compared to the Aβ₄₂ peptide, which shows that the interaction of toxic gases (CO, CO₂, SO_2, and NO₂) would increase the Aβ₄₂ peptide structural stability. The radius of gyration analysis also supports that Aβ₄₂ interacted CO₂ and SO₂ complexes have the minimum value in the range of 0.95 nm and 1.5 nm. It is accounted that the Aβ₄₂ interacted CO₂ and SO₂ complexes have a greater compact structure in comparison to Aβ₄₂ interacted CO and NO₂ complexes. Furthermore, all the Aβ₄₂ interacted toxic gas (CO, CO₂, SO_2, and NO₂) complexes exhibited an enhanced secondary structural probability for coil and turn regions with a reduced α-helix probability, which indicates that the interaction of toxic gases may enhance the toxicity and aggregation of Aβ₄₂.

Aggregation of disease-related peptides

Protein misfolding and aggregation of amyloid proteins is the fundamental cause of more than 20 diseases. Molecular mechanisms of the self-assembly and the formation of the toxic aggregates are still elusive. Computer simulations have been intensively used to study the aggregation of amyloid peptides of various amino acid lengths related to neurodegenerative diseases. We review atomistic and coarse-grained simulations of short amyloid peptides aimed at determining their transient oligomeric structures and the early and late aggregation steps.

Prediction of Misfolding-Specific Epitopes in SOD1 Using Collective Coordinates

We introduce a global, collective coordinate bias into molecular dynamics simulations that partially unfolds a protein, in order to predict misfolding-specific epitopes based on the regions that locally unfold. Several metrics are used to measure local disorder, including solvent exposed surface area (SASA), native contacts ( Q), and root mean squared fluctuations (RMSF). The method is applied to Cu, Zn superoxide dismutase (SOD1). For this protein, the processes of monomerization, metal loss, and conformational unfolding due to microenvironmental stresses are all separately taken into account. Several misfolding-specific epitopes are predicted, and consensus epitopes are calculated. These predicted epitopes are consistent with the "lower-resolution" peptide sequences used to raise disease-specific antibodies, but the epitopes derived from collective coordinates contain shorter, more refined sequences for the key residues constituting the epitope.

On the Applicability of Force Fields To Study the Aggregation of Amyloidogenic Peptides Using Molecular Dynamics Simulations

Molecular dynamics simulations play an essential role in understanding biomolecular processes such as protein aggregation at temporal and spatial resolutions which are not attainable by experimental methods. For a correct modeling of protein aggregation, force fields must accurately represent molecular interactions. Here, we study the effect of five different force fields on the oligomer formation of Alzheimer's Aβ_16-22 peptide and two of its mutants: Aβ_16-22(F19V,F20V), which does not form fibrils, and Aβ_16-22(F19L) which forms fibrils faster than the wild type. We observe that while oligomer formation kinetics depends strongly on the force field, structural properties, such as the most relevant protein-protein contacts, are similar between them. The oligomer formation kinetics obtained with different force fields differ more from each other than the kinetics between aggregating and nonaggregating peptides simulated with a single force field. We discuss the difficulties in comparing atomistic simulations of amyloid oligomer formation with experimental observables.

Inhibition of GNNQQNY prion peptide aggregation by trehalose: a mechanistic view

Deposition of amyloid fibrils is the seminal event in the pathogenesis of numerous neurodegenerative diseases. The formation of this amyloid assembly is the manifestation of a cascade of structural transitions including toxic oligomer formation in the early stages of aggregation. Thus a viable therapeutic strategy involves the use of small molecular ligands to interfere with this assembly. In this perspective, we have explored the kinetics of aggregate formation of the fibril forming GNNQQNY peptide fragment from the yeast prion protein SUP35 using multiple all atom MD simulations with explicit solvent and provided mechanistic insights into the way trehalose, an experimentally known aggregation inhibitor, modulates the aggregation pathway. The results suggest that the assimilation process is impeded by different barriers at smaller and larger oligomeric sizes: the initial one being easily surpassed at higher temperatures and peptide concentrations. The kinetic profile demonstrates that trehalose delays the aggregation process by increasing both these activation barriers, specifically the latter one. It increases the sampling of small-sized aggregates that lack the beta sheet conformation. Analysis reveals that the barrier in the growth of larger stable oligomers causes the formation of multiple stable small oligomers which then fuse together bimolecularly. The PCA of 26 properties was carried out to deconvolute the events within the temporary lag phases, which suggested dynamism in lags involving an increase in interchain contacts and burial of SASA. The predominant growth route is monomer addition, which changes to condensation on account of a large number of depolymerisation events in the presence of trehalose. The favourable interaction of trehalose specifically with the sidechain of the peptide promotes crowding of trehalose molecules in its vicinity - the combination of both these factors imparts the observed behaviour. Furthermore, increasing trehalose concentration leads to faster expulsion of water molecules than interpeptide interactions. These expelled water molecules have larger translational movement, suggesting an entropy factor to favor the assembly process. Different conformations observed under this condition suggest the role of water molecules in guiding the morphology of the aggregates as well. A similar scenario exists on increasing peptide concentration.

Virus Infection Triggers MAVS Polymers of Distinct Molecular Weight

The mitochondrial antiviral signaling (MAVS) adaptor protein is a central signaling hub required for cells to mount an antiviral response following virus sensing by retinoic acid-inducible gene I (RIG-I)-like receptors. MAVS localizes in the membrane of mitochondria and peroxisomes and in mitochondrial-associated endoplasmic reticulum membranes. Structural and functional studies have revealed that MAVS activity relies on the formation of functional high molecular weight prion-like aggregates. The formation of protein aggregates typically relies on a dynamic transition between oligomerization and aggregation states. The existence of intermediate state(s) of MAVS polymers, other than aggregates, has not yet been documented. Here, we used a combination of non-reducing SDS-PAGE and semi-denaturing detergent agarose gel electrophoresis (SDD-AGE) to resolve whole cell extract preparations to distinguish MAVS polymerization states. While SDD-AGE analysis of whole cell extracts revealed the formation of previously described high molecular weight prion-like aggregates upon constitutively active RIG-I ectopic expression and virus infection, non-reducing SDS-PAGE allowed us to demonstrate the induction of lower molecular weight oligomers. Cleavage of MAVS using the NS3/4A protease revealed that anchoring to intracellular membranes is required for the appropriate polymerization into active high molecular weight aggregates. Altogether, our data suggest that RIG-I-dependent MAVS activation involves the coexistence of MAVS polymers with distinct molecular weights.

Resolving the Atomistic Modes of Anle138b Inhibitory Action on Peptide Oligomer Formation

The diphenyl-pyrazole compound anle138b is a known inhibitor of oligomeric aggregate formation in vitro and in vivo. Therefore, anle138b is considered a promising drug candidate to beneficially interfere with neurodegenerative processes causing devastating pathologies in humans. The atomistic details of the aggregation inhibition mechanism, however, are to date unknown since the ensemble of small nonfibrillar aggregates is structurally heterogeneous and inaccessible to direct structural characterization. Here, we set out to elucidate anle138b's mode of action using all-atom molecular dynamics simulations on the multi-microsecond time scale. By comparing simulations of dimeric to tetrameric aggregates from fragments of four amyloidogenic proteins (Aβ, hTau40, hIAPP, and Sup35N) in the presence and absence of anle138b, we show that the compound reduces the overall number of intermolecular hydrogen bonds, disfavors the sampling of the aggregated state, and remodels the conformational distributions within the small oligomeric peptide aggregates. Most notably, anle138b preferentially interacts with the disordered structure ensemble via its pyrazole moiety, thereby effectively blocking interpeptide main chain interactions and impeding the spontaneous formation of ordered β-sheet structures, in particular those with out-of-register antiparallel β-strands. The structurally very similar compound anle234b was previously identified as inactive by in vitro experiments. Here, we show that anle234b has no significant effect on the aggregation process in terms of reducing the β-structure content. Moreover, we demonstrate that the hydrogen bonding capabilities are autoinhibited due to steric effects imposed by the molecular geometry of anle234b and thereby indirectly confirm the proposed inhibitory mechanism of anle138b. We anticipate that the prominent binding of anle138b to partially disordered and dynamical aggregate structures is a generic basis for anle138b's ability to suppress toxic oligomer formation in a wide range of amyloidogenic peptides and proteins.

Recent progress on understanding the mechanisms of amyloid nucleation

Amyloid fibrils are supramolecular protein assemblies with a fibrous morphology and cross-β structure. The formation of amyloid fibrils typically follows a nucleation-dependent polymerization mechanism, in which a one-step nucleation scheme has widely been accepted. However, a variety of oligomers have been identified in early stages of fibrillation, and a nucleated conformational conversion (NCC) mechanism, in which oligomers serve as a precursor of amyloid nucleation and convert to amyloid nuclei, has been proposed. This development has raised the need to consider more complicated multi-step nucleation processes in addition to the simplest one-step process, and evidence for the direct involvement of oligomers as nucleation precursors has been obtained both experimentally and theoretically. Interestingly, the NCC mechanism has some analogy with the two-step nucleation mechanism proposed for inorganic and organic crystals and protein crystals, although a more dramatic conformational conversion of proteins should be considered in amyloid nucleation. Clarifying the properties of the nucleation precursors of amyloid fibrils in detail, in comparison with those of crystals, will allow a better understanding of the nucleation of amyloid fibrils and pave the way to develop techniques to regulate it.

Comparing the energy landscapes for native folding and aggregation of PrP

Protein sequences are evolved to encode generally one folded structure, out of a nearly infinite array of possible folds. Underlying this code is a funneled free energy landscape that guides folding to the native conformation. Protein misfolding and aggregation are also a manifestation of free-energy landscapes. The detailed mechanisms of these processes are poorly understood, but often involve rare, transient species and a variety of different pathways. The inherent complexity of misfolding has hampered efforts to measure aggregation pathways and the underlying energy landscape, especially using traditional methods where ensemble averaging obscures important rare and transient events. We recently studied the misfolding and aggregation of prion protein by examining 2 monomers tethered in close proximity as a dimer, showing how the steps leading to the formation of a stable aggregated state can be resolved in the single-molecule limit and the underlying energy landscape thereby reconstructed. This approach allows a more quantitative comparison of native folding versus misfolding, including fundamental differences in the dynamics for misfolding. By identifying key steps and interactions leading to misfolding, it should help to identify potential drug targets. Here we describe the importance of characterizing free-energy landscapes for aggregation and the challenges involved in doing so, and we discuss how single-molecule studies can help test proposed structural models for PrP aggregates.

Lattice model for amyloid peptides: OPEP force field parametrization and applications to the nucleus size of Alzheimer's peptides

Coarse-grained protein lattice models approximate atomistic details and keep the essential interactions. They are, therefore, suitable for capturing generic features of protein folding and amyloid formation at low computational cost. As our aim is to study the critical nucleus sizes of two experimentally well-characterized peptide fragments Aβ16-22 and Aβ37-42 of the full length Aβ1-42 Alzheimer's peptide, it is important that simulations with the lattice model reproduce all-atom simulations. In this study, we present a comprehensive force field parameterization based on the OPEP (Optimized Potential for Efficient protein structure Prediction) force field for an on-lattice protein model, which incorporates explicitly the formation of hydrogen bonds and directions of side-chains. Our bottom-up approach starts with the determination of the best lattice force parameters for the Aβ16-22 dimer by fitting its equilibrium parallel and anti-parallel β-sheet populations to all-atom simulation results. Surprisingly, the calibrated force field is transferable to the trimer of Aβ16-22 and the dimer and trimer of Aβ37-42. Encouraged by this finding, we characterized the free energy landscapes of the two decamers. The dominant structure of the Aβ16-22 decamer matches the microcrystal structure. Pushing the simulations for aggregates between 4-mer and 12-mer suggests a nucleus size for fibril formation of 10 chains. In contrast, the Aβ37-42 decamer is largely disordered with mixed by parallel and antiparallel chains, suggesting that the nucleus size is >10 peptides. Our refined force field coupled to this on-lattice model should provide useful insights into the critical nucleation number associated with neurodegenerative diseases.

Hydrodynamic effects on β-amyloid (16-22) peptide aggregation

Computer simulations based on simplified representations are routinely used to explore the early steps of amyloid aggregation. However, when protein models with implicit solvent are employed, these simulations miss the effect of solvent induced correlations on the aggregation kinetics and lifetimes of metastable states. In this work, we apply the multi-scale Lattice Boltzmann Molecular Dynamics technique (LBMD) to investigate the initial aggregation phases of the amyloid Aβ16-22 peptide. LBMD includes naturally hydrodynamic interactions (HIs) via a kinetic on-lattice representation of the fluid kinetics. The peptides are represented by the flexible OPEP coarse-grained force field. First, we have tuned the essential parameters that control the coupling between the molecular and fluid evolutions in order to reproduce the experimental diffusivity of elementary species. The method is then deployed to investigate the effect of HIs on the aggregation of 100 and 1000 Aβ16-22 peptides. We show that HIs clearly impact the aggregation process and the fluctuations of the oligomer sizes by favouring the fusion and exchange dynamics of oligomers between aggregates. HIs also guide the growth of the leading largest cluster. For the 100 Aβ16-22 peptide system, the simulation of ∼300 ns allowed us to observe the transition from ellipsoidal assemblies to an elongated and slightly twisted aggregate involving almost the totality of the peptides. For the 1000 Aβ16-22 peptides, a system of unprecedented size at quasi-atomistic resolution, we were able to explore a branched disordered fibril-like structure that has never been described by other computer simulations, but has been observed experimentally.

The Physical Properties and Self-Assembly Potential of the RFFFR Peptide

The self-assembly of fibers from peptides has attracted a tremendous amount of attention due to its many applications, such as in drug-delivery systems, in tissue engineering, and in electronic devices. Recently, the self-assembly potential of the designer peptide RFFFR has been reported. Here it is experimentally verified that the peptide forms fibers that are entangled and form solid spheres without water inside. Upon dilution below the critical fiber concentration, the fibers untangle and become totally separated prior to dissolution. These structures readily bind thioflavin T, resulting in a characteristic change in fluorescent properties consistent with β-sheet-rich amyloid structures with aromatic/hydrophobic grooves. The circular dichroism spectroscopy data are dominated by a π→π* transition, thus indicating that the fibers are stabilized by π-stacking. Contrary to what was expected, the dissolution of the spheres/fibers results in increasing fluorescence anisotropy over time. This is explained in terms of HomoFRET between phenylalanine residues with a T-shaped π-stacking mode, which was determined in another study to be the dominant mode through atomistic simulations and semiempirical calculations. Kelvin probe force microscopy measurements indicate that the spheres and fibers have a conductivity comparable to that of gold. Hence, these self-assembled structures might be applicable in organic solid-state electronic devices. The dissolution properties of the spheres further suggest that they might be used as drug-delivery systems.

Efficient sampling over rough energy landscapes with high barriers: A combination of metadynamics with integrated tempering sampling

In order to efficiently overcome high free energy barriers embedded in a complex energy landscape and calculate overall thermodynamics properties using molecular dynamics simulations, we developed and implemented a sampling strategy by combining the metadynamics with (selective) integrated tempering sampling (ITS/SITS) method. The dominant local minima on the potential energy surface (PES) are partially exalted by accumulating history-dependent potentials as in metadynamics, and the sampling over the entire PES is further enhanced by ITS/SITS. With this hybrid method, the simulated system can be rapidly driven across the dominant barrier along selected collective coordinates. Then, ITS/SITS ensures a fast convergence of the sampling over the entire PES and an efficient calculation of the overall thermodynamic properties of the simulation system. To test the accuracy and efficiency of this method, we first benchmarked this method in the calculation of ϕ - ψ distribution of alanine dipeptide in explicit solvent. We further applied it to examine the design of template molecules for aromatic meta-C-H activation in solutions and investigate solution conformations of the nonapeptide Bradykinin involving slow cis-trans isomerizations of three proline residues.

An Atomistic View of Amyloidogenic Self-assembly: Structure and Dynamics of Heterogeneous Conformational States in the Pre-nucleation Phase

The formation of well-defined filamentous amyloid structures involves a polydisperse collection of oligomeric states for which relatively little is known in terms of structural organization. Here we use extensive, unbiased explicit solvent molecular dynamics (MD) simulations to investigate the structural and dynamical features of oligomeric aggregates formed by a number of highly amyloidogenic peptides at atomistic resolution on the μs time scale. A consensus approach has been adopted to analyse the simulations in multiple force fields, yielding an in-depth characterization of pre-fibrillar oligomers and their global and local structure properties. A collision cross section analysis revealed structurally heterogeneous aggregate ensembles for the individual oligomeric states that lack a single defined quaternary structure during the pre-nucleation phase. To gain insight into the conformational space sampled in early aggregates, we probed their substructure and found emerging β-sheet subunit layers and a multitude of ordered intermolecular β-structure motifs with growing aggregate size. Among those, anti-parallel out-of-register β-strands compatible with toxic β-barrel oligomers were particularly prevalent already in smaller aggregates and formed prior to ordered fibrillar structure elements. Notably, also distinct fibril-like conformations emerged in the oligomeric state and underscore the notion that pre-nucleated oligomers serve as a critical intermediate step on-pathway to fibrils.

Free energy surface of an intrinsically disordered protein: comparison between temperature replica exchange molecular dynamics and bias-exchange metadynamics

Intrinsically disordered proteins (IDPs), which are expected to be largely unstructured under physiological conditions, make up a large fraction of eukaryotic proteins. Molecular dynamics simulations have been utilized to probe structural characteristics of these proteins, which are not always easily accessible to experiments. However, exploration of the conformational space by brute force molecular dynamics simulations is often limited by short time scales. Present literature provides a number of enhanced sampling methods to explore protein conformational space in molecular simulations more efficiently. In this work, we present a comparison of two enhanced sampling methods: temperature replica exchange molecular dynamics and bias exchange metadynamics. By investigating both the free energy landscape as a function of pertinent order parameters and the per-residue secondary structures of an IDP, namely, human islet amyloid polypeptide, we found that the two methods yield similar results as expected. We also highlight the practical difference between the two methods by describing the path that we followed to obtain both sets of data.

Fe(2+) binding on amyloid β-peptide promotes aggregation

The metal ions Zn(2+) , Cu(2+) , and Fe(2+) play a significant role in the aggregation mechanism of Aβ peptides. However, the nature of binding between metal and peptide has remained elusive; the detailed information on this from the experimental study is very difficult. Density functional theory (dft) (M06-2X/6-311++G (2df,2pd) +LANL2DZ) has employed to determine the force field resulting due to metal and histidine interaction. We performed 200 ns molecular dynamics (MD) simulation on Aβ1-42 -Zn(2+) , Aβ1-42 -Cu(2+) , and Aβ1-42 -Fe(2+) systems in explicit water with different combination of coordinating residues including the three Histidine residues in the N-terminal. The present investigation, the Aβ1-42 -Zn(2+) system possess three turn conformations separated by coil structure. Zn(2+) binding caused the loss of the helical structure of N-terminal residues which transformed into the S-shaped conformation. Zn(2+) has reduced the coil and increases the turn content of the peptide compared with experimental study. On the other hand, the Cu(2+) binds with peptide, β sheet formation is observed at the N-terminal residues of the peptide. Fe(2+) binding is to promote the formation of Glu22-Lys28 salt-bridge which stabilized the turn conformation in the Phe19-Gly25 residues, subsequently β sheets were observed at His13-Lys18 and Gly29-Gly37 residues. The turn conformation facilitates the β sheets are arranged in parallel by enhancing the hydrophobic contact between Gly25 and Met35, Lys16 and Met35, Leu17 and Leu34, Val18 and Leu34 residues. The Fe(2+) binding reduced the helix structure and increases the β sheet content in the peptide, which suggested, Fe(2+) promotes the oligomerization by enhancing the peptide-peptide interaction. Proteins 2016; 84:1257-1274. © 2016 Wiley Periodicals, Inc.

Advances in the Simulation of Protein Aggregation at the Atomistic Scale

Protein aggregation into highly structured amyloid fibrils is associated with various diseases including Alzheimer's disease, Parkinson's disease, and type II diabetes. Amyloids can also have normal biological functions and, in the future, could be used as the basis for novel nanoscale materials. However, a full understanding of the physicochemical forces that drive protein aggregation is still lacking. Such understanding is crucial for the development of drugs that can effectively inhibit aberrant amyloid aggregation and for the directed design of functional amyloids. Atomistic simulations can help understand protein aggregation. In particular, atomistic simulations can be used to study the initial formation of toxic oligomers which are hard to characterize experimentally and to understand the difference in aggregation behavior between different amyloidogenic peptides. Here, we review the latest atomistic simulations of protein aggregation, concentrating on amyloidogenic protein fragments, and provide an outlook for the future in this field.

Critical Nucleus Structure and Aggregation Mechanism of the C-terminal Fragment of Copper-Zinc Superoxide Dismutase Protein

The aggregation of the copper-zinc superoxide dismutase (SOD1) protein is linked to familial amyotrophic lateral sclerosis, a progressive neurodegenerative disease. A recent experimental study has shown that the (147)GVIGIAQ(153) SOD1 C-terminal segment not only forms amyloid fibrils in isolation but also accelerates the aggregation of full-length SOD1, while substitution of isoleucine at site 149 by proline blocks its fibril formation. Amyloid formation is a nucleation-polymerization process. In this study, we investigated the oligomerization and the nucleus structure of this heptapeptide. By performing extensive replica-exchange molecular dynamics (REMD) simulations and conventional MD simulations, we found that the GVIGIAQ hexamers can adopt highly ordered bilayer β-sheets and β-barrels. In contrast, substitution of I149 by proline significantly reduces the β-sheet probability and results in the disappearance of bilayer β-sheet structures and the increase of disordered hexamers. We identified mixed parallel-antiparallel bilayer β-sheets in both REMD and conventional MD simulations and provided the conformational transition from the experimentally observed parallel bilayer sheets to the mixed parallel-antiparallel bilayer β-sheets. Our simulations suggest that the critical nucleus consists of six peptide chains and two additional peptide chains strongly stabilize this critical nucleus. The stabilized octamer is able to recruit additional random peptides into the β-sheet. Therefore, our simulations provide insights into the critical nucleus formation and the smallest stable nucleus of the (147)GVIGIAQ(153) peptide.

Proton Transfer and Structure-Specific Fluorescence in Hydrogen Bond-Rich Protein Structures

Protein structures which form fibrils have recently been shown to absorb light at energies in the near UV range and to exhibit a structure-specific fluorescence in the visible range even in the absence of aromatic amino acids. However, the molecular origin of this phenomenon has so far remained elusive. Here, we combine ab initio molecular dynamics simulations and fluorescence spectroscopy to demonstrate that these intrinsically fluorescent protein fibrils are permissive to proton transfer across hydrogen bonds which can lower electron excitation energies and thereby decrease the likelihood of energy dissipation associated with conventional hydrogen bonds. The importance of proton transfer on the intrinsic fluorescence observed in protein fibrils is signified by large reductions in the fluorescence intensity upon either fully protonating, or deprotonating, the fibrils at pH = 0 or 14, respectively. Thus, our results point to the existence of a structure-specific fluorophore that does not require the presence of aromatic residues or multiple bond conjugation that characterize conventional fluorescent systems. The phenomenon may have a wide range of implications in biological systems and in the design of self-assembled functional materials.

The self-assembly mechanism of tetra-peptides from the motif of β-amyloid peptides: a combined coarse-grained and all-atom molecular dynamics simulation

Understanding the self-assembly mechanisms of tetra-peptides from Aβ-peptides into different nanostructures.

All-Atom Structural Models of the Transmembrane Domains of Insulin and Type 1 Insulin-Like Growth Factor Receptors

The receptor tyrosine kinase superfamily comprises many cell-surface receptors including the insulin receptor (IR) and type 1 insulin-like growth factor receptor (IGF1R) that are constitutively homodimeric transmembrane glycoproteins. Therefore, these receptors require ligand-triggered domain rearrangements rather than receptor dimerization for activation. Specifically, binding of peptide ligands to receptor ectodomains transduces signals across the transmembrane domains for trans-autophosphorylation in cytoplasmic kinase domains. The molecular details of these processes are poorly understood in part due to the absence of structures of full-length receptors. Using MD simulations and enhanced conformational sampling algorithms, we present all-atom structural models of peptides containing 51 residues from the transmembrane and juxtamembrane regions of IR and IGF1R. In our models, the transmembrane regions of both receptors adopt helical conformations with kinks at Pro961 (IR) and Pro941 (IGF1R), but the C-terminal residues corresponding to the juxtamembrane region of each receptor adopt unfolded and flexible conformations in IR as opposed to a helix in IGF1R. We also observe that the N-terminal residues in IR form a kinked-helix sitting at the membrane-solvent interface, while homologous residues in IGF1R are unfolded and flexible. These conformational differences result in a larger tilt-angle of the membrane-embedded helix in IGF1R in comparison to IR to compensate for interactions with water molecules at the membrane-solvent interfaces. Our metastable/stable states for the transmembrane domain of IR, observed in a lipid bilayer, are consistent with a known NMR structure of this domain determined in detergent micelles, and similar states in IGF1R are consistent with a previously reported model of the dimerized transmembrane domains of IGF1R. Our all-atom structural models suggest potentially unique structural organization of kinase domains in each receptor.

Fmoc–RGDS based fibrils: atomistic details of their hierarchical assembly

We describe the 3D supramolecular structure of Fmoc–RGDS fibrils, where Fmoc and RGDS refer to the hydrophobic N-(fluorenyl-9-methoxycarbonyl) group and the hydrophilic Arg-Gly-Asp-Ser peptide sequence, respectively.

Secondary Structure of Rat and Human Amylin across Force Fields

The aggregation of human amylin has been strongly implicated in the progression of Type II diabetes. This 37-residue peptide forms a variety of secondary structures, including random coils, α-helices, and β-hairpins. The balance between these structures depends on the chemical environment, making amylin an ideal candidate to examine inherent biases in force fields. Rat amylin differs from human amylin by only 6 residues; however, it does not form fibrils. Therefore it provides a useful complement to human amylin in studies of the key events along the aggregation pathway. In this work, the free energy of rat and human amylin was determined as a function of α-helix and β-hairpin content for the Gromos96 53a6, OPLS-AA/L, CHARMM22/CMAP, CHARMM22*, Amberff99sb*-ILDN, and Amberff03w force fields using advanced sampling techniques, specifically bias exchange metadynamics. This work represents a first systematic attempt to evaluate the conformations and the corresponding free energy of a large, clinically relevant disordered peptide in solution across force fields. The NMR chemical shifts of rIAPP were calculated for each of the force fields using their respective free energy maps, allowing us to quantitatively assess their predictions. We show that the predicted distribution of secondary structures is sensitive to the choice of force-field: Gromos53a6 is biased towards β-hairpins, while CHARMM22/CMAP predicts structures that are overly α-helical. OPLS-AA/L favors disordered structures. Amberff99sb*-ILDN, AmberFF03w and CHARMM22* provide the balance between secondary structures that is most consistent with available experimental data. In contrast to previous reports, our findings suggest that the equilibrium conformations of human and rat amylin are remarkably similar, but that subtle differences arise in transient alpha-helical and beta-strand containing structures that the human peptide can more readily adopt. We hypothesize that these transient states enable dynamic pathways that facilitate the formation of aggregates and, eventually, amyloid fibrils.

A structural, functional, and computational analysis suggests pore flexibility as the base for the poor selectivity of CNG channels

Cyclic nucleotide-gated (CNG) ion channels, despite a significant homology with the highly selective K(+) channels, do not discriminate among monovalent alkali cations and are permeable also to several organic cations. We combined electrophysiology, molecular dynamics (MD) simulations, and X-ray crystallography to demonstrate that the pore of CNG channels is highly flexible. When a CNG mimic is crystallized in the presence of a variety of monovalent cations, including Na(+), Cs(+), and dimethylammonium (DMA(+)), the side chain of Glu66 in the selectivity filter shows multiple conformations and the diameter of the pore changes significantly. MD simulations indicate that Glu66 and the prolines in the outer vestibule undergo large fluctuations, which are modulated by the ionic species and the voltage. This flexibility underlies the coupling between gating and permeation and the poor ionic selectivity of CNG channels.

Energetic contributions of residues to the formation of early amyloid-β oligomers

Low-weight amyloid-β (Aβ) oligomers formed at early stages of oligomerization rather than fibril assemblies seem to be the toxic components that drive neurodegeneration in Alzheimer's disease. Unfortunately, detailed knowledge of the structure of these early oligomers at the residue level is not yet available. In this study, we performed all-atom explicit solvent molecular dynamics simulations to examine the oligomerization process of Aβ10-35 monomers when forming dimers, trimers, tetramers and octamers, with four independent simulations of a total simulated time of 3 μs for each oligomer system. The decomposition of the stability free energy by MM-GBSA methodology allowed us to unravel the network of energetic interactions that stabilize such oligomers. The contribution of the intermonomeric van der Waals term is the most significant energy feature of the oligomerization process, consistent with the so-called hydrophobic effect. Furthermore, the decomposition of the stability free energy into residues and residue-pairwise terms revealed that it is mainly apolar interactions between the three specific hydrophobic fragments 31-35 (C-terminal region), 17-20 (central hydrophobic core) and 12-14 (N-terminal region) that are responsible for such a favourable effect. The conformation in which the hydrophobic cthr-chc interaction is oriented perpendicularly is particularly important. We propose three other model substructures that favour the oligomerization process and can thus be considered as molecular targets for future inhibitors. Understanding Aβ oligomerization at the residue level could lead to more efficient design of inhibitors of this process.