Self-templated nucleation in peptide and protein aggregation

Advanced computational approaches to understand protein aggregation

Protein aggregation is a widespread phenomenon implicated in debilitating diseases like Alzheimer's, Parkinson's, and cataracts, presenting complex hurdles for the field of molecular biology. In this review, we explore the evolving realm of computational methods and bioinformatics tools that have revolutionized our comprehension of protein aggregation. Beginning with a discussion of the multifaceted challenges associated with understanding this process and emphasizing the critical need for precise predictive tools, we highlight how computational techniques have become indispensable for understanding protein aggregation. We focus on molecular simulations, notably molecular dynamics (MD) simulations, spanning from atomistic to coarse-grained levels, which have emerged as pivotal tools in unraveling the complex dynamics governing protein aggregation in diseases such as cataracts, Alzheimer's, and Parkinson's. MD simulations provide microscopic insights into protein interactions and the subtleties of aggregation pathways, with advanced techniques like replica exchange molecular dynamics, Metadynamics (MetaD), and umbrella sampling enhancing our understanding by probing intricate energy landscapes and transition states. We delve into specific applications of MD simulations, elucidating the chaperone mechanism underlying cataract formation using Markov state modeling and the intricate pathways and interactions driving the toxic aggregate formation in Alzheimer's and Parkinson's disease. Transitioning we highlight how computational techniques, including bioinformatics, sequence analysis, structural data, machine learning algorithms, and artificial intelligence have become indispensable for predicting protein aggregation propensity and locating aggregation-prone regions within protein sequences. Throughout our exploration, we underscore the symbiotic relationship between computational approaches and empirical data, which has paved the way for potential therapeutic strategies against protein aggregation-related diseases. In conclusion, this review offers a comprehensive overview of advanced computational methodologies and bioinformatics tools that have catalyzed breakthroughs in unraveling the molecular basis of protein aggregation, with significant implications for clinical interventions, standing at the intersection of computational biology and experimental research.

A geometrical framework for thinking about proteins

We present a model, based on symmetry and geometry, for proteins. Using elementary ideas from mathematics and physics, we derive the geometries of discrete helices and sheets. We postulate a compatible solvent-mediated emergent pairwise attraction that assembles these building blocks, while respecting their individual symmetries. Instead of seeking to mimic the complexity of proteins, we look for a simple abstraction of reality that yet captures the essence of proteins. We employ analytic calculations and detailed Monte Carlo simulations to explore some consequences of our theory. The predictions of our approach are in accord with experimental data. Our framework provides a rationalization for understanding the common characteristics of proteins. Our results show that the free energy landscape of a globular protein is pre-sculpted at the backbone level, sequences and functionalities evolve in the fixed backdrop of the folds determined by geometry and symmetry, and that protein structures are unique in being simultaneously characterized by stability, diversity, and sensitivity.

Conformational entropy limits the transition from nucleation to elongation in amyloid aggregation

The formation of β-sheet rich amyloid fibrils in Alzheimer's disease and other neurodegenerative disorders is limited by a slow nucleation event. To understand the initial formation of β-sheets from disordered peptides, we used all-atom simulations to parameterize a lattice model that treats each amino acid as a binary variable with β and non-β states. We show that translational and conformational entropy give the nascent β-sheet an anisotropic surface tension which can be used to describe the nucleus with two-dimensional Classical Nucleation Theory. Since translational entropy depends on concentration, the aspect ratio of the critical β-sheet changes with protein concentration. Our model explains the transition from the nucleation phase to elongation as the point where the β-sheet core becomes large enough to overcome the conformational entropy cost to straighten the terminal molecule. At this point the β-strands in the nucleus spontaneously elongate, which results in a larger binding surface to capture new molecules. These results suggest that nucleation is relatively insensitive to sequence differences in co-aggregation experiments because the nucleus only involves a small portion of the peptide.

Short Peptides as Tunable, Switchable, and Strong Gelators

This Perspective outlines our current understanding of molecular gels composed of short and ultrashort peptides over the past 20 years. We discuss in detail the state of the art regarding self-assembly mechanisms, structure, thermal stability, and kinetics of fibril and/or network formation. Emphasis is put on the importance of the combined use of spectroscopy and rheology for characterizing and validating self-assembly models. While a range of peptide chemistries are reviewed, we focus our discussion on a unique new class of ultrashort peptide gelators, denoted GxG peptides (x: guest residue), which are capable of forming self-assembled fibril networks. The storage moduli of GxG gels are tunable up to 100 kPa depending on concentration, pH, and/or cosolvent. The sheet structures of the fibrils differ from canonical β-sheets. When appropriate, each section highlights opportunities for additional research and technologies that would further our understanding.

Structure and function of the perivascular fluid compartment and vertebral venous plexus: Illumining a novel theory on mechanisms underlying the pathogenesis of Alzheimer's, cerebral small vessel, and neurodegenerative diseases

Blood dynamically and richly supplies the cerebral tissue via microvessels invested in pia matter perforating the cerebral substance. Arteries penetrating the cerebral substance derive an investment from one or two successive layers of pia mater, luminally apposed to the pial-glial basal lamina of the microvasculature and abluminally apposed to a series of aquaporin IV-studded astrocytic end feet constituting the soi-disant glia limitans. The full investment of successive layers forms the variably continuous walls of the periarteriolar, pericapillary, and perivenular divisions of the perivascular fluid compartment. The pia matter disappears at the distal periarteriolar division of the perivascular fluid compartment. Plasma from arteriolar blood sequentially transudates into the periarteriolar division of the perivascular fluid compartment and subarachnoid cisterns in precession to trickling into the neural interstitium. Fluid from the neural interstitium successively propagates into the venules through the subarachnoid cisterns and perivenular division of the perivascular fluid compartment. Fluid fluent within the perivascular fluid compartment flows gegen the net direction of arteriovenular flow. Microvessel oscillations at the central tendency of the cerebral vasomotion generate corresponding oscillations of within the surrounding perivascular fluid compartment, interposed betwixt the abluminal surface of the vessels and internal surface of the pia mater. The precise microanatomy of this most fascinating among designable spaces has eluded the efforts of various investigators to interrogate its structure, though most authors non-consensusly concur the investing layers effectively and functionally segregate the perivascular and subarachnoid fluid compartments. Enlargement of the perivascular fluid compartment in a variety of neurological disorders, including senile dementia of the Alzheimer's type and cerebral small vessel disease, may alternately or coordinately constitute a correlative marker of disease severity and a possible cause implicated in the mechanistic pathogenesis of these conditions. Venular pressures modulating oscillatory dynamic flow within the perivascular fluid compartment may similarly contribute to the development of a variety among neurological disorders. An intimate understanding of subtle features typifying microanatomy and microphysiology of the investing structures and spaces of the cerebral microvasculature may powerfully inform mechanistic pathophysiology mediating a variety of neurovascular ischemic, neuroinfectious, neuroautoimmune, and neurodegenerative diseases.

A two-step biopolymer nucleation model shows a nonequilibrium critical point

Biopolymer self-assembly pathways are complicated by the ability of their monomeric subunits to adopt different conformational states. This means nucleation often involves a two-step mechanism where the monomers first condense to form a metastable intermediate, which then converts to a stable polymer by conformational rearrangement of constituent monomers. Nucleation intermediates play a causative role in amyloid diseases such as Alzheimer's and Parkinson's. While existing mathematical models neglect the conversion dynamics, experiments show that conversion events frequently occur on comparable timescales to the condensation of intermediates and growth of mature polymers and thus cannot be ignored. We present a model that explicitly accounts for simultaneous assembly and conversion. To describe conversion, we propose an experimentally motivated initiation-propagation mechanism in which the stable phase arises locally within the intermediate and then spreads by nearest-neighbor interactions, in a manner analogous to one-dimensional Glauber dynamics. Our analysis shows that the competing timescales of assembly and conversion result in a nonequilibrium critical point, separating a regime where intermediates are kinetically unstable from one where conformationally mixed intermediates accumulate. This strongly affects the accumulation rate of the stable biopolymer phase. Our model is uniquely able to explain experimental phenomena such as the formation of mixed intermediates and abrupt changes in the scaling exponent γ, which relates the total monomer concentration to the accumulation rate of the stable phase. This provides a first step toward a general model of two-step biopolymer nucleation, which can quantitatively predict the concentration and composition of biologically crucial intermediates.

Thermodynamics of Huntingtin Aggregation

Amyloid aggregates are found in many neurodegenerative diseases, including Huntington's, Alzheimer's, and prion diseases. The precise role of the aggregates in disease progression has been difficult to elucidate because of the diversity of aggregated states they can adopt. Here, we study the formation of fibrils and oligomers by exon 1 of huntingtin protein. We show that the oligomer states are consistent with polymer micelles that are limited in size by the stretching entropy of the polyglutamine region. The model shows how the sequences flanking the amyloid core modulate aggregation behavior. The N17 region promotes aggregation through weakly attractive interactions, whereas the C38 tail opposes aggregation via steric repulsion. We also show that the energetics of cross-β stacking by polyglutamine would produce fibrils with many alignment defects, but minor perturbations from the flanking sequences are sufficient to reduce the defects to the level observed in experiment. We conclude with a discussion of the implications of this model for other amyloid-forming molecules.

Theoretical and computational advances in protein misfolding

Misfolded proteins escape the cellular quality control mechanism and fail to fold properly or remain correctly folded leading to a loss in their functional specificity. Thus misfolding of proteins cause a large number of very different diseases ranging from errors in metabolism to various types of complex neurodegenerative diseases. A theoretical and computational perspective of protein misfolding is presented with a special emphasis on its salient features, mechanism and consequences. These insights quantitatively analyze different determinants of misfolding, that may be applied to design disease specific molecular targets.

Is a cross-β-sheet structure of low molecular weight peptides necessary for the formation of fibrils and peptide hydrogels?

Short peptides have emerged as versatile building blocks for supramolecular structures and hydrogels. In particular, the presence of aromatic amino acid residues and/or aromatic end groups is generally considered to be a prerequisite for initiating aggregation of short peptides into nanotubes or cross β-sheet type fibrils. However, the cationic GAG tripeptide surprisingly violates these rules. Specifically, in water/ethanol mixtures, GAG peptides aggregate into very long crystalline fibrils at temperatures below 35 °C where they eventually form a spanning network structure and, thus, a hydrogel. Two gel phases are formed in this network, and they differ substantially in chirality and thickness of the underlying fibrils, their rheological parameters, and the kinetics of oligomerization, fibrilization, and gel formation. The spectroscopic data strongly suggests that the observed fibrils do not exhibit canonical cross β-sheet structures and are indicative of a yet unknown secondary conformation. To complement our unusual experimental observations in this perspective article, we performed large-scale DFT calculations to probe the geometry and spectroscopic properties of these GAG oligomers. Most importantly, our experimental and computational results yield rather unconventional structures that are not reminiscent of classical cross-β-sheet structures, and we give two extremely likely candidates for oligomer structures that are consistent with experimental amide I' profiles in IR and vibrational circular dichroism (VCD) spectra of the two gel phases.

Amino acid conformations control the morphological and chiral features of the self-assembled peptide nanostructures: Young investigators perspective

HYPOTHESIS

A variety of nanostructures with different chiral features can be self-assembled from short peptides with highly similar sequences. We hypothesize that these supramolecular nanostructures are ruled by the constituent amino acid residues which adopt their conformations under the influence of intra-/inter-molecular interactions during peptide self-assembly.

APPROACH

Through reviewing recent advances in the self-assembly of short peptides and focusing on the relationship between amino acid conformations, peptide secondary structures and intra-/inter-molecular interactions within the supramolecular architectures, we aim to rationalize the complex interactive processes involved in the self-assembly of short, designed peptides.

RESULTS

Given the highly complexing interactive processes, the adoption of amino acid conformations and their control over peptide self-assembly consist of 4 main steps: (1) Each amino acid residue adopts its unique conformation in a specific sequence; (2) The sequence exhibits its own main chain geometry and determines the propensity of the intermolecular alignment within the building block; (3) The structural propensity of the building block and the packing mode between them determine the self-assembled structural features such as twisting, growth and chirality; (4) In addition to intra-/inter-molecular interactions, inter-sheet and inter-building block interactions could also affect the residue conformations and nanostructures, causing structural readjustment.

Sequence dependent aggregation of peptides and fibril formation

Deciphering the links between amino acid sequence and amyloid fibril formation is key for understanding protein misfolding diseases. Here we use Monte Carlo simulations to study the aggregation of short peptides in a coarse-grained model with hydrophobic-polar (HP) amino acid sequences and correlated side chain orientations for hydrophobic contacts. A significant heterogeneity is observed in the aggregate structures and in the thermodynamics of aggregation for systems of different HP sequences and different numbers of peptides. Fibril-like ordered aggregates are found for several sequences that contain the common HPH pattern, while other sequences may form helix bundles or disordered aggregates. A wide variation of the aggregation transition temperatures among sequences, even among those of the same hydrophobic fraction, indicates that not all sequences undergo aggregation at a presumable physiological temperature. The transition is found to be the most cooperative for sequences forming fibril-like structures. For a fibril-prone sequence, it is shown that fibril formation follows the nucleation and growth mechanism. Interestingly, a binary mixture of peptides of an aggregation-prone and a non-aggregation-prone sequence shows the association and conversion of the latter to the fibrillar structure. Our study highlights the role of a sequence in selecting fibril-like aggregates and also the impact of a structural template on fibril formation by peptides of unrelated sequences.

A Free Energy Barrier Caused by the Refolding of an Oligomeric Intermediate Controls the Lag Time of Amyloid Formation by hIAPP

Transiently populated oligomers formed en route to amyloid fibrils may constitute the most toxic aggregates associated with many amyloid-associated diseases. Most nucleation theories used to describe amyloid aggregation predict low oligomer concentrations and do not take into account free energy costs that may be associated with structural rearrangements between the oligomer and fiber states. We have used isotope labeling and two-dimensional infrared spectroscopy to spectrally resolve an oligomeric intermediate during the aggregation of the human islet amyloid protein (hIAPP or amylin), the protein associated with type II diabetes. A structural rearrangement includes the F₂₃G₂₄A₂₅I₂₆L₂₇ region of hIAPP, which starts from a random coil structure, evolves into ordered β-sheet oligomers containing at least 5 strands, and then partially disorders in the fibril structure. The supercritical concentration is measured to be between 150 and 250 μM, which is the thermodynamic parameter that sets the free energy of the oligomers. A 3-state kinetic model fits the experimental data, but only if it includes a concentration independent free energy barrier >3 kcal/mol that represents the free energy cost of refolding the oligomeric intermediate into the structure of the amyloid fibril; i.e., "oligomer activation" is required. The barrier creates a transition state in the free energy landscape that slows fibril formation and creates a stable population of oligomers during the lag phase, even at concentrations below the supercritical concentration. Largely missing in current kinetic models is a link between structure and kinetics. Our experiments and modeling provide evidence that protein structural rearrangements during aggregation impact the populations and kinetics of toxic oligomeric species.

β-Amyloid and the Pathomechanisms of Alzheimer's Disease: A Comprehensive View

Protein dyshomeostasis is the common mechanism of neurodegenerative diseases such as Alzheimer’s disease (AD). Aging is the key risk factor, as the capacity of the proteostasis network declines during aging. Different cellular stress conditions result in the up-regulation of the neurotrophic, neuroprotective amyloid precursor protein (APP). Enzymatic processing of APP may result in formation of toxic Aβ aggregates (β-amyloids). Protein folding is the basis of life and death. Intracellular Aβ affects the function of subcellular organelles by disturbing the endoplasmic reticulum-mitochondria cross-talk and causing severe Ca²⁺-dysregulation and lipid dyshomeostasis. The extensive and complex network of proteostasis declines during aging and is not able to maintain the balance between production and disposal of proteins. The effectivity of cellular pathways that safeguard cells against proteotoxic stress (molecular chaperones, aggresomes, the ubiquitin-proteasome system, autophagy) declines with age. Chronic cerebral hypoperfusion causes dysfunction of the blood-brain barrier (BBB), and thus the Aβ-clearance from brain-to-blood decreases. Microglia-mediated clearance of Aβ also declines, Aβ accumulates in the brain and causes neuroinflammation. Recognition of the above mentioned complex pathogenesis pathway resulted in novel drug targets in AD research.

Fibril-Barrel Transitions in Cylindrin Amyloids

We introduce Replica-Exchange-with-Tunneling (RET) simulations as a tool for studies of the conversion between polymorphic amyloids. For the 11-residue amyloid-forming cylindrin peptide we show that this technique allows for a more efficient sampling of the formation and interconversion between fibril-like and barrel-like assemblies. We describe a protocol for optimized analysis of RET simulations that allows us to propose a mechanism for formation and interconversion between various cylindrin assemblies. Especially, we show that an interchain salt bridge between residues K3 and D7 is crucial for formation of the barrel structure.

Theory of amyloid fibril nucleation from folded proteins

We present a theoretical model for the nucleation of amyloid fibrils. In our model we use helix-coil theory to describe the equilibrium between a soluble native state and an aggregation-prone unfolded state. We then extend the theory to include oligomers with β-sheet cores and calculate the free energy of these states using estimates for the energies of H-bonds, steric zipper interactions, and the conformational entropy cost of forming secondary structure. We find that states with fewer than ~10 β-strands are unstable relative to the dissociated state and three β-strands is the highest free energy state. We then use a modified version of Classical Nucleation Theory to compute the nucleation rate of fibrils from a supersaturated solution of monomers, dimers, and trimers. The nucleation rate has a non-monotonic dependence on denaturant concentration reflecting the competing effects of destabilizing the fibril and increasing the concentration of unfolded monomers. We estimate heterogeneous nucleation rates and discuss the application of our model to secondary nucleation.

Physical principles of filamentous protein self-assembly kinetics

The polymerization of proteins and peptides into filamentous supramolecular structures is an elementary form of self-organization of key importance to the functioning biological systems, as in the case of actin biofilaments that compose the cellular cytoskeleton. Aberrant filamentous protein self-assembly, however, is associated with undesired effects and severe clinical disorders, such as Alzheimer's and Parkinson's diseases, which, at the molecular level, are associated with the formation of certain forms of filamentous protein aggregates known as amyloids. Moreover, due to their unique physicochemical properties, protein filaments are finding extensive applications as biomaterials for nanotechnology. With all these different factors at play, the field of filamentous protein self-assembly has experienced tremendous activity in recent years. A key question in this area has been to elucidate the microscopic mechanisms through which filamentous aggregates emerge from dispersed proteins with the goal of uncovering the underlying physical principles. With the latest developments in the mathematical modeling of protein aggregation kinetics as well as the improvement of the available experimental techniques it is now possible to tackle many of these complex systems and carry out detailed analyses of the underlying microscopic steps involved in protein filament formation. In this paper, we review some classical and modern kinetic theories of protein filament formation, highlighting their use as a general strategy for quantifying the molecular-level mechanisms and transition states involved in these processes.

Primary Fibril Nucleation of Aggregation Prone Tau Fragments PHF6 and PHF6

We performed replica exchange molecular dynamics and forward flux sampling simulations of hexapeptide VQIINK and VQIVYK systems, also known as, respectively, fragments PHF6* and PHF6 from the tau protein. Being a part of the microtubule binding region, these fragments are known to be aggregation prone, and at least one of them is a prerequisite for fibril formation of the tau protein. Using a coarse-grained force field, we establish the phase behavior of both fragments, and investigate the nucleation kinetics for the conversion into a β-sheet fibril. As the conversion is, in principle, a reversible process, we predict the rate constants for both the fibril formation and melting, and examine the corresponding mechanisms. Our simulations indicate that, while both fragments form disordered aggregates, only PHF6 is able to form β-sheet fibrils. This observation provides a possible explanation for the lack of available steric zipper crystal structures for PHF6*.

Protein Aggregation and Molecular Crowding: Perspectives From Multiscale Simulations

Cells are extremely crowded environments, thus the use of diluted salted aqueous solutions containing a single protein is too simplistic to mimic the real situation. Macromolecular crowding might affect protein structure, folding, shape, conformational stability, binding of small molecules, enzymatic activity, interactions with cognate biomolecules, and pathological aggregation. The latter phenomenon typically leads to the formation of amyloid fibrils that are linked to several lethal neurodegenerative diseases, but that can also play a functional role in certain organisms. The majority of molecular simulations performed before the last few years were conducted in diluted solutions and were restricted both in the timescales and in the system dimensions by the available computational resources. In recent years, several computational solutions were developed to get close to physiological conditions. In this review we summarize the main computational techniques used to tackle the issue of protein aggregation both in a diluted and in a crowded environment.

Dilute Semiflexible Polymers with Attraction: Collapse, Folding and Aggregation

We review the current state on the thermodynamic behavior and structural phases of self- and mutually-attractive dilute semiflexible polymers that undergo temperature-driven transitions. In extreme dilution, polymers may be considered isolated, and this single polymer undergoes a collapse or folding transition depending on the internal structure. This may go as far as to stable knot phases. Adding polymers results in aggregation, where structural motifs again depend on the internal structure. We discuss in detail the effect of semiflexibility on the collapse and aggregation transition and provide perspectives for interesting future investigations.

Modulating the Nucleated Self-Assembly of Tri-β(3) -Peptides Using Cucurbit[n]urils

The modulation of the hierarchical nucleated self-assembly of tri-β(3) -peptides has been studied. β(3) -Tyrosine provided a handle to control the assembly process through host-guest interactions with CB[7] and CB[8]. By varying the cavity size from CB[7] to CB[8] distinct phases of assembling tri-β(3) -peptides were arrested. Given the limited size of the CB[7] cavity, only one aromatic β(3) -tyrosine can be simultaneously hosted and, hence, CB[7] was primarily acting as an inhibitor of self-assembly. In strong contrast, the larger CB[8] can form a ternary complex with two aromatic amino acids and hence CB[8] was acting primarily as cross-linker of multiple fibers and promoting the formation of larger aggregates. General insights on modulating supramolecular assembly can lead to new ways to introduce functionality in supramolecular polymers.

The interplay of aggregation, fibrillization and gelation of an unexpected low molecular weight gelator: glycylalanylglycine in ethanol/water

Hydrogels formed by polypeptides could be much-favored tools for drug delivery because their main ingredients are generally biodegradable. However, the gelation of peptides in aqueous solution generally requires a minimal length of the peptide as well as distinct sequences of hydrophilic and hydrophobic residues. The aggregation of short peptides like tripeptides, which are relatively cheap and offer a high degree of biodegradability, are generally thought to require a high hydrophobicity of their residues. We found that contrary to this expectation cationic glycylalanylglycine in 55 mol% ethanol/45 mol% water forms a gel below a melting temperature of ca. 36 °C. A pure hydrogel state can be obtained after allowing the ethanol component to evaporate. The gel phase consists of crystalline fibrils of several 100 μm, which form a sample-spanning network. Rheological data reveal a soft elastic solid gel. We investigated the kinetics of the various processes that lead to the final gel state of the ternary mixture by a unique combination of UV circular dichroism, infrared, vibrational circular dichroism (VCD) and rheological measurements. A mathematical analysis of our data show that gelation is preceded by the formation of peptide β-sheet like tapes or ribbons, which give rise to a significant enhancement of the amide I' VCD signal, and the subsequent formation of rather thick and long fibrils. The VCD signals indicate that the tapes exhibit a right-handed helicity at temperatures above 16 °C and a left-handed helicity below. The tapes'/ribbons' helicity change occurs at a temperature where the UVCD data reflect a relatively long nucleation process. The kinetics of gel formation probed by the storage and loss moduli are composed of a fast process that follows tape/ribbon/fibril formation and is clearly identifiable in a movie that shows the gelation process and a slow process that causes an additional gel stabilization. The rheological data indicate that left-handed fibrils observed at low temperatures form a more solid-like structure than their right-handed counterparts formed at higher temperatures. Taken together our data reveal GAG as an unexpected gelator, the formation of which is underlied by a set of distinguishable kinetic processes.

Thermodynamics of amyloid formation and the role of intersheet interactions

The self-assembly of proteins into β-sheet-rich amyloid fibrils has been observed to occur with sigmoidal kinetics, indicating that the system initially is trapped in a metastable state. Here, we use a minimal lattice-based model to explore the thermodynamic forces driving amyloid formation in a finite canonical (NVT) system. By means of generalized-ensemble Monte Carlo techniques and a semi-analytical method, the thermodynamic properties of this model are investigated for different sets of intersheet interaction parameters. When the interactions support lateral growth into multi-layered fibrillar structures, an evaporation/condensation transition is observed, between a supersaturated solution state and a thermodynamically distinct state where small and large fibril-like species exist in equilibrium. Intermediate-size aggregates are statistically suppressed. These properties do not hold if aggregate growth is one-dimensional.

Pseudo-one-dimensional nucleation in dilute polymer solutions

Pathogenic protein fibrils have been shown in vitro to have nucleation-dependent kinetics despite the fact that one-dimensional structures do not have the size-dependent surface energy responsible for the lag time in classical theory. We present a theory showing that the conformational entropy of the peptide chains creates a free-energy barrier that is analogous to the translational entropy barrier in higher dimensions. We find that the dynamics of polymer rearrangement make it very unlikely for nucleation to succeed along the lowest free-energy trajectory, meaning that most of the nucleation flux avoids the free-energy saddle point. We use these results to construct a three-dimensional model for amyloid nucleation that accounts for conformational entropy, backbone H bonds, and side-chain interactions to compute nucleation rates as a function of concentration.

Prediction of a stable associated liquid of short amyloidogenic peptides

Amyloid fibril formation is believed to be a nucleation-controlled process. Depending on the nature of peptide sequence, fibril nucleation can occur in one step, straight from a dilute solution, or in multiple steps via oligomers or disordered aggregates. What determines this process is poorly understood. Since the fibril formation kinetics is driven by thermodynamic forces, knowledge of the phase behavior is crucial. Here, we investigated the phase behavior of three short peptide sequences of varying side-chain hydrophobicity. Replica exchange molecular dynamics simulations of a mid-resolution model indicate that the weakly hydrophobic peptide forms fibrils directly from solution, whereas the most hydrophobic peptide forms a dense liquid phase before crystallizing into ordered fibrils at low temperatures. For the medium hydrophobic peptide we found evidence of a novel additional transition to a liquid phase consisting of clusters of aligned peptides, implying a three-step nucleation process. We tested the robustness of this prediction by applying Wertheim's theory and statistical associating fluid theory to a hard-sphere model dressed with isotropic and anisotropic attractions. We found that the ratio of interaction strengths strongly affects the phase behavior, and under certain conditions indeed gives rise to a stable polymerized liquid phase. The peptide clusters in the associated liquid tend to be slow and long-lived, which may give the oligomer droplet more time to act as a toxic oligomer, before turning into a fibril.

Dynamics of the conformational transitions during the dimerization of an intrinsically disordered peptide: a case study on the human islet amyloid polypeptide fragment

Dimerization pathways of the human islet amyloid polypeptide fragment are elucidated from extensive molecular dynamics simulations.

Mapping the Protein Fold Universe Using the CamTube Force Field in Molecular Dynamics Simulations

It has been recently shown that the coarse-graining of the structures of polypeptide chains as self-avoiding tubes can provide an effective representation of the conformational space of proteins. In order to fully exploit the opportunities offered by such a ‘tube model’ approach, we present here a strategy to combine it with molecular dynamics simulations. This strategy is based on the incorporation of the ‘CamTube’ force field into the Gromacs molecular dynamics package. By considering the case of a 60-residue polyvaline chain, we show that CamTube molecular dynamics simulations can comprehensively explore the conformational space of proteins. We obtain this result by a 20 μs metadynamics simulation of the polyvaline chain that recapitulates the currently known protein fold universe. We further show that, if residue-specific interaction potentials are added to the CamTube force field, it is possible to fold a protein into a topology close to that of its native state. These results illustrate how the CamTube force field can be used to explore efficiently the universe of protein folds with good accuracy and very limited computational cost.

Modelling protein behaviour using computer simulations has progressively emerged in the last 50 years as a powerful strategy in structural and molecular biology. Over this period there has been a continuing interest in pushing the boundaries of this approach in terms of the size of the systems and the timescale of the processes that can be studied. Coarse-grained models offer in principle great opportunities in this context, but it has been extremely challenging to obtain force fields of accuracy comparable to that typical of fully atomistic models. We show here that the representation of protein molecules as self-avoiding tubes within the CamTube model enables the comprehensive, accurate and very fast exploration of the conformational space of proteins in molecular dynamics simulations. We illustrate in particular how the comprehensive mapping of the protein fold universe obtained using the CamTube model offers the possibility of analysing the behaviour of proteins in a wide range of non-native states.

Simulations of Protein Aggregation: Insights from Atomistic and Coarse-Grained Models

This Perspective highlights recent computational approaches to protein aggregation, from coarse-grained models to atomistic simulations, using the islet amyloid polypeptide (IAPP) as a case study. We review salient open questions where simulations can make an impact, discuss the successes and challenges met by simulations, and explore new directions.

Understanding amyloid fibril nucleation and aβ oligomer/drug interactions from computer simulations

Evolution has fine-tuned proteins to accomplish a variety of tasks. Yet, with aging, some proteins assemble into harmful amyloid aggregates associated with neurodegenerative diseases, such as Alzheimer's disease (AD), which presents a complex and costly challenge to our society. Thus, far, drug after drug has failed to slow the progression of AD, characterized by the self-assembly of the 39-43 amino acid β-amyloid (Aβ) protein into extracellular senile plaques that form a cross-β structure. While there is experimental evidence that the Aβ small oligomers are the primary toxic species, standard tools of biology have failed to provide structures of these transient, inhomogeneous assemblies. Despite extensive experimental studies, researchers have not successfully characterized the nucleus ensemble, the starting point for rapid fibril formation. Similarly scientists do not have atomic data to show how the compounds that reduce both fibril formation and toxicity in cells bind to Aβ42 oligomers. In this context, computer simulations are important tools for gaining insights into the self-assembly of amyloid peptides and the molecular mechanism of inhibitors. This Account reviews what analytical models and simulations at different time and length scales tell us about the dynamics, kinetics, and thermodynamics of amyloid fibril formation and, notably, the nucleation process. Though coarse-grained and mesoscopic protein models approximate atomistic details by averaging out unimportant degrees of freedom, they provide generic features of amyloid formation and insights into mechanistic details of the self-assembly process. The thermodynamics and kinetics vary from linear peptides adopting straight β-strands in fibrils to longer peptides adopting in parallel U shaped conformations in fibrils. In addition, these properties change with the balance between electrostatic and hydrophobic interactions and the intrinsic disorder of the system. However, simulations suggest that the critical nucleus size might be on the order of 20 chains under physiological conditions. The transition state might be characterized by a simultaneous change from mixed antiparallel/parallel β-strands with random side-chain packing to the final antiparallel or parallel states with the steric zipper packing of the side chains. Second, we review our current computer-based knowledge of the 3D structures of inhibitors with Aβ42 monomer and oligomers, a prerequisite for developing new drugs against AD. Recent extensive all-atom simulations of Aβ42 dimers with known inhibitors such as the green tea compound epigallocatechin-3-gallate and 1,4-naphthoquinon-2-yl-l-tryptophan provide a spectrum of initial Aβ42/inhibitor structures useful for screening and drug design. We conclude by discussing future directions that may offer opportunities to fully understand nucleation and further AD drug development.

Impact of sequence on the molecular assembly of short amyloid peptides

The goal of this work is to understand how the sequence of a protein affects the likelihood that it will form an amyloid fibril and the kinetics along the fibrillization pathway. The focus is on very short fragments of amyloid proteins since these play a role in the fibrillization of the parent protein and can form fibrils themselves. Discontinuous molecular dynamics simulations using the PRIME20 force field were performed of the aggregation of 48-peptide systems containing SNQNNF (PrP (170-175)), SSTSAA (RNaseA(15-20)), MVGGVV (Aβ(35-40)), GGVVIA (Aβ(37-42)), and MVGGVVIA (Aβ(35-42)). In our simulations SNQQNF, SSTTSAA, and MVGGVV form large numbers of fibrillar structures spontaneously (as in experiment). GGVVIA forms β-sheets that do not stack into fibrils (unlike experiment). The combination sequence MVGGVVIA forms less fibrils than MVGGVV, hindered by the presence of the hydrophobic residues at the C-terminal. Analysis of the simulation kinetics and energetics reveals why MVGGVV forms fibrils and GGVVIA does not, and why adding I and A to MVGGVVIA reduces fibrillization and enhances amorphous aggregation into oligomeric structures. The latter helps explain why Aβ(1-42) assembles into more complex oligomers than Aβ(1-40), a consequence of which is that it is more strongly associated with Alzheimer's disease.

Effects of a disulfide bridge prior to amyloid formation of the ABRI peptide

Computational studies characterize remarkable differences between the most probable structures of the monomeric amyloidogenic peptide, ABRI, with and without a single disulfide bond; the peptide is compact and alpha-helical with the bond, otherwise it is partially extended with slight β-bridges and an exposed hydrophobic surface area.

Effects of environmental factors on MSP21-25 aggregation indicate the roles of hydrophobic and electrostatic interactions in the aggregation process

Merozoite surface protein 2 (MSP2), one of the most abundant proteins on the merozoite surface of Plasmodium falciparum, is recognized to be important for the parasite's invasion into the host cell and is thus a promising malaria vaccine candidate. However, mediated mainly by its conserved N-terminal 25 residues (MSP21-25), MSP2 readily forms amyloid fibril-like aggregates under physiological conditions in vitro, which impairs its potential as a vaccine component. In addition, there is evidence that MSP2 exists in aggregated forms on the merozoite surface in vivo. To elucidate the aggregation mechanism of MSP21-25 and thereby understand the behavior of MSP2 in vivo and find ways to avoid the aggregation of relevant vaccine in vitro, we investigated the effects of agitation, pH, salts, 1-anilinonaphthalene-8-sulfonic acid (ANS), trimethylamine N-oxide dihydrate (TMAO), urea, and sub-micellar sodium dodecyl sulfate (SDS) on the aggregation kinetics of MSP21-25 using thioflavin T (ThT) fluorescence. The results showed that MSP21-25 aggregation was accelerated by agitation, while repressed by acidic pHs. The salts promoted the aggregation in an anion nature-dependent pattern. Hydrophobic surface-binding agent ANS and detergent urea repressed MSP21-25 aggregation, in contrast to hydrophobic interaction strengthener TMAO, which enhanced the aggregation. Notably, sub-micellar SDS, contrary to its micellar form, promoted MSP21-25 aggregation significantly. Our data indicated that hydrophobic interactions are the predominant driving force of the nucleation of MSP21-25 aggregation, while the elongation is controlled mainly by electrostatic interactions. A kinetic model of MSP21-25 aggregation and its implication were also discussed.

Interplay between folding and assembly of fibril-forming polypeptides

Polypeptides can self-assemble into hierarchically organized fibrils consisting of a stack of individually folded polypeptides driven together by hydrophobic interaction. Using a coarse-grained model, we systematically studied this self-assembly as a function of temperature and hydrophobicity of the residues on the outside of the building block. We find the self-assembly can occur via two different pathways-a random aggregation-folding route and a templated-folding process-thus indicating a strong coupling between folding and assembly. The simulation results can explain experimental evidence that assembly through stacking of folded building blocks is rarely observed, at the experimental concentrations. The model thus provides a generic picture of hierarchical fibril formation.

Thinking laterally about neurodegenerative proteinopathies

Many neurodegenerative disorders, including Alzheimer's disease, Parkinson's disease, Huntington's disease, and frontotemporal dementia, are proteinopathies that are associated with the aggregation and accumulation of misfolded proteins. While remarkable progress has been made in understanding the triggers of these conditions, several challenges have hampered the translation of preclinical therapies targeting pathways downstream of the initiating proteinopathies. Clinical trials in symptomatic patients using therapies directed toward initiating trigger events have met with little success, prompting concerns that such therapeutics may be of limited efficacy when used in advanced stages of the disease rather than as prophylactics. Herein, we discuss gaps in our understanding of the pathological processes downstream of the trigger and potential strategies to identify common features of the downstream degenerative cascade in multiple CNS proteinopathies, which could potentially lead to the development of common therapeutic targets for multiple disorders.

Aggregate geometry in amyloid fibril nucleation

We present and study a minimal structure-based model for the self-assembly of peptides into ordered β-sheet-rich fibrils. The peptides are represented by unit-length sticks on a cubic lattice and interact by hydrogen bonding and hydrophobicity forces. Using Monte Carlo simulations with >10(5) peptides, we show that fibril formation occurs with sigmoidal kinetics in the model. To determine the mechanism of fibril nucleation, we compute the joint distribution in length and width of the aggregates at equilibrium, using an efficient cluster move and flat-histogram techniques. This analysis, based on simulations with 256 peptides in which aggregates form and dissolve reversibly, shows that the main free-energy barriers that a nascent fibril has to overcome are associated with changes in width.

Kinetics of amyloid aggregation: a study of the GNNQQNY prion sequence

The small amyloid-forming GNNQQNY fragment of the prion sequence has been the subject of extensive experimental and numerical studies over the last few years. Using unbiased molecular dynamics with the OPEP coarse-grained potential, we focus here on the onset of aggregation in a 20-mer system. With a total of 16.9 of simulations at 280 K and 300 K, we show that the GNNQQNY aggregation follows the classical nucleation theory (CNT) in that the number of monomers in the aggregate is a very reliable descriptor of aggregation. We find that the critical nucleus size in this finite-size system is between 4 and 5 monomers at 280 K and 5 and 6 at 300 K, in overall agreement with experiment. The kinetics of growth cannot be fully accounted for by the CNT, however. For example, we observe considerable rearrangements after the nucleus is formed, as the system attempts to optimize its organization. We also clearly identify two large families of structures that are selected at the onset of aggregation demonstrating the presence of well-defined polymorphism, a signature of amyloid growth, already in the 20-mer aggregate.

Protein aggregation plays an important pathological role in numerous neurodegenerative diseases such as Alzheimer's, Parkinson's, Creutzfeldt-Jakob, the Prion disease and diabetes mellitus. In most cases, misfolded proteins are involved and aggregate irreversibly to form highly ordered insoluble macrostructures, called amyloid fibrils, which deposit in the brain. Studies have revealed that all proteins are capable of forming amyloid fibrils that all share common structural features and therefore aggregation mechanisms. The toxicity of amyloid aggregates is however not attributed to the fibrils themselves but rather to smaller more disordered aggregates, oligomers, forming parallel to or prior to fibrils. Understanding the assembly process of these amyloid oligomers is key to understanding their toxicity mechanism in order to devise a possible treatment strategy targeting these toxic aggregates. Our approach here is to computationally study the aggregation dynamics of a 20-mer of an amyloid peptide GNNQQNY from a prion protein. Our findings suggest that the assembly is a spontaneous process that can be described as a complex nucleation and growth mechanism and which can lead to two classes of morphologies for the aggregates, one of which resembles a protofibril-like structure. Such numerical studies are crucial to understanding the details of fast biological processes and complement well experimental studies.

Length distribution of stiff, self-assembled polymers at thermal equilibrium

We investigate the length distribution of self-assembled, long and stiff polymers at thermal equilibrium. Our analysis is based on calculating the partition functions of stiff polymers of variable lengths in the elastic regime. Our conclusion is that the length distribution of this self-assembled system follows closely the exponential distribution, except at the short length limit. We then discuss the implications of our results on the experimentally observed length distributions in amyloid fibrils.

Influence of temperature on formation of perfect tau fragment fibrils using PRIME20/DMD simulations

We investigate the fibrillization process for amyloid tau fragment peptides (VQIVYK) by applying the discontinuous molecular dynamics method to a system of 48 VQIVYK peptides modeled using a new protein model/force field, PRIME20. The aim of the article is to ascertain which factors are most important in determining whether or not a peptide system forms perfect coherent fibrillar structures. Two different directional criteria are used to determine when a hydrogen bond occurs: the original H-bond constraints and a parallel preference H-bond constraint that imparts a slight bias towards the formation of parallel versus antiparallel strands in a β-sheet. Under the original H-bond constraints, the resulting fibrillar structures contain a mixture of parallel and antiparallel pairs of strands within each β-sheet over the whole fibrillization temperature range. Under the parallel preference H-bond constraints, the β-sheets within the fibrillar structures are more likely to be parallel and indeed become perfectly parallel, consistent with X-ray crystallography, at a high temperature slightly below the fibrillization temperature. The high temperature environment encourages the formation of perfect fibril structures by providing enough time and space for peptides to rearrange during the aggregation process. There are two different kinetic mechanisms, template assembly with monomer addition at high temperature and merging/rearrangement without monomer addition at low temperature, which lead to significant differences in the final fibrillar structure. This suggests that the diverse fibril morphologies generally observed in vitro depend more on environmental conditions than has heretofore been appreciated.

Nanomaterials design and tests for neural tissue engineering

Nanostructured scaffolds recently showed great promise in tissue engineering: nanomaterials can be tailored at the molecular level and scaffold morphology may more closely resemble features of extracellular matrix components in terms of porosity, framing and biofunctionalities. As a consequence, both biomechanical properties of scaffold microenvironments and biomaterial-protein interactions can be tuned, allowing for improved transplanted cell engraftment and better controlled diffusion of drugs. Easier said than done, a nanotech-based regenerative approach encompasses different fields of know-how, ranging from in silico simulations, nanomaterial synthesis and characterization at the nano-, micro- and mesoscales to random library screening methods (e.g. phage display), in vitro cellular-based experiments and validation in animal models of the target injury. All of these steps of the "assembly line" of nanostructured scaffolds are tightly interconnected both in their standard analysis techniques and in their most recent breakthroughs: indeed their efforts have to jointly provide the deepest possible analyses of the diverse facets of the challenging field of neural tissue engineering. The purpose of this review is therefore to provide a critical overview of the recent advances in and drawbacks and potential of each mentioned field, contributing to the realization of effective nanotech-based therapies for the regeneration of peripheral nerve transections, spinal cord injuries and brain traumatic injuries. Far from being the ultimate overview of such a number of topics, the reader will acknowledge the intrinsic complexity of the goal of nanotech tissue engineering for a conscious approach to the development of a regenerative therapy and, by deciphering the thread connecting all steps of the research, will gain the necessary view of its tremendous potential if each piece of stone is correctly placed to work synergically in this impressive mosaic.

Template induced conformational change of amyloid-β monomer

Population of aggregation-prone conformers for the monomeric amyloid-β (Aβ) can dramatically speed up its fibrillar aggregation. In this work, we study the effect of preformed template on the conformational distributions of the monomeric Aβ by replica exchange molecular dynamics. Our results show that the template consisting of Aβ peptides with cross-β structure can induce the formation of β-rich conformations for the monomeric Aβ, which is the key feature of the aggregation-prone conformers. Similar effect is observed when the hIAPP peptides and poly alanine peptides were used as templates, suggesting that the template effect is insensitive to the sequence details of the template peptides. In comparison, the template with helical structure has no significant effects on the β-propensity of the monomeric Aβ. Analysis to the interaction details revealed that the template tends to disrupt the intrapeptide interactions of the monomeric Aβ, which are absent in the fibrillar state, suggesting that the preformed template can reorganize the intrapeptide interactions of the monomeric Aβ during the capturing stage and reduce the energy frustrations for the fibrillar aggregations.

Protein aggregation: mechanisms and functional consequences

Understanding the mechanisms underlying protein misfolding and aggregation has become a central issue in biology and medicine. Compelling evidence show that the formation of amyloid aggregates has a negative impact in cell function and is behind the most prevalent human degenerative disorders, including Alzheimer's Parkinson's and Huntington's diseases or type 2 diabetes. Surprisingly, the same type of macromolecular assembly is used for specialized functions by different organisms, from bacteria to human. Here we address the conformational properties of these aggregates, their formation pathways, their role in human diseases, their functional properties and how bioinformatics tools might be of help to study these protein assemblies.

Chemical crosslinking and mass spectrometric identification of interaction sites within soluble aggregate of protein therapeutics

Protein aggregation presents a major challenge to bioengineering. In the present study, chemical crosslinking and mass spectrometry are employed to probe the interaction amongst soluble oligomer formed by Fc molecule of monoclonal antibody. Aggregation was induced by thermal stress at 42°C for 6h under physiological pH. Contacting residues on adjacent molecules were captured with bifunctional crosslinker BS3, followed by mass spectrometric identification of the crosslinked sites. The approach provides site-specific information regarding the binding interface that would have broad application in the field.