Modelling amyloid fibril formation kinetics: mechanisms of nucleation and growth

Secondary Nucleation of Aβ Revealed by Single-Molecule and Computational Approaches

Understanding the mechanisms underlying amyloid-β (Aβ) aggregation is pivotal in the context of Alzheimer's disease. This study aims to elucidate the secondary nucleation process of Aβ42 peptides by combining experimental and computational methods. Using a newly developed nanopipette-based amyloid seeding and translocation assay, confocal fluorescence spectroscopy, and molecular dynamics simulations, the influence of the seed properties on Aβ aggregation is investigated. Both fragmented and unfragmented seeds played distinct roles in the formation of oligomers, with fragmented seeds facilitating the formation of larger aggregates early in the incubation phase. The results show that secondary nucleation leads to the formation of oligomers of various sizes and structures as well as larger fibrils structured in β-sheets. From these findings a mechanism of secondary nucleation involving two types of aggregate populations, one released and one growing on the mother fiber is proposed.

Implantable Patch of Oxidized Nanofibrillated Cellulose and Lysozyme Amyloid Nanofibrils for the Regeneration of Infarcted Myocardium Tissue and Local Delivery of RNA-Loaded Nanoparticles

Biopolymeric implantable patches are popular scaffolds for myocardial regeneration applications. Besides being biocompatible, they can be tailored to have required properties and functionalities for this application. Recently, fibrillar biobased nanostructures prove to be valuable in the development of functional biomaterials for tissue regeneration applications. Here, periodate-oxidized nanofibrillated cellulose (OxNFC) is blended with lysozyme amyloid nanofibrils (LNFs) to prepare a self-crosslinkable patch for myocardial implantation. The OxNFC:LNFs patch shows superior wet mechanical properties (60 MPa for Young's modulus and 1.5 MPa for tensile stress at tensile strength), antioxidant activity (70% scavenging activity under 24 h), and bioresorbability ratio (80% under 91 days), when compared to the patches composed solely of NFC or OxNFC. These improvements are achieved while preserving the morphology, required thermal stability for sterilization, and biocompatibility toward rat cardiomyoblast cells. Additionally, both OxNFC and OxNFC:LNFs patches reveal the ability to act as efficient vehicles to deliver spermine modified acetalated dextran nanoparticles, loaded with small interfering RNA, with 80% of delivery after 5 days. This study highlights the value of simply blending OxNFC and LNFs, synergistically combining their key properties and functionalities, resulting in a biopolymeric patch that comprises valuable characteristics for myocardial regeneration applications.

Stability of Protein Pharmaceuticals: Recent Advances

There have been significant advances in the formulation and stabilization of proteins in the liquid state over the past years since our previous review. Our mechanistic understanding of protein-excipient interactions has increased, allowing one to develop formulations in a more rational fashion. The field has moved towards more complex and challenging formulations, such as high concentration formulations to allow for subcutaneous administration and co-formulation. While much of the published work has focused on mAbs, the principles appear to apply to any therapeutic protein, although mAbs clearly have some distinctive features. In this review, we first discuss chemical degradation reactions. This is followed by a section on physical instability issues. Then, more specific topics are addressed: instability induced by interactions with interfaces, predictive methods for physical stability and interplay between chemical and physical instability. The final parts are devoted to discussions how all the above impacts (co-)formulation strategies, in particular for high protein concentration solutions.'

Variance and higher moments in the sigmoidal self-assembly of branched fibrils

Self-assembly of functional branched filaments, such as actin filaments and microtubules, or dysfunctional ones, such as amyloid fibrils, plays important roles in many biological processes. Here, based on the master equation approach, we study the kinetics of the formation of the branched fibrils. In our model, a branched fibril has one mother branch and several daughter branches. A daughter branch grows from the side of a pre-existing mother branch or daughter branch. In our model, we consider five basic processes for the self-assembly of the branched filaments, namely, the nucleation, the dissociation of the primary nucleus of fibrils, the elongation, the fragmentation, and the branching. The elongation of a mother branch from two ends and the elongation of a daughter branch from two ends can, in principle, occur with four different rate constants associated with the corresponding tips. This leads to a pronounced impact of the directionality of growth on the kinetics of the self-assembly. Here, we have unified and generalized our four previously presented models of branched fibrillogenesis in a single model. We have obtained a system of non-linear ordinary differential equations that give the time evolution of the polymer numbers and the mass concentrations along with the higher moments as observable quantities.

Molecular Insights into the Dynamics of Amyloid Fibril Growth: Elongation and Lateral Assembly of GNNQQNY Protofibrils

The self-assembly of peptides and proteins into β-sheet rich amyloid fibrils is linked to both functional and pathological states. In this study, the growth of fibrillar structures of the short peptide GNNQQNY, a fragment from the yeast prion Sup35 protein, was examined. Molecular dynamics simulations were used to study alternative mechanisms of fibril growth, including elongation through binding of monomers as well as fibril self-assembly into larger, more mature structures. It was found that after binding, monomers diffused along preformed fibrils toward the ends, supporting the mechanism of fibril growth via elongation. Lateral assembly of protofibrils was found to occur readily, suggesting that this could be the key to transitioning from isolated fibrils to mature multilayer structures. Overall, the work provides mechanistic insights into the competitive pathways that govern amyloid fibril growth.

Exploration of Resveratrol as a Potent Modulator of α-Synuclein Fibril Formation

The molecular determinants of amyloid protein misfolding and aggregation are key for the development of therapeutic interventions in neurodegenerative disease. Although small synthetic molecules, bifunctional molecules, and natural products offer a potentially advantageous approach to therapeutics to remodel aggregation, their evaluation requires new platforms that are informed at the molecular level. To that end, we chose pulsed hydrogen/deuterium exchange mass spectrometry (HDX-MS) to discern the phenomena of aggregation modulation for a model system of alpha synuclein (αS) and resveratrol, an antiamyloid compound. We invoked, as a complement to HDX, advanced kinetic modeling described here to illuminate the details of aggregation and to determine the number of oligomeric populations by kinetically fitting the experimental data under conditions of limited proteolysis. The misfolding of αS is most evident within and nearby the nonamyloid-β component region, and resveratrol significantly remodels that aggregation. HDX distinguishes readily a less solvent-accessible, more structured oligomer that coexists with a solvent-accessible, more disordered oligomer during aggregation. A view of the misfolding emerges from time-dependent changes in the fractional species across the protein with or without resveratrol, while details were determined through kinetic modeling of the protected species. A detailed picture of the inhibitory action of resveratrol with time and regional specificity emerges, a picture that can be obtained for other inhibitors and amyloid proteins. Moreover, the model reveals that new states of aggregation are sampled, providing new insights on amyloid formation. The findings were corroborated by circular dichroism and transmission electron microscopy.

How Can We Use Mathematical Modeling of Amyloid-β in Alzheimer's Disease Research and Clinical Practices?

The accumulation of amyloid-β (Aβ) plaques in the brain is considered a hallmark of Alzheimer's disease (AD). Mathematical modeling, capable of predicting the motion and accumulation of Aβ, has obtained increasing interest as a potential alternative to aid the diagnosis of AD and predict disease prognosis. These mathematical models have provided insights into the pathogenesis and progression of AD that are difficult to obtain through experimental studies alone. Mathematical modeling can also simulate the effects of therapeutics on brain Aβ levels, thereby holding potential for drug efficacy simulation and the optimization of personalized treatment approaches. In this review, we provide an overview of the mathematical models that have been used to simulate brain levels of Aβ (oligomers, protofibrils, and/or plaques). We classify the models into five categories: the general ordinary differential equation models, the general partial differential equation models, the network models, the linear optimal ordinary differential equation models, and the modified partial differential equation models (i.e., Smoluchowski equation models). The assumptions, advantages and limitations of these models are discussed. Given the popularity of using the Smoluchowski equation models to simulate brain levels of Aβ, our review summarizes the history and major advancements in these models (e.g., their application to predict the onset of AD and their combined use with network models). This review is intended to bring mathematical modeling to the attention of more scientists and clinical researchers working on AD to promote cross-disciplinary research.

Development of Small Molecules Targeting α-Synuclein Aggregation: A Promising Strategy to Treat Parkinson's Disease

Parkinson's disease, the second most common neurodegenerative disorder worldwide, is characterized by the accumulation of protein deposits in the dopaminergic neurons. These deposits are primarily composed of aggregated forms of α-Synuclein (α-Syn). Despite the extensive research on this disease, only symptomatic treatments are currently available. However, in recent years, several compounds, mainly of an aromatic character, targeting α-Syn self-assembly and amyloid formation have been identified. These compounds, discovered by different approaches, are chemically diverse and exhibit a plethora of mechanisms of action. This work aims to provide a historical overview of the physiopathology and molecular aspects associated with Parkinson's disease and the current trends in small compound development to target α-Syn aggregation. Although these molecules are still under development, they constitute an important step toward discovering effective anti-aggregational therapies for Parkinson's disease.

Perphenazine-Macrocycle Conjugates Rapidly Sequester the Aβ42 Monomer and Prevent Formation of Toxic Oligomers and Amyloid

Alzheimer's disease is imposing a growing social and economic burden worldwide, and effective therapies are urgently required. One possible approach to modulation of the disease outcome is to use small molecules to limit the conversion of monomeric amyloid (Aβ42) to cytotoxic amyloid oligomers and fibrils. We have synthesized modulators of amyloid assembly that are unlike others studied to date: these compounds act primarily by sequestering the Aβ42 monomer. We provide kinetic and nuclear magnetic resonance data showing that these perphenazine conjugates divert the Aβ42 monomer into amorphous aggregates that are not cytotoxic. Rapid monomer sequestration by the compounds reduces fibril assembly, even in the presence of pre-formed fibrillar seeds. The compounds are therefore also able to disrupt monomer-dependent secondary nucleation, the autocatalytic process that generates the majority of toxic oligomers. The inhibitors have a modular design that is easily varied, aiding future exploration and use of these tools to probe the impact of distinct Aβ42 species populated during amyloid assembly.

Evolution of π-Peptide Self-Assembly: From Understanding to Prediction and Control

Supramolecular materials derived from the self-assembly of engineered molecules continue to garner tremendous scientific and technological interest. Recent innovations include the realization of nano- and mesoscale particles (0D), rods and fibrils (1D), sheets (2D), and even extended lattices (3D). Our research groups have focused attention over the past 15 years on one particular class of supramolecular materials derived from oligopeptides with embedded π-electron units, where the oligopeptides can be viewed as substituents or side chains to direct the assembly of the central π-electron cores. Upon assembly, the π-systems are driven into close cofacial architectures that facilitate a variety of energy migration processes within the nanomaterial volume, including exciton transport, voltage transmission, and photoinduced electron transfer. Like many practitioners of supramolecular materials science, many of our initial molecular designs were designed with substantial inspiration from biologically occurring self-assembly coupled with input from chemical intuition and molecular modeling and simulation. In this feature article, we summarize our current understanding of the π-peptide self-assembly process as documented through our body of publications in this area. We address fundamental spectroscopic and computational tools used to extract information regarding the internal structures and energetics of the π-peptide assemblies, and we address the current state of the art in terms of recent applications of data science tools in conjunction with high-throughput computational screening and experimental assays to guide the efficient traversal of the π-peptide molecular design space. The abstract image details our integrated program of chemical synthesis, spectroscopic and functional characterization, multiscale simulation, and machine learning which has advanced the understanding and control of the assembly of synthetic π-conjugated peptides into supramolecular nanostructures with energy and biomedical applications.

Amyloidogenesis: What Do We Know So Far?

The study of protein aggregation, and amyloidosis in particular, has gained considerable interest in recent times. Several neurodegenerative diseases, such as Alzheimer's (AD) and Parkinson's (PD) show a characteristic buildup of proteinaceous aggregates in several organs, especially the brain. Despite the enormous upsurge in research articles in this arena, it would not be incorrect to say that we still lack a crystal-clear idea surrounding these notorious aggregates. In this review, we attempt to present a holistic picture on protein aggregation and amyloids in particular. Using a chronological order of discoveries, we present the case of amyloids right from the onset of their discovery, various biophysical techniques, including analysis of the structure, the mechanisms and kinetics of the formation of amyloids. We have discussed important questions on whether aggregation and amyloidosis are restricted to a subset of specific proteins or more broadly influenced by the biophysiochemical and cellular environment. The therapeutic strategies and the significant failure rate of drugs in clinical trials pertaining to these neurodegenerative diseases have been also discussed at length. At a time when the COVID-19 pandemic has hit the globe hard, the review also discusses the plausibility of the far-reaching consequences posed by the virus, such as triggering early onset of amyloidosis. Finally, the application(s) of amyloids as useful biomaterials has also been discussed briefly in this review.

The effect of mechanical shocks on the initial aggregation behavior of yeast prion protein Sup35NM

To study the effect of mechanical shocks on the neurodegenerative-related fibril-formation protein, the aggregation process, especially the initial oligomerization of a model yeast prion protein Sup35NM, was followed and analyzed by using a combination of laser light scattering, the Smoluchowski coagulation analysis, Thioflavin T fluorescence assay, and transmission electron microscopy. We find that an initial short-time mechanical shock (ultrasonication or circular shaking) affects the in vitro association kinetics of neurodegenerative-related Sup35NM proteins in dilute PBS solutions by generating a relatively larger number of smaller non-structured oligomers that further serve as tiny "crystallization" seeds in promoting the formation of longer fibrils. Our study provides an effective and quantitative method to investigate the initial oligomerization kinetics of amyloid fibrils formation. Furthermore, the current results may shed light on the molecular understanding on how environmental factors increase the risk of neurodegenerative diseases such as dementia.

Structural basis for the mechanisms of human presequence protease conformational switch and substrate recognition

Presequence protease (PreP), a 117 kDa mitochondrial M16C metalloprotease vital for mitochondrial proteostasis, degrades presequence peptides cleaved off from nuclear-encoded proteins and other aggregation-prone peptides, such as amyloid β (Aβ). PreP structures have only been determined in a closed conformation; thus, the mechanisms of substrate binding and selectivity remain elusive. Here, we leverage advanced vitrification techniques to overcome the preferential denaturation of one of two ~55 kDa homologous domains of PreP caused by air-water interface adsorption. Thereby, we elucidate cryoEM structures of three apo-PreP open states along with Aβ- and citrate synthase presequence-bound PreP at 3.3–4.6 Å resolution. Together with integrative biophysical and pharmacological approaches, these structures reveal the key stages of the PreP catalytic cycle and how the binding of substrates or PreP inhibitor drives a rigid body motion of the protein for substrate binding and catalysis. Together, our studies provide key mechanistic insights into M16C metalloproteases for future therapeutic innovations.

Presequence protease (PreP) is essential to mitochondrial proteostasis. This study leverages advanced vitrification techniques to solve cryoEM structures of apo- and substrate-bound PreP and integrates these data with other analysis to reveal key stages and mechanistic insights of the PreP catalytic cycle.

Inhibiting mTTR Aggregation/Fibrillation by a Chaperone-like Hydrophobic Amino Acid-Conjugated SPION

Transthyretin (TTR) aggregation via misfolding of a mutant or wild-type protein leads to systemic or partial amyloidosis (ATTR). Here, we utilized variable biophysical assays to characterize two distinct aggregation pathways for mTTR (a synthesized monomer TTR incapable of association into a tetramer) at pH 4.3 and also pH 7.4 with agitation, referred to as mTTR aggregation and fibrillation, respectively. The findings suggest that early-stage conformational changes termed monomer activation here determine the aggregation pathway, resulting in developing either amorphous aggregates or well-organized fibrils. Less packed partially unfolded monomers consisting of more non-regular secondary structures that were rapidly produced via a mildly acidic condition form amorphous aggregates. Meanwhile, more hydrophobic and packed monomers consisting of rearranged β sheets and increased helical content developed well-organized fibrils. Conjugating superparamagnetic iron oxide nanoparticles (SPIONs) with leucine and glutamine (L-SPIONs and G-SPIONs in order) via a trimethoxysilane linker provided the chance to study the effect of hydrophobic/hydrophilic surfaces on mTTR aggregation. The results indicated a powerful inhibitory effect of hydrophobic L-SPIONs on both mTTR aggregation and fibrillation. Monomer depletion was introduced as the governing mechanism for inhibiting mTTR aggregation, while a chaperone-like property of L-SPIONs by maintaining an mTTR native structure and adsorbing oligomers suppressed the progression of further fibril formation.

Modeling and Designing Particle-Regulated Amyloid-like Assembly of Synthetic Polypeptides in Aqueous Solution

In cells, actin and tubulin polymerization is regulated by nucleation factors, which promote the nucleation and subsequent growth of protein filaments in a controlled manner. Mimicking this natural mechanism to control the supramolecular polymerization of macromolecular monomers by artificially created nucleation factors remains a largely unmet challenge. Biological nucleation factors act as molecular scaffolds to boost the local concentrations of protein monomers and facilitate the required conformational changes to accelerate the nucleation and subsequent polymerization. An accelerated assembly of synthetic poly(l-glutamic acid) into amyloid fibrils catalyzed by cationic silica nanoparticle clusters (NPCs) as artificial nucleation factors is demonstrated here and modeled as supramolecular polymerization with a surface-induced heterogeneous nucleation pathway. Kinetic studies of fibril growth coupled with mechanistic analysis demonstrate that the artificial nucleators predictably accelerate the supramolecular polymerization process by orders of magnitude (e.g., shortening the assembly time by more than 10 times) when compared to the uncatalyzed reaction, under otherwise identical conditions. Amyloid-like fibrillation was supported by a variety of standard characterization methods. Nucleation followed a Michaelis-Menten-like scheme for the cationic silica NPCs, while the corresponding anionic or neutral nanoparticles had no effect on fibrillation. This approach shows the effectiveness of charge-charge interactions and surface functionalities in facilitating the conformational change of macromolecular monomers and controlling the rates of nucleation for fibril growth. Molecular design approaches like these inspire the development of novel materials via biomimetic supramolecular polymerizations.

A generic approach to decipher the mechanistic pathway of heterogeneous protein aggregation kinetics

Amyloid formation is a generic property of many protein/polypeptide chains. A broad spectrum of proteins, despite having diversity in the inherent precursor sequence and heterogeneity present in the mechanism of aggregation produces a common cross β-spine structure that is often associated with several human diseases. However, a general modeling framework to interpret amyloid formation remains elusive. Herein, we propose a data-driven mathematical modeling approach that elucidates the most probable interaction network for the aggregation of a group of proteins (α-synuclein, Aβ42, Myb, and TTR proteins) by considering an ensemble set of network models, which include most of the mechanistic complexities and heterogeneities related to amyloidogenesis. The best-fitting model efficiently quantifies various timescales involved in the process of amyloidogenesis and explains the mechanistic basis of the monomer concentration dependency of amyloid-forming kinetics. Moreover, the present model reconciles several mutant studies and inhibitor experiments for the respective proteins, making experimentally feasible non-intuitive predictions, and provides further insights about how to fine-tune the various microscopic events related to amyloid formation kinetics. This might have an application to formulate better therapeutic measures in the future to counter unwanted amyloidogenesis. Importantly, the theoretical method used here is quite general and can be extended for any amyloid-forming protein.

The curvature of gold nanoparticles influences the exposure of amyloid-β and modulates its aggregation process

Gold nanoparticles (GNP) are tunable nanomaterials that can be used to develop rational therapeutic inhibitors against the formation of pathological aggregates of proteins. In the case of the pathological aggregation of the amyloid-β protein (Aβ), the shape of the GNP can slow down or accelerate its aggregation kinetics. However, there is a lack of elementary knowledge about how the curvature of GNP alters the interaction with the Aβ peptide and how this interaction modifies key molecular steps of fibril formation. In this study, we analysed the effect of flat gold nanoprisms (GNPr) and curved gold nanospheres (GNS) on in vitro Aβ42 fibril formation kinetics by using the thioflavin-based kinetic assay and global fitting analysis, with several models of aggregation. Whereas GNPr accelerate the aggregation process and maintain the molecular mechanism of aggregation, GNS slow down this process and modify the molecular mechanism to one of fragmentation/secondary nucleation, with respect to controls. These results can be explained by a differential interaction between the Aβ peptide and GNP observed by Raman spectroscopy. While flat GNPr expose key hydrophobic residues involved in the Aβ peptide aggregation, curved GNS hide these residues from the solvent. Thus, this study provides mechanistic insights to improve the rational design of GNP nanomaterials for biomedical applications in the field of amyloid-related aggregation.

Kinetics theories to understand the mechanism of aggregation of a protein and to design strategies for its inhibition

Protein aggregation phenomenon is closely related to the formation of amyloids which results in many neurodegenerative diseases like Alzheimer's, Parkinson's, Huntington's, and Amyotrophic Lateral Sclerosis. In order to prevent and treat these diseases, a clear understanding of the mechanism of misfolding and self-assembly of peptides and proteins is very crucial. The aggregation of a protein may involve various microscopic events. Multiple simulations utilizing the solutions of the master equation have given a better understanding of the kinetic profiles involved in the presence and absence of a particular microscopic event. This review focuses on understanding the contribution of these molecular events to protein aggregation based on the analysis of kinetic profiles of aggregation. We also discuss the effect of inhibitors, which target various species of aggregation pathways, on the kinetic profile of protein aggregation. At the end of this review, some strategies for the inhibition of aggregation that can be utilized by combining the chemical kinetics approach with thermodynamics are proposed.

The intrinsic amyloidogenic propensity of cofilin-1 is aggravated by Cys-80 oxidation: A possible link with neurodegenerative diseases

Cofilin-1, an actin dynamizing protein, forms actin-cofilin rods, which is one of the major events that exacerbates the pathophysiology of amyloidogenic diseases. Cysteine oxidation in cofilin-1 under oxidative stress plays a crucial role in the formation of these rods. Others and we have reported that cofilin-1 possesses a self-oligomerization property in vitro and in vivo under physiological conditions. However, it remains elusive if cofilin-1 itself forms amyloid-like structures. We, therefore, hypothesized that cofilin-1 might form amyloid-like assemblies, with a potential to intensify the pathophysiology of amyloid-linked diseases. We used various in silico and in vitro techniques and examined the amyloid-forming propensity of cofilin-1. The study confirms that cofilin-1 possesses an intrinsic tendency of aggregation and forms amyloid-like structures in vitro. Further, we studied the effect of cysteine oxidation on the stability and structural features of cofilin-1. Our data show that oxidation at Cys-80 renders cofilin-1 unstable, leading to a partial loss of protein structure. The results substantiate our hypothesis and establish a strong possibility that cofilin-1 aggregation might play a role in cofilin-mediated pathology and the progression of several amyloid-linked diseases.

Stochastic Kinetic Treatment of Protein Aggregation and the Effects of Macromolecular Crowding

Investigation of protein self-assembly processes is important for understanding the growth processes of functional proteins as well as disease-causing amyloids. Inside cells, intrinsic molecular fluctuations are so high that they cast doubt on the validity of the deterministic rate-equation approach. Furthermore, the protein environments inside cells are often crowded with other macromolecules, with volume fractions of the crowders as high as 40%. We have developed a stochastic kinetic framework using Gillespie's algorithm for general systems undergoing particle self-assembly, including particularly protein aggregation at the cellular level. The effects of macromolecular crowding are investigated using models built on scaled-particle and transition-state theories. The stochastic kinetic method can be formulated to provide information on the dominating aggregation mechanisms in a method called reaction frequency (or propensity) analysis. This method reveals that the change of scaling laws related to the lag time can be directly related to the change in the frequencies of reaction mechanisms. Further examination of the time evolution of the fibril mass and length quantities unveils that maximal fluctuations occur in the periods of rapid fibril growth and the fluctuations of both quantities can be sensitive functions of rate constants. The presence of crowders often amplifies the roles of primary and secondary nucleation and causes shifting in the relative importance of elongation, shrinking, fragmentation, and coagulation of linear aggregates. We also show a dual effect of changing volume on the halftime of aggregation for ApoC2 which is reduced in the presence of crowders. A comparison of the results of stochastic simulations with those of rate equations gives us information on the convergence relation between them and how the roles of reaction mechanisms change as the system volume is varied.

Graph Models of Pathology Spread in Alzheimer's Disease: An Alternative to Conventional Graph Theoretic Analysis

Background: Graph theory and connectomics are new techniques for uncovering disease-induced changes in the brain's structural network. Most prior studied have focused on network statistics as biomarkers of disease. However, an emerging body of work involves exploring how the network serves as a conduit for the propagation of disease factors in the brain and has successfully mapped the functional and pathological consequences of disease propagation. In Alzheimer's disease (AD), progressive deposition of misfolded proteins amyloid and tau is well-known to follow fiber projections, under a "prion-like" trans-neuronal transmission mechanism, through which misfolded proteins cascade along neuronal pathways, giving rise to network spread. Methods: In this review, we survey the state of the art in mathematical modeling of connectome-mediated pathology spread in AD. Then we address several open questions that are amenable to mathematically precise parsimonious modeling of pathophysiological processes, extrapolated to the whole brain. We specifically identify current formal models of how misfolded proteins are produced, aggregate, and disseminate in brain circuits, and attempt to understand how this process leads to stereotyped progression in Alzheimer's and other related diseases. Conclusion: This review serves to unify current efforts in modeling of AD progression that together have the potential to explain observed phenomena and serve as a test-bed for future hypothesis generation and testing in silico. Impact statement Graph theory is a powerful new approach that is transforming the study of brain processes. There do not exist many focused reviews of the subfield of graph modeling of how Alzheimer's and other dementias propagate within the brain network, and how these processes can be mapped mathematically. By providing timely and topical review of this subfield, we fill a critical gap in the community and present a unified view that can serve as an in silico test-bed for future hypothesis generation and testing. We also point to several open and unaddressed questions and controversies that future practitioners can tackle.

Neurodegenerative Proteinopathies in the Proteoform Spectrum-Tools and Challenges

Proteinopathy refers to a group of disorders defined by depositions of amyloids within living tissue. Neurodegenerative proteinopathies, including Alzheimer's disease, Parkinson's disease, Creutzfeldt-Jakob disease, and others, constitute a large fraction of these disorders. Amyloids are highly insoluble, ordered, stable, beta-sheet rich proteins. The emerging theory about the pathophysiology of neurodegenerative proteinopathies suggests that the primary amyloid-forming proteins, also known as the prion-like proteins, may exist as multiple proteoforms that contribute differentially towards the disease prognosis. It is therefore necessary to resolve these disorders on the level of proteoforms rather than the proteome. The transient and hydrophobic nature of amyloid-forming proteins and the minor post-translational alterations that lead to the formation of proteoforms require the use of highly sensitive and specialized techniques. Several conventional techniques, like gel electrophoresis and conventional mass spectrometry, have been modified to accommodate the proteoform theory and prion-like proteins. Several new ones, like imaging mass spectrometry, have also emerged. This review aims to discuss the proteoform theory of neurodegenerative disorders along with the utility of these proteomic techniques for the study of highly insoluble proteins and their associated proteoforms.

Directionality of growth and kinetics of branched fibril formation

The self-assembly of fibrils is a subject of intense interest, primarily due to its relevance to the formation of pathological structures. Some fibrils develop branches via the so-called secondary nucleation. In this paper, we use the master equation approach to model the kinetics of formation of branched fibrils. In our model, a branched fibril consists of one mother branch and several daughter branches. We consider five basic processes of fibril formation, namely, nucleation, elongation, branching, fragmentation, and dissociation of the primary nucleus of fibrils into free monomers. Our main focus is on the effect of the directionality of growth on the kinetics of fibril formation. We consider several cases. At first, the mother branch may elongate from one or from both ends, while the daughter branch elongates only from one end. We also study the case of branched fibrils with bidirectionally growing daughter branches, tangentially to the main stem, which resembles the intertwining process. We derive a set of ordinary differential equations for the moments of the number concentration of fibrils, which can be solved numerically. Assuming that the primary nucleus of fibrils dissociates with the fragmentation rate, in the limit of the zero branching rate, our model reproduces the results of a previous model that considers only the three basic processes of nucleation, elongation, and fragmentation. We also use the experimental parameters for the fibril formation of Huntingtin fragments to investigate the effect of unidirectional vs bidirectional elongation of the filaments on the kinetics of fibrillogenesis.

Computational Model for Studying Breakage-Dependent Amyloid Growth

Amyloid fibrils are typically associated with neurodegenerative diseases. Recent studies have suggested that, similar to prions, many amyloid proteins are infectious in nature and may cause spreading and dissemination of diseases. Typical amyloid infection propagates by recruiting functional proteins into amyloidogenic form and multiplying by breaking the existing fibril. In this study, we model the kinetics of fibril growth through breakage and the subsequent elongation process, similar to the prion infection process. Using kinetic Monte Carlo simulations as well as mathematical counting methods, we show how the measurable quantities like the 50% aggregation time (T₅₀) and the maximum growth rate (V_max) scale with various parameters in the problem. This study has a direct application where it can be used to understand experiments that amplify the minute amount of amyloid seeds present in biological fluid for early detection of human disease. Using the knowledge from our simulations, we can predict the initial seed concentration, known as the filament kinetics.

Investigating the Effects of Molecular Crowding on the Kinetics of Protein Aggregation

The thermodynamics and kinetics of protein folding and protein aggregation in vivo are of great importance in numerous scientific areas including fundamental biophysics research, nanotechnology, and medicine. However, these processes remain poorly understood in both in vivo and in vitro systems. Here we extend an established model for protein aggregation that is based on the kinetic equations for the moments of the polymer size distribution by introducing macromolecular crowding particles into the model using scaled-particle and transition-state theories. The model predicts that the presence of crowders can either speed up, cause no change to, or slow down the progress of the aggregation compared to crowder-free solutions, in striking agreement with experimental results from nine different amyloid-forming proteins that utilized dextran as the crowder. These different dynamic effects of macromolecular crowding can be understood in terms of the change of excluded volume associated with each reaction step.

Network Hamiltonian models reveal pathways to amyloid fibril formation

Amyloid fibril formation is central to the etiology of a wide range of serious human diseases, such as Alzheimer's disease and prion diseases. Despite an ever growing collection of amyloid fibril structures found in the Protein Data Bank (PDB) and numerous clinical trials, therapeutic strategies remain elusive. One contributing factor to the lack of progress on this challenging problem is incomplete understanding of the mechanisms by which these locally ordered protein aggregates self-assemble in solution. Many current models of amyloid deposition diseases posit that the most toxic species are oligomers that form either along the pathway to forming fibrils or in competition with their formation, making it even more critical to understand the kinetics of fibrillization. A recently introduced topological model for aggregation based on network Hamiltonians is capable of recapitulating the entire process of amyloid fibril formation, beginning with thousands of free monomers and ending with kinetically accessible and thermodynamically stable amyloid fibril structures. The model can be parameterized to match the five topological classes encompassing all amyloid fibril structures so far discovered in the PDB. This paper introduces a set of network statistical and topological metrics for quantitative analysis and characterization of the fibrillization mechanisms predicted by the network Hamiltonian model. The results not only provide insight into different mechanisms leading to similar fibril structures, but also offer targets for future experimental exploration into the mechanisms by which fibrils form.

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.

Caenorhabditis elegans as a model system for studying aging-associated neurodegenerative diseases

Neurodegenerative diseases (NDs) are a heterogeneous group of aging-associated disorders characterized by the disruption of cellular proteostasis machinery and the misfolding of distinct protein species to form toxic aggregates in neurons. The increasing prevalence of NDs represents a growing healthcare burden worldwide, a concern compounded by the fact that few, if any, treatments exist to target the underlying cause of these diseases. Consequently, the application of a high-throughput, physiologically relevant model system to studies dissecting the molecular mechanisms governing ND pathology is crucial for identifying novel avenues for the development of targeted therapeutics. The nematode Caenorhabditis elegans (C. elegans) has emerged as a powerful tool for the study of disease mechanisms due to its ease of genetic manipulation and swift cultivation, while providing a whole-animal system amendable to numerous molecular and biochemical techniques. To date, numerous C. elegans models have been generated for a variety of NDs, allowing for the large-scale in vivo study of protein-conformation disorders. Furthermore, the comparatively low barriers to entry in the development of transgenic worm models have facilitated the modeling of rare or "orphan" NDs, thereby providing unparalleled insight into the shared mechanisms underlying these pathologies. In this review, we summarize findings from a comprehensive collection of C. elegans neurodegenerative disease models of varying prevalence to emphasize shared mechanisms of proteotoxicity, and highlight the utility of these models in elucidating the molecular basis of ND pathologies.

Structural Influence and Interactive Binding Behavior of Dopamine and Norepinephrine on the Greek-Key-Like Core of α-Synuclein Protofibril Revealed by Molecular Dynamics Simulations

The pathogenesis of Parkinson’s disease (PD) is closely associated with the aggregation of α-synuclein (αS) protein. Finding the effective inhibitors of αS aggregation has been considered as the primary therapeutic strategy for PD. Recent studies reported that two neurotransmitters, dopamine (DA) and norepinephrine (NE), can effectively inhibit αS aggregation and disrupt the preformed αS fibrils. However, the atomistic details of αS-DA/NE interaction remain unclear. Here, using molecular dynamics simulations, we investigated the binding behavior of DA/NE molecules and their structural influence on αS44–96 (Greek-key-like core of full length αS) protofibrillar tetramer. Our results showed that DA/NE molecules destabilize αS protofibrillar tetramer by disrupting the β-sheet structure and destroying the intra- and inter-peptide E46–K80 salt bridges, and they can also destroy the inter-chain backbone hydrogen bonds. Three binding sites were identified for both DA and NE molecules interacting with αS tetramer: T54–T72, Q79–A85, and F94–K96, and NE molecules had a stronger binding capacity to these sites than DA. The binding of DA/NE molecules to αS tetramer is dominantly driven by electrostatic and hydrogen bonding interactions. Through aromatic π-stacking, DA and NE molecules can bind to αS protofibril interactively. Our work reveals the detailed disruptive mechanism of protofibrillar αS oligomer by DA/NE molecules, which is helpful for the development of drug candidates against PD. Given that exercise as a stressor can stimulate DA/NE secretion and elevated levels of DA/NE could delay the progress of PD, this work also enhances our understanding of the biological mechanism by which exercise prevents and alleviates PD.

Recent advances in the design and applications of amyloid-β peptide aggregation inhibitors for Alzheimer's disease therapy

Alzheimer's disease (AD) is an irreversible neurological disorder that progresses gradually and can cause severe cognitive and behavioral impairments. This disease is currently considered a social and economic incurable issue due to its complicated and multifactorial characteristics. Despite decades of extensive research, we still lack definitive AD diagnostic and effective therapeutic tools. Consequently, one of the most challenging subjects in modern medicine is the need for the development of new strategies for the treatment of AD. A large body of evidence indicates that amyloid-β (Aβ) peptide fibrillation plays a key role in the onset and progression of AD. Recent studies have reported that amyloid hypothesis-based treatments can be developed as a new approach to overcome the limitations and challenges associated with conventional AD therapeutics. In this review, we will provide a comprehensive view of the challenges in AD therapy and pathophysiology. We also discuss currently known compounds that can inhibit amyloid-β (Aβ) aggregation and their potential role in advancing current AD treatments. We have specifically focused on Aβ aggregation inhibitors including metal chelators, nanostructures, organic molecules, peptides (or peptide mimics), and antibodies. To date, these molecules have been the subject of numerous in vitro and in vivo assays as well as molecular dynamics simulations to explore their mechanism of action and the fundamental structural groups involved in Aβ aggregation. Ultimately, the aim of these studies (and current review) is to achieve a rational design for effective therapeutic agents for AD treatment and diagnostics.

Single-Molecular Heteroamyloidosis of Human Islet Amyloid Polypeptide

Human amyloids and plaques uncovered post mortem are highly heterogeneous in structure and composition, yet literature concerning the heteroaggregation of amyloid proteins is extremely scarce. This knowledge deficiency is further exacerbated by the fact that peptide delivery is a major therapeutic strategy for targeting their full-length counterparts associated with the pathologies of a range of human diseases, including dementia and type 2 diabetes (T2D). Accordingly, here we examined the coaggregation of full-length human islet amyloid polypeptide (IAPP), a peptide associated with type 2 diabetes, with its primary and secondary amyloidogenic fragments 19-29 S20G and 8-20. Single-molecular aggregation dynamics was obtained by high-speed atomic force microscopy, augmented by transmission electron microscopy, X-ray diffraction, and super-resolution stimulated emission depletion microscopy. The coaggregation significantly prolonged the pause phase of fibril elongation, increasing its dwell time by 3-fold. Surprisingly, unidirectional elongation of mature fibrils, instead of protofilaments, was observed for the coaggregation, indicating a new form of tertiary protein aggregation unknown to existing theoretical models. Further in vivo zebrafish embryonic assay indicated improved survival and hatching, as well as decreased frequency and severity of developmental abnormalities for embryos treated with the heteroaggregates of IAPP with 19-29 S20G, but not with 8-20, compared to the control, indicating the therapeutic potential of 19-29 S20G against T2D.

The Formation Mechanism of Segmented Ring-Shaped Aβ Oligomers and Protofibrils

A clear understanding of amyloid formation with diverse morphologies is critical to overcoming the fatal disease amyloidosis. Studies have revealed that monomer concentration is a crucial factor for determining amyloid morphologies, such as protofibrils, annular, or spherical oligomers. However, gaining a complete understanding of the mechanism of formation of the various amyloid morphologies has been limited by the lack of experimental devices and insufficient knowledge. In this study, we demonstrate that the monomer concentration is an essential factor in determining the morphology of beta-amyloid (Aβ) oligomers or protofibrils. By computational and experimental approaches, we investigated the strategies for structural stabilization of amyloid protein, the morphological changes, and amyloid aggregation. In particular, we found unprecedented conformations, e.g., single bent oligomers and segmented ring-shaped protofibrils, the formation of which was explained by the computational analysis. Our findings provide insight into the structural features of amyloid molecules formed at low concentrations of monomer, which will help determine the clinical targets (in therapy) to effectively inhibit amyloid formation in the early stages of the amyloid growth phase.

Early mechanisms of amyloid fibril nucleation in model and disease-related proteins

Protein amyloid aggregation is a hallmark in neuropathologies and other diseases of tremendous impact such as Alzheimer's or Parkinson's diseases. During the last decade, it has become increasingly evident that neuronal death is mainly induced by proteinaceous oligomers rather than the mature amyloid fibrils. Therefore, the earliest molecular events occurring during the amyloid aggregation cascade represent a growing interest of study. Important breakthroughs have been achieved using experimental data from different proteins, used as models, as well as systems related to diseases. Here, we summarize the structural properties of amyloid oligomeric and fibrillar aggregates and review the recent advances on how biophysical techniques can be combined with quantitative kinetic analysis and theoretical models to study the detailed mechanism of oligomer formation and nucleation of fibrils. These insights into the mechanism of early oligomerization and amyloid nucleation are of relevant interest in drug discovery and in the design of preventive strategies against neurodegenerative diseases.

Network-Based Classification and Modeling of Amyloid Fibrils

Amyloid fibrils are locally ordered protein aggregates that self-assemble under a variety of physiological and in vitro conditions. Their formation is of fundamental interest as a physical chemistry problem and plays a central role in Alzheimer's disease, Type II diabetes, and other human diseases. As the number of known amyloid fibril structures has grown, the need has arisen for a nomenclature for describing and classifying fibril types, as well as a theoretical description of the physics that gives rise to the self-assembly of these structures. Here, we introduce a systematic nomenclature and coarse-graining methodology for describing the topology of fibrils and other protein aggregates, along with a computational methodology for simulating protein aggregation. Both have mathematical underpinnings in graph theory and statistical mechanics and are consistent with available experimental data on the fibril structure and aggregation kinetics. Our graph representation of the fibril topology enables us to define a network Hamiltonian based on connectivity patterns among monomers rather than detailed intermolecular interactions, greatly speeding up the simulation of large ensembles. Our simulation strategy is capable of recapitulating the formation of all currently known amyloid fibril topologies found in the Protein Data Bank, as well as the formation kinetics of fibrils and oligomers.

Inhibiting and catalysing amyloid fibrillation at dynamic lipid interfaces

Proteins are naturally exposed to diverse interfaces in living organisms, from static solid to dynamic fluid. Solid interfaces can enrich proteins as corona, and then catalyze, retard or hinder amyloid fibrillation. But fluid interfaces abundant in biology have rarely been studied for their correlation with protein fibrillation. Unsaturated fatty acids own growing essential roles in diet, whose fluid interfaces are found in vitro to catalyze amyloid fibrillation under certain physiologic conditions. It is determined by the location of double bonds within alkyl chains as well as the presence of physical shear. Docosahexaenoic acid (DHA) shows low catalysis because its unique alkyl chain does not favor to stabilize cross-β nucleus. Mixtures of different fatty acids also decelerate their catalytic activity. High catalysis poses an unprecedented approach to synthesize biologic nanofibrils as one-dimensional (1D) building blocks of functional hybrids. Fibrillation inhibition implied that appropriate diet would be a preventive strategy for amyloid-related diseases. Thus these results may find their significances in diverse fields of science as chemistry, biotechnology, nanotechnology, nutrition, amyloid pathobiology and nanomedicine.

RETRACTED: Peptide-induced formation of protein aggregates and amyloid fibrils in human and guinea pig αA-crystallins under physiological conditions of temperature and pH

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been retracted at the request of the authors. The senior author contacted the journal in a forthright manner, in an effort to preserve the scientific integrity of the literature, after discovering a significant error in the results reported in the article. The authors were recently made aware of a paper by Kim et al. (Nature Commun. 2019) which shows a spirosome structure (the enzyme aldehyde-alcohol dehydrogenase) present in E. coli (Fig. 5a) that is very similar to the structure the authors thought formed when synthetic alpha A crystallin (66-80) peptide was incubated for 24 h with recombinant guinea pig alpha A insert crystallin (see Kumarasamy et al., Figs. 7C and F, and Fig. 9). Subsequent to publication of their report, the authors later found a number of images that showed what appeared to be the same structure present in samples of their presumably purified recombinant guinea pig alpha A insert crystallin which had been incubated without peptide for 24 h. Hence, the authors now conclude that the structures shown in Figs. 7C and F, and Fig. 9 of their article published in this journal are actually due to E. coli contaminant aldehyde-alcohol dehydrogenase. The authors deeply regret this error and any inconvenience it may have caused.

Growth probability and formation time of the individual Oosawa-Kasai protein fibril

Protein fibrils are currently of great academic and practical interest because of their involvement in scores of severe human diseases and their promising use in various high-technology devices. The Oosawa-Kasai (OK) model of protein self-assembly into fibrils has been widely used to gain mechanistic insight into the process of fibril formation and growth. Here this model is employed to obtain exact and mathematically simple expressions for the probability P_{n} of an individual fibril of n protein monomers to grow to a macroscopically large size and for the mean time τ_{n} that such a fibril needs for its formation. These expressions quantify the increase of P_{n} and the decrease of τ_{n} with increasing the concentration of monomeric protein in the solution. When used for analysis of experimental P_{n} and τ_{n} data, they make it possible to determine the parameters characterizing fibril nucleation and growth in the framework of the OK model. Finally, an expression is found for the mean time of the first appearance of an n-sized fibril in the protein solution. The results obtained are applicable to the formation of other aggregates corresponding to the OK fibrils, such as the one-dimensional Kossel-Stranski crystals and Ising ferromagnets.

The yeast GRASP Grh1 displays a high polypeptide backbone mobility along with an amyloidogenic behavior

GRASPs are proteins involved in cell processes that seem paradoxical: responsible for shaping the Golgi cisternae and involved in unconventional secretion mechanisms that bypass the Golgi. Despite its physiological relevance, there is still a considerable lack of studies on full-length GRASPs. Our group has previously reported an unexpected behavior of the full-length GRASP from the fungus C. neoformans: its intrinsically-disordered characteristic. Here, we generalize this finding by showing that it is also observed in the GRASP from S. cerevisae (Grh1), which strongly suggests it might be a general property within the GRASP family. Furthermore, Grh1 is also able to form amyloid-like fibrils either upon heating or when submitted to changes in the dielectric constant of its surroundings, a condition that is experienced by the protein when in close contact with membranes of cell compartments, such as the Golgi apparatus. Intrinsic disorder and fibril formation can thus be two structural properties exploited by GRASP during its functional cycle.

Length-Dependent Manifestation of Vibration Modes Regulates a Specific Intermediate Morphology of Aβ17-42 in Different Environments

Various cytotoxic mechanisms for neurodegenerative disease are induced by specific conformations of Aβ intermediates. The efforts to understand the diverse intermediate forms of amyloid oligomers have been focused on understanding the aggregation mechanism of specific morphologies for Aβ intermediates. However, these are still not easy tasks to be accomplished because the diverse conformations of Aβ intermediates can be altered during the aggregation process, even though the same Aβ monomers are present. Thus, efforts to reveal the conformational change mechanism could be a fundamental process to understand the formation of diverse Aβ intermediate conformations. Here, we evaluate the conformational characteristics of Aβ_17-42 fibrillar oligomers in different environments according to the length. We observed that Aβ fibrillar oligomers optimize their inherent hydrogen bonds and configurational entropy to stabilize their structure according to the simulation time and their length increase. In addition, we revealed the role of the expressed vibration mode shape in the fibrillar oligomers' elongation and deformation processes. Our results suggest that limitations in amyloid oligomer growth and transformations of their morphologies can be regulated and controlled by modifying the vibration features.

Reductionist Approach in Peptide-Based Nanotechnology

The formation of ordered nanostructures by molecular self-assembly of proteins and peptides represents one of the principal directions in nanotechnology. Indeed, polyamides provide superior features as materials with diverse physical properties. A reductionist approach allowed the identification of extremely short peptide sequences, as short as dipeptides, which could form well-ordered amyloid-like β-sheet-rich assemblies comparable to supramolecular structures made of much larger proteins. Some of the peptide assemblies show remarkable mechanical, optical, and electrical characteristics. Another direction of reductionism utilized a natural noncoded amino acid, α-aminoisobutryic acid, to form short superhelical assemblies. The use of this exceptional helix inducer motif allowed the fabrication of single heptad repeats used in various biointerfaces, including their use as surfactants and DNA-binding agents. Two additional directions of the reductionist approach include the use of peptide nucleic acids (PNAs) and coassembly techniques. The diversified accomplishments of the reductionist approach, as well as the exciting future advances it bears, are discussed.

Paradoxical Effect of Trehalose on the Aggregation of α-Synuclein: Expedites Onset of Aggregation yet Reduces Fibril Load

Aggregation of α-synuclein is closely connected to the pathology of Parkinson's disease. The phenomenon involves multiple steps, commenced by partial misfolding and eventually leading to mature amyloid fibril formation. Trehalose, a widely accepted osmolyte, has been shown previously to inhibit aggregation of various globular proteins owing to its ability to prevent the initial unfolding of protein. In this study, we have examined if it behaves in a similar fashion with intrinsically disordered protein α-synuclein and possesses the potential to act as therapeutic agent against Parkinson's disease. It was observed experimentally that samples coincubated with trehalose fibrillate faster compared to the case in its absence. Molecular dynamics simulations suggested that this initial acceleration is manifestation of trehalose's tendency to perturb the conformational transitions between different conformers of monomeric protein. It stabilizes the aggregation prone "extended" conformer of α-synuclein, by binding to its exposed acidic residues of the C terminus. It also favors the β-rich oligomers once formed. Interestingly, the total fibrils formed are still promisingly less since it accelerates the competing pathway toward formation of amorphous aggregates.

Dissection of the deep-blue autofluorescence changes accompanying amyloid fibrillation

Pathogenesis of numerous diseases is associated with the formation of amyloid fibrils. Extrinsic fluorescent dyes, including Thioflavin T (ThT), are used to follow the fibrillation kinetics. It has recently been reported that the so-called deep-blue autofluorescence (dbAF) is changing during the aggregation process. However, the origin of dbAF and the reasons for its change remain debatable. Here, the kinetics of fibril formation in model proteins were comprehensively analyzed using fluorescence lifetime and intensity of ThT, intrinsic fluorescence of proteinaceous fluorophores, and dbAF. For all systems, intensity enhancement of the dbAF band with similar spectral parameters (∼350 nm excitation; ∼450 nm emission) was observed. Although the time course of ThT lifetime (indicative of protofibrils formation) coincided with that of tyrosine residues in insulin, and the kinetic changes in the ThT fluorescence intensity (reflecting formation of mature fibrils) coincided with changes in ThT absorption spectrum, the dbAF band started to increase from the beginning of the incubation process without a lag-phase. Our mass-spectrometry data and model experiments suggested that dbAF could be at least partially related to oxidation of amino acids. This study scrutinizes the dbAF features in the context of the existing hypotheses about the origin of this spectral band.

Modeling of the Inhibitory Effect of Nanoparticles on Amyloid β Fibrillation

Experiments have shown that charged nanoparticles (NP) inhibit, partially or completely, the aggregation of Aβ protein monomers into fibrils. The equilibrium fibril content is found to be inversely proportional to the concentration of NP. In this work, we report a kinetic model for the fibrillation of Aβ protein in the presence of NP. In the model, apart from nucleation, elongation and fragmentation processes, the effect of NP is considered to cause a conformational change to the protein monomer, making the latter incompatible for aggregation. The simulated results explain the growth kinetics of pure Aβ (1-40) protein, and the kinetics in the presence of NP. The NP-monomer interaction considered in the model captures the significant effect of NP on the fibrillation process at a very molar ratio (NP to Aβ monomer) as low as 10^-4. The model predictions are compared with two different NP systems, namely, gold and silica NP. The model can be applied to explain the inhibitory effect of other additives such as small molecules, NP, lipids, and surfactants that show a similar inhibition trend for fibril formation of Aβ and other proteins.