IAPP Amyloid Aggregation and IAPP-Associated Toxicity Mitigation

Human islet amyloid polypeptide (IAPP, a.k.a. amylin) is a 37-residue peptide hormone co-synthesized and co-secreted with insulin by pancreatic β-cells for glycemic control. Extensive research indicates that the amyloid aggregation of IAPP into cross-β amyloid fibrils is a ubiquitous phenomenon as well as a major factor in the development and pathogenesis of type 2 diabetes mellitus (T2D), which is a long-term metabolic disorder compromises the quality of life of millions globally. The amyloid IAPP aggregation products, either soluble intermediate oligomers or mature fibrils, are found toxic to human cells and capable of eliciting systemic damage in T2D patients. Recent studies reveal that IAPP is able to cross the blood-brain barrier and co-aggregate with human amyloid-beta (Aβ), which is the protein associated with another amyloid neurodegenerative disorder, the Alzheimer’s disease (AD). In vitro experiments demonstrate that soluble IAPP could significantly accelerate the aggregation of Aβ, with accumulating clinical and epidemiological evidences also suggest that T2D and AD are linked together. Despite the significant differences in their pathologies, T2D is suggested as a risk factor for AD. Here, we investigate the possible mechanism of the co-aggregation of IAPP and Aβ to explore the cross-talk between these two diseases and propose that IAPP promotes Aβ aggregation by reducing the aggregation free energy barrier through its binding with Aβ. In addition, with the fact that IAPPs are stored inside β-cell granules without apparent aggregation in healthy individuals, we also study the physiological environment inside β-cell granules and its endogenous inhibition effect on IAPP aggregation. Our work demonstrates that Zn2+ coordinated molecular complex might be important to stabilize IAPP and hence the endogenous inhibition. Moreover, we study the interactions between IAPP and two different materials, the small molecule epigallocatechin gallate (EGCG) and the star-shaped polymer poly(2-hydroxyethyl acrylate) (PHEA). Our study demonstrates both EGCG and PHEA as inhibitors against amyloidogenesis, while perform in different strategies. EGCG is able to inhibit IAPP aggregation and result in minimizing the population of toxic oligomers and protofibrils, while PHEA accelerates IAPP fibrillation to circumvent accumulation of the more toxic intermediates

Systematic development of small molecules to inhibit specific microscopic steps of Aβ42 aggregation in Alzheimer’s disease

The aggregation of the 42-residue form of the amyloid-β peptide (Aβ42) is a pivotal event in Alzheimer’s disease (AD). The use of chemical kinetics has recently enabled highly accurate quantifications of the effects of small molecules on specific microscopic steps in Aβ42 aggregation. Here, we exploit this approach to develop a rational drug discovery strategy against Aβ42 aggregation that uses as a read-out the changes in the nucleation and elongation rate constants caused by candidate small molecules. We thus identify a pool of compounds that target specific microscopic steps in Aβ42 aggregation. We then test further these small molecules in human cerebrospinal fluid and in a Caenorhabditis elegans model of AD. Our results show that this strategy represents a powerful approach to identify systematically small molecule lead compounds, thus offering an appealing opportunity to reduce the attrition problem in drug discovery

Characterisation of the structure and oligomerisation of islet amyloid polypeptides (IAPP): A review of molecular dynamics simulation studies

Human islet amyloid polypeptide (hIAPP) is a naturally occurring, intrinsically disordered protein whose abnormal aggregation into amyloid fibrils is a pathological feature in type 2 diabetes, and its cross-aggregation with amyloid beta has been linked to an increased risk of Alzheimer’s disease. The soluble, oligomeric forms of hIAPP are the most toxic to ß-cells in the pancreas. However, the structure of these oligomeric forms is difficult to characterise because of their intrinsic disorder and their tendency to rapidly aggregate into insoluble fibrils. Experimental studies of hIAPP have generally used non-physiological conditions to prevent aggregation, and they have been unable to describe its soluble monomeric and oligomeric structure at physiological conditions. Molecular dynamics (MD) simulations offer an alternative for the detailed characterisation of the monomeric structure of hIAPP and its aggregation in aqueous solution. This paper reviews the knowledge that has been gained by the use of MD simulations, and its relationship to experimental data for both hIAPP and rat IAPP. In particular, the influence of the choice of force field and water models, the choice of initial structure, and the configurational sampling method used, are discussed in detail. Characterisation of the solution structure of hIAPP and its mechanism of oligomerisation is important to understanding its cellular toxicity and its role in disease states, and may ultimately offer new opportunities for therapeutic interventions

Dynamics of Protofibril Elongation and Association Involved in Aβ42 peptide Aggregation in Alzheimer\u27s Disease

Background: The aggregates of a protein called, ‘Aβ’ found in brains of Alzheimer’s patients are strongly believed to be the cause for neuronal death and cognitive decline. Among the different forms of Aβ aggregates, smaller aggregates called ‘soluble oligomers’ are increasingly believed to be the primary neurotoxic species responsible for early synaptic dysfunction. Since it is well known that the Aβ aggregation is a nucleation dependant process, it is widely believed that the toxic oligomers are intermediates to fibril formation, or what we call the ‘on-pathway’ products. Modeling of Aβ aggregation has been of intense investigation during the last decade. However, precise understanding of the process, pre-nucleation events in particular, are not yet known. Most of these models are based on curve-fitting and overlook the molecular-level biophysics involved in the aggregation pathway. Hence, such models are not reusable, and fail to predict the system dynamics in the presence of other competing pathways. Results: In this paper, we present a molecular-level simulation model for understanding the dynamics of the amyloid-β (Aβ) peptide aggregation process involved in Alzheimer’s disease (AD). The proposed chemical kinetic theory based approach is generic and can model most nucleation-dependent protein aggregation systems that cause a variety of neurodegenerative diseases. We discuss the challenges in estimating all the rate constants involved in the aggregation process towards fibril formation and propose a divide and conquer strategy by dissecting the pathway into three biophysically distinct stages: 1) pre-nucleation stage 2) post-nucleation stage and 3) protofibril elongation stage. We next focus on estimating the rate constants involved in the protofibril elongation stages for Aβ42 supported by in vitro experimental data. This elongation stage is further characterized by elongation due to oligomer additions and lateral association of protofibrils (13) and to properly validate the rate constants involved in these phases we have presented three distinct reaction models. We also present a novel scheme for mapping the fluorescence sensitivity and dynamic light scattering based in vitro experimental plots to estimates of concentration variation with time. Finally, we discuss how these rate constants will be incorporated into the overall simulation of the aggregation process to identify the parameters involved in the complete Aβ pathway in a bid to understand its dynamics. Conclusions: We have presented an instance of the top-down modeling paradigm where the biophysical system is approximated by a set of reactions for each of the stages that have been modeled. In this paper, we have only reported the kinetic rate constants of the fibril elongation stage that were validated by in vitro biophysical analyses. The kinetic parameters reported in the paper should be at least accurate upto the first two decimal places of the estimate. We sincerely believe that our top-down models and kinetic parameters will be able to accurately model the biophysical phenomenon of Aβ protein aggregation and identify the nucleation mass and rate constants of all the stages involved in the pathway. Our model is also reusable and will serve as the basis for making computational predictions on the system dynamics with the incorporation of other competing pathways introduced by lipids and fatty acids

Physical determinants of the self-replication of protein fibrils

The ability of biological molecules to replicate themselves, achieved with the aid of a complex cellular machinery, is the foundation of life. However, a range of aberrant processes involve the selfreplication of pathological protein structures without any additional factors. A dramatic example is the autocatalytic replication of pathological protein aggregates, including amyloid fibrils and prions, involved in neurodegenerative disorders. Here, we use computer simulations to identify the necessary requirements for the self-replication of fibrillar assemblies of proteins. We establish that a key physical determinant for this process is the affinity of proteins for the surfaces of fibrils. We find that self-replication can only take place in a very narrow regime of inter-protein interactions, implying a high level of sensitivity to system parameters and experimental conditions. We then compare our theoretical predictions with kinetic and biosensor measurements of fibrils formed from the Aβ peptide associated with Alzheimer’s disease. Our results show a quantitative connection between the kinetics of self-replication and the surface coverage of fibrils by monomeric proteins. These findings reveal the fundamental physical requirements for the formation of supra-molecular structures able to replicate themselves, and shed light on mechanisms in play in the proliferation of protein aggregates in nature.We acknowledge support from the Human Frontier Science Program and Emmanuel College (A.Š), Leverhulme Trust and Magdalene College (A.K.B), St. John’s College (T.C.T.M), the Biotechnology and Biological Sciences Research Council (T.P.J.K. and C. M. D.), the Frances and Augustus Newman Foundation (T.P.J.K.), the European Research Council (T.P.J.K., S.L. and D.F), and the Engineering and Physical Sciences Research Council (D.F.).This is the author accepted manuscript. The final version is available from Nature Publishing Group via https://doi.org/10.1038/nphys382

Fatty Acid Concentration and Phase Transitions Modulate Aβ Aggregation Pathways

Aggregation of amyloid β (Aβ) peptides is a significant event that underpins Alzheimer disease (AD) pathology. Aβ aggregates, especially the low-molecular weight oligomers, are the primary toxic agents in AD and hence, there is increasing interest in understanding their formation and behavior. Aggregation is a nucleation-dependent process in which the pre-nucleation events are dominated by Aβ homotypic interactions. Dynamic flux and stochasticity during pre-nucleation renders the reactions susceptible to perturbations by other molecules. In this context, we investigate the heterotypic interactions between Aβ and fatty acids (FAs) by two independent tool-sets such as reduced order modelling (ROM) and ensemble kinetic simulation (EKS). We observe that FAs influence Aβ dynamics distinctively in three broadly-defined FAconcentration regimes containing non-micellar, pseudo-micellar or micellar phases. While the non-micellar phase promotes on-pathway fibrils, pseudo-micellar and micellar phases promote predominantly off-pathway oligomers, albeit via subtly different mechanisms. Importantly off-pathway oligomers saturate within a limited molecular size, and likely with a different overall conformation than those formed along the on-pathway, suggesting the generation of distinct conformeric strains of Aβ, which may have profound phenotypic outcomes. Our results validate previous experimental observations and provide insights into potential influence of biological interfaces in modulating Aβ aggregation pathways

Dynamics of Protofibril Elongation and Association Involved in Aβ42 peptide Aggregation in Alzheimer\u27s Disease

Background: The aggregates of a protein called, ‘Aβ’ found in brains of Alzheimer’s patients are strongly believed to be the cause for neuronal death and cognitive decline. Among the different forms of Aβ aggregates, smaller aggregates called ‘soluble oligomers’ are increasingly believed to be the primary neurotoxic species responsible for early synaptic dysfunction. Since it is well known that the Aβ aggregation is a nucleation dependant process, it is widely believed that the toxic oligomers are intermediates to fibril formation, or what we call the ‘on-pathway’ products. Modeling of Aβ aggregation has been of intense investigation during the last decade. However, precise understanding of the process, pre-nucleation events in particular, are not yet known. Most of these models are based on curve-fitting and overlook the molecular-level biophysics involved in the aggregation pathway. Hence, such models are not reusable, and fail to predict the system dynamics in the presence of other competing pathways. Results: In this paper, we present a molecular-level simulation model for understanding the dynamics of the amyloid-β (Aβ) peptide aggregation process involved in Alzheimer’s disease (AD). The proposed chemical kinetic theory based approach is generic and can model most nucleation-dependent protein aggregation systems that cause a variety of neurodegenerative diseases. We discuss the challenges in estimating all the rate constants involved in the aggregation process towards fibril formation and propose a divide and conquer strategy by dissecting the pathway into three biophysically distinct stages: 1) pre-nucleation stage 2) post-nucleation stage and 3) protofibril elongation stage. We next focus on estimating the rate constants involved in the protofibril elongation stages for Aβ42 supported by in vitro experimental data. This elongation stage is further characterized by elongation due to oligomer additions and lateral association of protofibrils (13) and to properly validate the rate constants involved in these phases we have presented three distinct reaction models. We also present a novel scheme for mapping the fluorescence sensitivity and dynamic light scattering based in vitro experimental plots to estimates of concentration variation with time. Finally, we discuss how these rate constants will be incorporated into the overall simulation of the aggregation process to identify the parameters involved in the complete Aβ pathway in a bid to understand its dynamics. Conclusions: We have presented an instance of the top-down modeling paradigm where the biophysical system is approximated by a set of reactions for each of the stages that have been modeled. In this paper, we have only reported the kinetic rate constants of the fibril elongation stage that were validated by in vitro biophysical analyses. The kinetic parameters reported in the paper should be at least accurate upto the first two decimal places of the estimate. We sincerely believe that our top-down models and kinetic parameters will be able to accurately model the biophysical phenomenon of Aβ protein aggregation and identify the nucleation mass and rate constants of all the stages involved in the pathway. Our model is also reusable and will serve as the basis for making computational predictions on the system dynamics with the incorporation of other competing pathways introduced by lipids and fatty acids

A Game-Theoretic Approach to Deciphering the Dynamics of Amyloid-Beta Aggregation Along Competing Pathways

Aggregation of amyloid-β (Aβ) peptides is a significant event that underpins Alzheimer\u27s disease (AD). Aβ aggregates, especially the low-molecular weight oligomers, are the primary toxic agents in AD pathogenesis. Therefore, there is increasing interest in understanding their formation and behaviour. In this paper, we use our previously established results on heterotypic interactions between Aβ and fatty acids (FAs) to investigate off-pathway aggregation under the control of FA concentrations to develop a mathematical framework that captures the mechanism. Our framework to define and simulate the competing on- and off-pathways of Aβ aggregation is based on the principles of game theory. Together with detailed simulations and biophysical experiments, our models describe the dynamics involved in the mechanisms of Aβ aggregation in the presence of FAs to adopt multiple pathways. Specifically, our reduced-order computations indicate that the emergence of off- or on-pathway aggregates are tightly controlled by a narrow set of rate constants, and one could alter such parameters to populate a particular oligomeric species. These models agree with the detailed simulations and experimental data on using FA as a heterotypic partner to modulate the temporal parameters. Predicting spatio-temporal landscape along competing pathways for a given heterotypic partner such as lipids is a first step towards simulating scenarios in which the generation of specific ‘conformer strains’ of Aβ could be predicted. This approach could be significant in deciphering the mechanisms of amyloid aggregation and strain generation, which are ubiquitously observed in many neurodegenerative diseases

Small Molecule Effects on Amyloidogenic, Intrinsically Disordered Peptides

In recent years there has been an explosion of interest in the physiological functions of intrinsically disordered peptides (IDPs) and how they are involved in diseases, specifically amyloid diseases. A fascinating aspect of amyloid is that rigid, ordered fibrils can be formed from highly flexible IDPs such as, Amyloid-beta (AB) and human Islet Amyloid Polypeptide (hIAPP). These two peptides aggregate to form amyloid in two, currently incurable diseases: Alzheimer's disease and Type II Diabetes Mellitus (TIIDM) respectively. The early steps of how AB and hIAPP transition from disordered monomers to conformers compatible with amyloid formation is an enigma which remains a challenge to understand in molecular detail. The combination of IDP structural fluidity and the complexities of amyloid formation makes structural analysis and study of this area challenging to investigate but has the potential to reveal invaluable information. The strategy for such investigation presented here focuses on searching for small molecules able to stabilise monomeric conformers of these peptides and hence to potentially disfavour amyloid formation. This work presents a methodological strategy to assess small molecule effects on recombinantly expressed and purified AB40 amyloid aggregation. The strategy is then implemented on a carefully selected set of lead molecules; a library of 67 compounds were selected from in silico rapid overlay of chemical structures (ROCS) analysis based on structural similarity to either 1,2-naphthoquinone, adapalene, bexarotene, MM3003, or UV11352. These were screened for AB40 amyloid perturbation effects using a Thioflavin-T fluorescence assay and lead compounds were identified. Lead compounds which could modulate amyloid formation were then assessed by a carefully selected toolbox of methods including Electrospray ionisation ion mobility mass spectrometry, and electron microscopy. Finally a set of complementary NMR methods are presented which enable residue specific structural propensity (residual dipolar couplings, temperature coefficients and dCa measurements) and flexibility (transverse relaxation rates, heteronuclear nuclear Overhauser effects) of small molecule-induced conformers to be monitored and compared with the same proteins in the absence of bound ligand. The framework laid out in this work has great impact potential due to is applicability to the amyloid and IDP fields. The ability to study early species in the amyloid process will reveal insights on important structures and potential folding routes in the amyloid aggregation process

Amyloid Aggregation Behavior of Human Calcitonin

Under appropriate conditions, certain peptides and proteins, both intrinsically disordered and misfolded from their native state, can self-associate to form long proteinaceous fibrils known as amyloids. This transition forms the molecular basis of several pathologies, through both losses of native functions and cytotoxic effects. Calcitonin (CT) is a 32 amino acid therapeutic hormone peptide that can be considered a molecular paradigm for the central events associated with amyloid misfolding. CT’s biological activity is limited by its aggregation along the canonical amyloid aggregation pathway. A better understanding of the misfolding process would not only provide a structural basis to improve CT’s long-term stability and activity as a therapeutic, but also provide valuable insights into the pathological aggregation of other amyloids. As such, the aggregation of human CT (hCT) has been studied in this dissertation using a range of biophysical techniques, with a particular focus on native modulators of kinetic behavior. A direct relationship between human calcitonin (hCT) concentration and aggregation lag time was observed for the first time, contrary to the conventional understanding of amyloid aggregation. This kinetic trend was found to persist over a range of aggregation conditions, as confirmed by Thioflavin-T kinetics assays, CD spectroscopy, and transmission EM. On the basis of kinetics modeling and experimental results, a mechanism whereby structural conversion of hCT monomers is needed before incorporation into the fibril was proposed. Comparative studies of hCT and the canonically aggregating salmon CT (sCT) using experimental and computational techniques suggested that alpha-helical monomers represent a growth-competent species, whereas unstructured random coil monomers represent a growth-incompetent species. The kinetic mechanism proposed represents a novel mechanism in amyloid aggregation, and synthesizes several previously disparate amyloid behaviors. The determinants of hCT lag time were further investigated in a membrane environment, providing the first systematic study of the effect of membranes on CT aggregation. The direct relationship between peptide concentration and lag phase was found to persist in the presence of large unilamellar vesicles (LUVs), and was shown to be dependent on membrane composition. Specifically, lipid compositions encouraging stronger surface interactions increased the concentration dependent differences in lag time. CD experiments suggested adsorption and sequestration of growth-competent helical monomers to play a role in this behavior. An apparent reformatting of mature hCT fibrils was also observed, in a process which appears dependent on not only lipid composition but also the peptide to lipid ratio. The ability of LUVs to remodel fibers grown in solution suggests that interactions between mature fibrils and lipid bilayers are causative in the behavior, rather than membrane-peptide interactions during fiber growth. The results of this thesis, particularly as they relate to monomer growth competence, represent significant contributions to the amyloid field and CT therapy. The novel kinetic mechanism proposed reveals that intramolecular interactions in disordered monomers, while often transient and weak compared to intermolecular interactions, can play crucial roles in mediating amyloid aggregation. Additionally, the elucidated effects of monomer structure and lipid interactions on hCT aggregation kinetics present possible means by which aggregation kinetics can be modulating while maintaining peptide sequence and thus therapeutic efficacy, a key goal in hCT therapies. Such results present a richer picture of hCT aggregation than had previously been available, and potentially provide novel insights as to more general mechanisms of amyloid aggregation.PHDApplied PhysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144023/1/kkamgar_1.pd