Repulsive interaction induces fibril formation and their growth

Khatun, Suparna; Shikha, Kumari; Ganguly, Anirban; Pawar, Nisha; Gupta, Amar Nath

doi:10.1016/j.ijbiomac.2018.10.205

Cited by 11 publications

(5 citation statements)

References 47 publications

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“…This step is entropically favorable and results in the steady-state or plateau phase ( Figure 5 ). In this phase, the concentration of fibrils dominates, along with equilibrium with the monomer concentration [ 107 ]. Apart from this, mutations have also been known to fasten the aggregation kinetics.…”

Section: Different Types Of Amyloids Forming Proteinsmentioning

confidence: 99%

Amyloid Cross-Seeding: Mechanism, Implication, and Inhibition

et al. 2022

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Most neurodegenerative diseases such as Alzheimer’s disease, type 2 diabetes, Parkinson’s disease, etc. are caused by inclusions and plaques containing misfolded protein aggregates. These protein aggregates are essentially formed by the interactions of either the same (homologous) or different (heterologous) sequences. Several experimental pieces of evidence have revealed the presence of cross-seeding in amyloid proteins, which results in a multicomponent assembly; however, the molecular and structural details remain less explored. Here, we discuss the amyloid proteins and the cross-seeding phenomena in detail. Data suggest that targeting the common epitope of the interacting amyloid proteins may be a better therapeutic option than targeting only one species. We also examine the dual inhibitors that target the amyloid proteins participating in the cross-seeding events. The future scopes and major challenges in understanding the mechanism and developing therapeutics are also considered. Detailed knowledge of the amyloid cross-seeding will stimulate further research in the practical aspects and better designing anti-amyloid therapeutics.

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Section: Different Types Of Amyloids Forming Proteinsmentioning

confidence: 99%

Amyloid Cross-Seeding: Mechanism, Implication, and Inhibition

et al. 2022

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“…[28] Synthetic human amylin peptide molecules can spontaneously assemble into protofibrils with a coil-like structure (a-helix) or ribbon-like structure (rich in b-sheet conformation), and the protofibrils prefer to change from an exclusive conformation to an attractive conformation, which will further assemble into higher-order fibrils either by a lateral association (sheet-like arrays) or by coiling around each other (cable-like structures). [29][30][31] The super-pleated b structures are envisaged to have a lefthanded twist along the H-bond direction and may further form super-left-handed coils. [32] However, the small, diffusible amorphous intracellular and extracellular aggregates of hIAPP (also known as prefibrillar amyloid species) rather than mature fibrillar aggregates are toxic and contribute to the apoptosis and necrosis of mammalian cells [33] ; in some cases, the maturation of toxic amylin into a large amyloid is considered a protective mechanism.…”

Section: Secretion and Function Of Amylinmentioning

confidence: 99%

“…In individuals with prediabetes, paralleled with hyperinsulinemia, a compensatory mechanism to regulate blood glucose and hypersecretion of amylin is common, which may lead to amylin deposition, amyloidogenesis, and proteotoxicity in pancreatic islets, and contributes to the development of type 2 diabetes [28] . Synthetic human amylin peptide molecules can spontaneously assemble into protofibrils with a coil-like structure (α-helix) or ribbon-like structure (rich in β-sheet conformation), and the protofibrils prefer to change from an exclusive conformation to an attractive conformation, which will further assemble into higher-order fibrils either by a lateral association (sheet-like arrays) or by coiling around each other (cable-like structures) [29–31] . The super-pleated β structures are envisaged to have a left-handed twist along the H-bond direction and may further form super-left-handed coils [32] .…”

Section: Conformational Changes Of Amylin and The Formation Of Amyloidmentioning

confidence: 99%

Amylin: new insight into pathogenesis, diagnosis, and prognosis of non-insulin-dependent diabetes-mellitus-related cardiomyopathy

Liu

Tong

Shen

et al. 2022

Emergency and Critical Care Medicine

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Co-secretion with insulin, highly amyloidogenic human amylin is considered to contribute to the initiation and progression of diabetic heart complications, despite other situations such as hypertension and atherosclerosis. In response to insulin resistance, hyperinsulinemia, and consequently hyperamylinemia, is common in prediabetic patients, where highly concentrated amylin is prone to form amylin oligomers, which further assemble into fibrils and amyloids with high β-sheet content. The infusion and deposition of oligomeric amylin in myocytes cause a series of consequences, including cytosolic Ca2+ dysregulation, calmodulin activation, myocyte hypertrophy, and ventricular stiffness, eventually leading to heart failure. In this review, we present the latest reports of amylin-related heart complications, provide new insights, and state the underlying pathogenesis, diagnosis, possible treatment, and prevention of diabetic cardiomyopathy.

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“…For proteins in aqueous solution, measuring association states and propensities towards/away from aggregation is essential for understanding the formation and evolution of both native quaternary structure and deleterious aggregation, due to the fundamental roles of these properties in protein association [ 1 – 4 ]. Unfortunately, this is difficult, particularly in the highly relevant case of systems at low concentration at or near physiological pH.…”

Section: Introductionmentioning

confidence: 99%

Bayesian analysis of static light scattering data for globular proteins

et al. 2021

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Static light scattering is a popular physical chemistry technique that enables calculation of physical attributes such as the radius of gyration and the second virial coefficient for a macromolecule (e.g., a polymer or a protein) in solution. The second virial coefficient is a physical quantity that characterizes the magnitude and sign of pairwise interactions between particles, and hence is related to aggregation propensity, a property of considerable scientific and practical interest. Estimating the second virial coefficient from experimental data is challenging due both to the degree of precision required and the complexity of the error structure involved. In contrast to conventional approaches based on heuristic ordinary least squares estimates, Bayesian inference for the second virial coefficient allows explicit modeling of error processes, incorporation of prior information, and the ability to directly test competing physical models. Here, we introduce a fully Bayesian model for static light scattering experiments on small-particle systems, with joint inference for concentration, index of refraction, oligomer size, and the second virial coefficient. We apply our proposed model to study the aggregation behavior of hen egg-white lysozyme and human γS-crystallin using in-house experimental data. Based on these observations, we also perform a simulation study on the primary drivers of uncertainty in this family of experiments, showing in particular the potential for improved monitoring and control of concentration to aid inference.

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Repulsive interaction induces fibril formation and their growth

Cited by 11 publications

References 47 publications

Amyloid Cross-Seeding: Mechanism, Implication, and Inhibition

Amyloid Cross-Seeding: Mechanism, Implication, and Inhibition

Amylin: new insight into pathogenesis, diagnosis, and prognosis of non-insulin-dependent diabetes-mellitus-related cardiomyopathy

Bayesian analysis of static light scattering data for globular proteins

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