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Updated: May 12, 2025

Fabrication of Amyloid-β-Secreting Alginate Microbeads for Use in Modelling Alzheimer's Disease
Published on: July 6, 2019
Three scenarios for amyloid transformation in the context of the funnel model
I Roterman1, M Słupina2, D Dułak3
1Department of Bioinformatics and Telemedicine, Jagiellonian University Medical College, ul. Medyczna 7, Kraków 30-688, Poland.
Abstract:
Analysis of the structure of proteins based on the evaluation of their geometric structure (secondary and supersecondary structure) can be extended to assess the structuring of the hydrophobic region of a protein. Such analysis of amyloid protein structures leads to the identification of three scenarios for amyloid formation. One is the loss of the micelle-like ordering present in the native form (a centric hydrophobic nucleus with a polar surface) in favour of a disordered distribution of hydrophobicity in the amyloid form. The term "micelle-like" is to be understood as specific hydrophobic burial. The second scenario is the reverse process, when the highly disordered distribution of hydrophobicity in the native form is replaced by a hydrophobic burial after amyloid transformation. These two scenarios have been identified for pathological (neurodegenerative) amyloids. The third scenario is the presence of hydrophobic burial ordering in a functional amyloid fibril. In this case, this ordering is present both in the fibril and in the single chain that is the building block of the fibril. This hydrophobic burial ordering provides a means of self-control of fibril size. It prevents unrestricted fibril propagation, which in the case of pathological amyloids is the main factor that disrupts the normal functioning of organelles in the amyloid surroundings. Population analysis (including numerous polymorphic forms) was performed using a collection of structures deposited in the Amyloid Atlas database. These observations allow the construction of a kind of amyloid funnel model, in which the energy minimum depends on external, environmental conditions that may be evaluated using the fuzzy oil drop model in its modified version (FOD-M).
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