Analytical Tools for Detecting Amyloid Beta Oligomerisation and Assembly

Author(s): Mun'delanji Vestergaard, Kagan Kerman

Journal Name: Current Pharmaceutical Analysis

Volume 5 , Issue 3 , 2009

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One of the main histopathological features of Alzheimers disease (AD) is the formation of neuritic plaques in the brain of AD individuals. The aggregation of amyloid beta (Aβ) peptides is central to the formation of the plaques. In its native form, Aβ is unfolded but self-assembles into a β-sheet structure of ordered fibrils under various conditions. It was originally proposed that fibrillar Aβ deposits cause the various symptoms of AD observed during its early and progressed stages but increasing evidence indicates that smaller, soluble forms of Aβ are the primary neurotoxic species. Still, the underlying mechanism of Aβ-induced neurotoxicity remains unknown. In order to fully understand which Aβ species are the most toxic under certain environmental conditions, we need sensitive analytical tools that are able to selectively detect the various stages of Aβ oligomerisation and assembly. Capturing these species would also aid in identifying potential therapeutic targets for the involved patho-physiological stages. Currently, Aβ oligomerisation and assembly are commonly studied using techniques such as microscopy, circular dichroism, fluorescence and light scattering spectroscopy. Label-free electrochemical aggregation of Aβ-peptides, surface plasmon resonance and agarose gel diffusion-based method have also been reported. In this paper, we review techniques used for analysing Aβ oligomerisation and assembly, emphasising those that provide information on Aβ aggregation kinetics. We will conclude by discussing the potential role nanotechnology has in enhancing the detection sensitivity and selectivity of Aβ oligomerisation and assembly.

Keywords: Amyloid beta, Oligomerisation, Assembly, Kinetics, Detection tools, Nanotechnology

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Article Details

Year: 2009
Page: [229 - 245]
Pages: 17
DOI: 10.2174/157341209788922039
Price: $65

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