Characterization of Conjugated Polyelectrolytes As Molecular Sensors for the Detection of Amyloids in Neurodegenerative Diseases

Misfolding and aggregation of proteins is a central pathogenic event in neurodegenerative disorders such as Alzheimer’s and Parkinson’s diseases. Currently, there lacks a reliable sensor platform for detecting the range of protein aggregates involved in disease etiology, particularly the pre-fibrillar aggregate conformations that are the most neurotoxic due to a lack of molecular probes that could selectively and differentially target different protein aggregate conformations. We have shown that a class of synthetic polyelectrolytes, oligo p-phenylene ethylenes (OPEs), show promise as molecular sensors that can selectively detect fibrillar conformations of two model proteins, lysozyme and insulin. Compared to existing probes that are of limited clinical use, e.g., Thioflavin-T based probes, OPEs offer many distinct advantages, including versatile and highly tailorable structural and chemical properties, and most notably the multiple modes by which OPEs respond to interactions with ligands. In this study, we test the sensing capability of two leading OPE compounds against aggregates of a series of disease-relevant proteins, including the amyloid-beta peptide and tau protein implicated in Alzheimer’s disease, islet amyloid polypeptide in diabetes, and the Huntingtin protein in Huntington’s disease. Changes in the photophysical properties of the OPEs including absorbance, fluorescence excitation and emission were characterized in the presence and absence of amyloid protein aggregates. Our results indicate that the OPE sensors exhibit non-protein specific, large fluorescence enhancements in the presence of protein aggregates. Preliminary data of OPE staining of brain tissue sections of Alzheimer’s mouse models indicate that the OPEs has the potential to specifically stain amyloid deposits in the brain. This project contributes towards our goal of developing a novel class of sensors for the early detection and tracking of neurodegenerative disorders such as Alzheimer’s disease, which will not only help us understand the diseases better, but will also lead to early diagnosis and therapies to prevent and treat these devastating diseases.