Developing Peptide Based Inhibitors Targeting Amyloid-Beta for Alzheimer’s Disease

Abstract

Alzheimer’s Disease is widely known as the most common precursor of dementia, cited as a progressive neurological disease that negatively impacts one’s cognitive functions over time. It’s identified as the seventh leading cause of death by the CDC, seeing an 145% increase in deaths since its discovery by Alois Alzheimer in 1906. Throughout the years of various potential treatment options for this disorder, scientists have been unsuccessful in both curing the disease and eradicating its merciless symptoms. One promising avenue is the use of targeted therapeutics via amyloid-beta, a peptide that is placed at the forefront of Alzheimer’s disease causes due to its accumulation that results in neurofibrillary tangles and senile plaques. In this research, various peptides are developed, synthesized, and investigated to analyze their impact on binding affinity to Amyloid-beta. The aim is to improve potent analogues by modifying previously tested peptide sequences, display superior binding affinities in developed peptides to amyloid-beta and showcase a decrease in fibril formation through fluorescence testing. Solid phase peptide synthesis protocol was employed to synthesize the peptide and mass spectrometry experiment was conducted to verify the mass of these peptides. Cyclic peptide was synthesized by adding 10% DMSO and stirring for one or two days. Selected ion monitoring (SIM) assay was performed by liquid chartography and mass spectrometry by monitoring the intensity of related peaks of amyloid beta once peptide inhibitors were added at various concentrations. Dissociation constant (Kd) is used to measure the binding affinity between amyloid-beta and peptide inhibitors. The linear peptide (LP1) has shown excellent binding affinity with a Kd value of 0.037 micromolar (µM). Its cyclic counterpart (CP-1) also displayed similar binding affinity with a Kd value of 0.049 micromolar (µM)

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DigitalCommons@Kennesaw State University

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Last time updated on 12/04/2025

This paper was published in DigitalCommons@Kennesaw State University.

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