(174aj) Modeling Amyloid Beta Aggregation Inhibition with Decapeptide

Alzheimer’s disease (AD) is a form of dementia commonly found in the elderly and is related to the interplay between the overproduced reactive oxygen species and the amyloid beta (Aβ). Amyloid beta protein, found in the human brain, is considered a main factor of AD pathogenesis. In AD, Aβ protein aggregates to form fibrils/plaques. Fibrils accumulate across the nerve cells and damage them. The amyloid hypothesis has gained significant attention in understanding the disease progression and, hence, is actively utilized to get insights into the drug interactions with Aβ protein.

In open literature, it is shown that the decapeptide drug acts as an inhibitor for Aβ aggregation and the relevant experimental data is also reported. In this work, a simple mathematical model is developed to study the mechanism of action of decapeptide drug on the inhibition of amyloid beta protein agglomeration. The model includes the simultaneous differential equations based of species mass balance of protein and decapeptide. The developed model is tuned using the reported experimental data using “lsqnonlin” optimizer in MATLAB. Lsqnonlin minimizes the difference between the experimental data and the model predicted data to find the model parameters. The model is further tested on another set of experimental data given at a different initial drug concentration. The model prediction shows a good agreement with the experimental data. Sensitivity analysis is performed to check the parameters’ reliability and the robustness of the developed model.