Computational modeling of convergent mechanisms in Alzheimer’s and Parkinson’s disease with insulin signaling using biochemical systems theory

Abstract Computational modeling has significantly impacted clinical assessment and treatment of diseases by improving diagnosis, prognosis, discovery of novel biomarkers and developing new drugs that assures treatment for incurable diseases. In this study, a biochemical systems theory model was developed to explore crucial pathways involved in shared mechanisms between Alzheimer’s and Parkinson’s diseases and insulin signaling involved in Parkinson’s disease (PD). Mass kinetic concentration values and rate constants were retrieved from experiments cited in literature and simulations were developed using systems of ordinary differential equations. Calcium changes were reconstructed accounting reduced levels in diseased conditions. Simulations suggest that AD and PD share some of the important cellular pathways such as α-synuclein, tau phosphorylation, calcium homeostasis, ROS and TNF-α in spite of the differences in mechanisms and symptoms. Here, modeling relates the critical role insulin signaling may have in maintaining dopamine levels in PD patients.