Mathematical Modelling of Complex Cellular Networks of Autophagy—Lysosomal Pathway in Neurodegeneration

Abstract

Systems biology modelling helps to develop large complex biochemical pathways of disease networks including biochemical components and the interactions towards a multi-scale understanding of complex diseases. Mathematical modelling with the applications of biochemical systems theory using time-dependent ordinary differential equations and reaction rate equations helps to predict emergent behaviour of networks under different cellular conditions. In this study, the biochemical networks of autophagy-lysosomal pathway and role of alpha synuclein in Alzheimer's and Parkinson's disease have been modelled by using biochemical systems theory. The results show lysosome and autophagosome dysregulation by the action of amyloid beta and lipofuscin aggregation as a major contributor to Alzheimer's onset. The modelling allows comparing the interactions between biochemical species in both normal and diseased conditions and predicting new biomarkers to find potential targets which can help in early diagnosis and disease progression over time. Model predictions indicated activated calpain led to lysosomal leakage and activation of pro-apoptotic caspases that may result in irreversible cell damage. Simulations indicated dysfunctions in the degradation process of aggregated αS result in the formation of excess Lewy bodies, a known cause leading to dopaminergic cell death in Parkinson's. From the simulations, the model implicated lipofuscin aggregates, Lysosome-associated membrane protein 2 (LAMP2A), deglycase DJ-1, vesicular monoamine transporter 2 (VMAT-2), ubiquitinated proteins, amyloid beta and α-synuclein aggregates as the major network components involved in the deregulation of protein degradation that may be used as biomarkers for Alzheimer's and Parkinson's disease.