Visualization and refinement of quantitative modelling of APP processing
A key event in Alzheimer’s disease is amyloidogenic cleavage of the Amyloid Precursor Protein (APP). The molecular mechanism underlying the APP cleavage is well understood. Accordingly, a first mathematical model of this process was suggested. This model was based on experimental data gained from the influence of one genetic risk factor. Contrary to previous hypotheses, this study demonstrated that secretases represent allosteric enzymes that require cooperativity by APP dimerization for efficient processing.
We aim to improve the current model in two different ways. First, we will adjust the Matlab code describing the current model, in a way that allows easy implementation of different data sets. Secondly, we attempt to implement a visual tool for interactive modeling and simulation of protein kinetic networks that will allow quick iteration of models and estimation of parameters. The tool is further intended to facilitate comparison of multiple model variations to experimental data to validate them. Appropriate visualization and interaction techniques will be used to expedite these processes and generate insight into model traits and behavior. Through this methodology, we aim to extend the model of APP processing by implementation of additional genetic or abiotic risc factors of AD. Third, we aim to refine the parameters describing the kinetics of APP dimerization, using experimental data gained with a previously established inducible dimerization system for APP.
The optimized model will allow mapping the quantitative contribution of additional cis-acting factors to APP metabolism and perhaps even to stratify the amyloidogenic burden (a stage of AD patients) in individuals with a given ratio of APP and main effector components.