Modeling the neuron as a nanocommunication system to identify spatiotemporal molecular events in neurodegenerative disease

Aim In tauopathies such as Alzheimer’s disease (AD), molecular changes spanning multiple subcellular compartments of the neuron contribute to neurodegeneration and altered axonal signaling. Computational modeling of end-to-end linked events benefit mechanistic analysis and can be informative to understand disease progression and accelerate development of effective therapies. In the calcium-amyloid beta model of AD, calcium ions that are an important regulator of neuronal function undergo dysregulated homeostasis that disrupts cargo loading for neurotrophic signaling along axonal microtubules (MTs). The aim of the present study was to develop a computational model of the neuron using a layered architecture simulation that enables us to evaluate the functionalities of several interlinked components in the calcium-amyloid beta model. Methods The elevation of intracellular calcium levels is modeled upon binding of amyloid beta oligomers (AβOs) to calcium channels or as a result of membrane insertion of oligomeric Aβ1-42 to form pores/channels. The resulting subsequent Ca2+ disruption of dense core vesicle (DCV)-kinesin cargo loading and transport of brain-derived neurotrophic factor (BDNF) on axonal MTs are then evaluated. Our model applies published experimental data on calcium channel manipulation of DCV-BDNF and incorporates organizational complexity of the axon as bundled polar and discontinuous MTs. The interoperability simulation is based on the Institute of Electrical and Electronics Engineers standard association P1906.1 framework for nanoscale and molecular communication. Results Our analysis provides new spatiotemporal insights into the end-to-end signaling events linking calcium dysregulation and BDNF transport and by simulation compares the relative impact of dysregulation of calcium levels by AβO-channel interactions, oligomeric Aβ1-42 pores/channel formation, and release of calcium by internal stores. The flexible platform of our model allows continued expansion of molecular details including mechanistic and morphological parameters of axonal cytoskeleton networks as they become available to test disease and treatment predictions. Conclusion The present model will benefit future drug studies on calcium homeostasis and dysregulation linked to measurable neural functional outcomes. The algorithms used can also link to other multiscale multi-cellular modeling platforms to fill in molecular gaps that we believe will assist in broadening and refining multiscale computational maps of neurodegeneration.

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