Abstract
The paper aims developing a computational framework of signaling using the principles of biochemical systems theory as a model for Parkinson’s disease. Several molecular interactions aided by TNFα, a proinflammatory cytokine play key roles in mediating glutamate excitotoxicity and neuroinflammation, resulting in neuronal cell death. In this paper, initial concentrations and rate constants were extracted from literature and simulations developed were based on systems of ordinary differential equations following first-order kinetics. In control or healthy conditions, a decrease in TNFα and neuronal cell death was predicted in simulations matching data from experiments, whereas in diseased condition, a drastic increase in levels of TNFα, glutamate, TNFR1 and ROS were observed similar to experimental data correlating diseased condition to augmented neuronal cell death. The study suggests toxic effects induced by TNFα in the substantia nigra may be attributed to Parkinson’s disease conditions.
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Acknowledgements
This work derives direction and ideas from the Chancellor of Amrita University, Sri Mata Amritanandamayi Devi. This work was partially funded by Department of Science and Technology Grant DST/CSRI/2017/31, Government of India and by Embracing the World Research-for-a-Cause initiative.
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Sasidharakurup, H., Nair, L., Bhaskar, K., Diwakar, S. (2020). Computational Modelling of TNFα Pathway in Parkinson’s Disease – A Systemic Perspective. In: Cherifi, H., Gaito, S., Mendes, J., Moro, E., Rocha, L. (eds) Complex Networks and Their Applications VIII. COMPLEX NETWORKS 2019. Studies in Computational Intelligence, vol 882. Springer, Cham. https://doi.org/10.1007/978-3-030-36683-4_61
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