Parkinson’s disease is a progressive neurodegenerative disease associated with a loss of dopaminergic neurons in the substantia nigra of the brain. Neuroinflammation, another hallmark of the disease, is thought to play an important role in the neurodegenerative process. While mitigating neuroinflammation could prove beneficial for Parkinson’s disease, identifying the most relevant biological processes and pharmacological targets as well as drugs to modulate them remains highly challenging. The present study aimed to better understand the protein network behind neuroinflammation in Parkinson’s disease and to prioritize possible targets for its pharmacological modulation. We first used text-mining to systematically collect the proteins significantly associated to Parkinson’s disease neuroinflammation over the scientific literature. The functional interaction network formed by these proteins was then analyzed by integrating functional enrichment, network topology analysis and drug-protein interaction analysis. We identified 57 proteins significantly associated to neuroinflammation in Parkinson’s disease. Toll-like Receptor Cascades as well as Interleukin 4, Interleukin 10 and Interleukin 13 signaling appeared as the most significantly enriched biological processes. Protein network analysis using STRING and CentiScaPe identified 8 proteins with the highest ability to control these biological processes underlying neuroinflammation, namely caspase 1, heme oxygenase 1, interleukin 1beta, interleukin 4, interleukin 6, interleukin 10, tumor necrosis factor alpha and toll-like receptor 4. These key proteins were indexed to be targetable by a total of 38 drugs including 27 small compounds 11 protein-based therapies. In conclusion, our study highlights key proteins in Parkinson’s disease neuroinflammation as well as pharmacological compounds acting on them. As such, it may facilitate the prioritization of biomarkers for the development of diagnostic, target-engagement assessment and therapeutic tools against Parkinson’s disease.
About The Expert
Marie-Amandine Bonte
Fatima El Idrissi
Bernard Gressier
David Devos
Karim Belarbi
References
PubMed