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Abstract
Parkinson's disease (PD) is a chronic and progressive neurological disorder that significantly impairs a person's ability to control their movements. Currently, nearly one million people in the USA are living with PD. After Alzheimer’s disease, PD is the second most common neurodegenerative disease in the USA. The disease is characterized by the aggregation of the alpha-synuclein protein, which forms fibril-like structures called Lewy bodies. The current work aims to develop therapeutic strategies against the disease by inhibiting this fibril formation. We hypothesize that chemical compounds that can bind at the interface can block the binding and prevent fibril formation. We have utilized molecular docking techniques to screen 3450 chemical compounds against the alpha-synuclein protein, to bind to and prevent alpha-synuclein clumping, thereby inhibiting fibril formation. Based on our docking simulations, we have selected the top five compounds that bind strongly to the protein. All these ligands bind to the hydrophobic region of the protein, suggesting that hydrophobic drugs (capable of crossing the blood-brain barrier) will be more effective in treating this disease. We validated our hypothesis by docking inhibitor-bound fibrils and free fibrils together and found that the inhibitor blocks the fibril interface interaction. In addition, we have also used machine learning and graph neural network tools to propose the druggable site on the fibril surface which will help in designing inhibitors against the fibrils. The work opens new avenues for novel treatment of Parkinson’s disease and offers hope for improved therapeutic options in the future.
