A Computational Approach towards Targeting Parkinson’s Disease
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Parkinson’s disease is one of the common complex progressive neurodegenerative diseases. This devastating neurodegenerative disease that predominately affects the dopamine producing neurons in a specific area of the brain called Substantia Nigra (SN). The lossof dopaminergic neurons in the Substantia Nigra pars compacta (SNpc) leads to the characteristic motor and non-motor symptoms. The pathophysiological changes associated with PD may start before the onset of motor features such as progressive involuntary tremors, gait, fatigue, complications in walking, speech, swallowing and may include numerous NMS that encompass behavioral changes, autonomic dysfunction, sleep disorders, depression, sensory abnormalities, and cognitive changes. The Parkinson’s disease Foundation reports that approximately 1 million Americans currently have the disease. The incidence rates (IRs) in different countries vary from 1.5 to 20 per 100,000 per year. Recently a few advances in the understanding of the pathogenesis of the disease. The autosomal dominant PD caused by the mutations in SNCA, LRRK2, and VPS35 genes and PINK1, DJ-1, and Parkin are responsible for an autosomal recessive form of PD. SNCA and PINK1 proteins have a remarkable contribution in the disease enhancement of Parkinson’s disease. It also associated with the early onset form of the disorder, which begins before the age of 50.