Computational association in parkinson's disease SNPs with brain structural and functional alterations.

Parkinson's disease (PD) is the second most prevalent neurodegenerative disorder which seriously affects human health. Worldwide, there has been a significant increase in the incidence rate of PD reported in many populations. Several epigenetic factors are associated with pathogenesis of the PD. SNCA, LRRK2, NURR1, ATP13A2, GSK3B, Parkin, PINK1, DJ-1, and UCHL1are the major genes involved and play a crucial role in the regulatory mechanisms and progression of PD. In this study, a comprehensive approach was used to identify single nucleotide polymorphisms (SNPs) that have a high deleterious effect on the nine proteins mentioned above. In this approach the SNPs of the genes listed above were subjected to more than 13 different computational tools specifically based on sequence, structural and functional analyses. The Frustrometer, NetSurf 3.0, and xProtCAS servers were used to screen the highly deleterious SNPs. Subsequently, modelling of the mutant proteins, structural analysis, STRING analysis, and binding site analysis were performed and compared with wild type proteins. Finally, the highly deleterious missense variants of the SNPs were subjected to molecular docking analysis with FDA-approved drugs for PD. The results indicate that one of the FDA drug compounds exhibits a high binding affinity across all targets. Subsequently, molecular dynamics simulations were performed on the identified compound. These results provide new insights into the genetic variants linked to PD and contribute to the exploration of future research directions in the field of PD.