Comprehensive analysis of non-synonymous SNPs related to Parkinson’s disease and molecular dynamics simulation of PRKN mutants

Abstract

Parkinson’s disease (PD) is associated with a mutation in the PRKN (Parkin RBR E3 Ubiquitin Protein Ligase). PRKN functions as maintaining dopamine (DA) neuronal homeostasis and homeostasis dysfunction, which play an important role in early PD onset. The main objective behind this work is to identify PRKN deleterious single nucleotide polymorphism (SNPs) by computational analysis and implement molecular dynamic simulation (MDS) to study the structural and functional properties of native and mutant proteins. We found A46T, I23T, C212Y, D243N, E28G, G359D, P37L, Q34R, R256C, R275W, R366W, and R402C as the most delirious and disease-linked by using different bioinformatics tools such as ANNOVAR (SIFT & POLYPHEN2) annotation, SNPs & GO, PROVEAN, and I-Mutant3.0. To understand protein functionality and atomic arrangement in 3-D space, the comparative modeling of native and mutant PRKN protein (A46T, I23T, C212Y, D243N, E28G, G359D, P37L, Q34R, R256C, R275W, R366W, and R402C) was performed with standalone MODELLER 9.15 program. Finally, MDS analysis was done by using the GROMACS 5.1.5 comprehensive package to study the structural stability and dynamic perturbations in native and mutant PRKN proteins. MDS analysis shows more flexibility in native structures in comparison to mutant structures. Mutant structures show structural perturbation and result in loss of PRKN protein function. The findings of this study might assist wet-lab studies to create effective pharmacological treatments against PD targeting PRKN.

Keywords

• Parkinson’s Disease PRKN
• Non-synonymous SNPs
• Molecular dynamic simulation
• Annovar
• Mutation