分子生物学：开放获取

A Computational Approach towards Targeting Parkinson’s Disease: The Discovery of Potential Inhibitors against Alpha-Synuclein and Pten-Induced Putative Kinase 1 Protein

Abstract

Suganya Selvaraj, Shobana Sundar, Shanmughavel Piramanayagam

Parkinson’s disease (PD) is the second most common age-related neurodegenerative disease caused by the degeneration of dopaminergic neurons of the substantia nigra pars compacta (SNpc), which influences the basal ganglia network that results in a host of the motor and cognitive deficits. The autosomal dominant and recessive form of Parkinson’s disease caused by the abnormal aggregation of Alpha-synuclein and PTEN- induced putative kinase 1 protein. The present study focuses on developing lead compounds and antibody mimetic oligopeptides for inhibiting PD targets such as SNCA and PINK1. Virtual screening and docking were performed to find the best lead compounds further the docked complex were subjected to a molecular dynamics approach to predict the stability and the lowest conformation energy of the compounds. Nearly 5780 Similar compounds of carbidopa/levodopa are used to predict the potential lead molecules inhibiting the target proteins. Four potential lead compounds selected from a total of 1865 compounds based on their drug likeness properties and docking score. Biological activity prediction and statistical analysis were used for validating the inhibition of lead molecules against target protein.