MOLECULAR-LEVEL COMPARATIVE ANALYSIS ON HUB-PROTEINS OF PARKINSON’S DISEASE WITH SELECTED SYNTHETIC DRUGS USING AN IN-SILICO APPROACH

Physical interactions between proteins are cardinal to biological processes. To restore their function, proteins must interact with one another. Hub proteins are densely interconnected proteins with a wide range of biological significance and are also to blame for several illnesses, including cancer, autoimmune disorders, and neurodegenerative diseases. The most prevalent of these is Parkinson’s disease. SNCA, alpha synucelin is a hub protein that is the main cause of this disease; along with this DJ 1 and Parkin also responsible for Parkinson’s disease. Through this study, we performed a molecular-level comparative analysis on hub-proteins of Parkinson’s disease with selected synthetic drugs using the in-silico approach. The binding energy and complex energy identified the better efficacy of the drug. The Lipinski rule of filtering and the ADMET pharmacological parameters were satisfied by seven out of the twelve medicines. Levodopa, among these medications, had superior effectiveness with 4RKW and 5C32 in both approaches. Better Lib Dock scores, binding energies, and complex energies with 4RKW were displayed by safinamide. The molecular dynamic modelling further validated the binding stability of the 4RKW-safinamide complex. The amount of GC content was also analyzed with the aid of a Python programme to establish the stability of DJ1.