Identification of potent inhibitors for β-secretase through structure based virtual screening and molecular dynamics simulations

Abstract

Background: Alzheimer's disease (AD) is a neurodegenerative disorder in elderly persons aged above 65 years. The cleavage of amyloid precursor protein (APP) by -secretase generates peptide fragment A42, the main cause of memory and cognitive defects in AD. Therefore, elevated level of -secretase results in accumulation of insoluble form of A peptides (senile plaques) representing the protein as an attractive drug target of AD. Methods: Five recently reported -secretase antagonist (thiazolidinediones, rosiglitazone, pioglitazone, SC7 and tartaric acid) structural analogs were searched from ligand info database and prepared using LigPrep. The crystal structure of -secretase was optimized using Maestro v9.2 protein preparation wizard applying optimized potential for liquid simulations (OPLS)-2005 force field. Structure based virtual screening was performed for -secretase from prepared ligands using virtual screening workflow of Maestro v9.2 and was ranked based on XP Gscore. Results: Eight lead molecules were identified to have better binding affinity (lower XP Gscore) compared to five existing -secretase antagonists and appear to have good pharmacological properties. Binding orientations of the lead molecules were in well agreement with existing inhibitors. Lead1 showed lowest XP Gscore (-10.72 Kcal/mol). Molecular dynamics (MD) simulations of -secretase-lead1 complex was stable in all trajectories. Conclusion: Lead1 is proposed as potent inhibitor of -secretase and thus could be considered for rational drug design