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Year : 2013  |  Volume : 2  |  Issue : 3  |  Page : 139-150

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

Department of Bioinformatics, Sri Venkateswara Institute of Medical Sciences, Tirupati, Andhra Pradesh, India

Correspondence Address:
A Umamaheswari
Associate Professor & Co-ordinator of BIF, Department of Bioinformatics, SVIMS Bioinformatics Centre, Sri Venkateswara Institute of Medical Sciences, Tirupati
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Source of Support: None, Conflict of Interest: None

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Background: Alzheimer's disease (AD) is a neurodegenerative disorder in elderly persons aged above 65 years. The cleavage of amyloid precursor protein (APP) by β-secretase generates peptide fragment Aβ42, the main cause of memory and cognitive defects in AD. Therefore, elevated level of β-secretase results in accumulation of insoluble form of Aβ peptides (senile plaques) representing the protein as an attractive drug target of AD. Methods: Five recently reported β-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 β-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 β-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 β-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 β-secretase-lead1 complex was stable in all trajectories. Conclusion: Lead1 is proposed as potent inhibitor of β-secretase and thus could be considered for rational drug design against AD.

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