Arun Ekiri Vaidyanathan Raman, Karthic Krishnan, Arun Maurya and Nandini Sarkar Pages 770 - 780 ( 11 )
Modulation of gamma-secretase cleavage of Amyloid Precursor Protein (APP) to control the level of Amyloidbeta (A-beta) peptide is one of the strategies to develop therapy for Alzheimer’s disease. Presenilin is a subunit and the catalytic core of gamma-secretase. It has Asp 257 and Asp 385 residues, which are essential for catalytic activity and thus serve as the region of interest for screening of potential gamma-secretase inhibitors. In the present study, in silico screening of drug molecules has been performed in an attempt to identify effective inhibitors of presenilin. Ligand-based pharmacophore models generated with reported inhibitor molecules have been used as query for screening from DrugBank database. Inhibitory activity (IC50) of the screening hits is predicted using a QSAR model developed. The selected molecules have been subjected to docking study against Presenilin1 C-terminal fragment that houses Asp 385 in place of presenilin, as its structure is unavailable. Finally, 46 potential inhibitor molecules were selected based on scores of scoring function and interaction with Asp 385. The selected compounds have spatial arrangement of features essential for binding to presenilin, desired inhibitory activity against processing of APP to A-beta by gamma-secretase and selective interaction with specific amino acids in ligand-protein docked complexes.
Alzheimer’s disease, drugs, gamma-secretase, IC50, inhibitors, ligand-based pharmacophore model, QSAR, screening.
Department of Biotechnology and Medical Engineering, National Institute of Technology Rourkela, Rourkela 769008, Odisha, India.