β-secretase inhibitors for Alzheimer's disease: identification using pharmacoinformatics.

In this study we searched for potential β-site amyloid precursor protein cleaving enzyme1 (BACE1) inhibitors using pharmacoinformatics. A large dataset containing 7155 known BACE1 inhibitors was evaluated for pharmacophore model generation. The final model (R = 0.950, RMSD = 1.094, Q2  = 0.901, se = 0.332, [Formula: see text] = 0.901, [Formula: see text] = 0.756, sp = 0.468, [Formula: see text] = 0.667) was revealed with the importance of spatial arrangement of hydrogen bond acceptor and donor, hydrophobicity and aromatic ring features. The validated model was then used to search NCI and InterBioscreen databases for promising BACE1 inhibitors. The initial hits from both databases were sorted using a number of criteria and finally three molecules from each database were considered for further validation using molecular docking and molecular dynamics studies. Different protonation states of Asp32 and Asp228 dyad were analysed and best protonated form used for molecular docking study. Observation of the number of binding interactions in the molecular docking study supported the potential of these molecules being promising inhibitors. Values of RMSD, RMSF, Rg in molecular dynamics study and binding energies unquestionably explained that final screened molecules formed stable complexes inside the receptor cavity of BACE1. Hence, it can be concluded that the final screened six compounds may be potential therapeutic agents for Alzheimer's disease.