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Alzheimer&#x2019;s disease (AD) is one of the most prominent neurodegenerative disorders, particularly in elder persons over 65 age. It is characterized by progressive cognitive deterioration together with declining activities. Amyloid precursor protein (APP) cleaves at A-beta (A&#x3b2;) peptide by rate limiting factor of Beta-site APP cleaving enzyme (BACE-1) in amyloidogenic pathway. Elevated level of BACE-1 leads to the accumulation of an insoluble form of A&#x3b2; peptides (Senile Plaques), an important hallmark in the pathogenesis of Alzheimer disease. Five published inhibitors of BACE-1, thiazolidinediones, rosiglitazone, pioglitazone, Sc7 and tartaric acid are available with poor pharmacological properties and intolerable side effects. Therefore, a computational approach was undertaken to design novel inhibitors against human BACE-1. The crystal structure of human BACE-1 was retrieved from the protein data bank and optimized by applying OPLS force field in Maestro v9.2. An ASINEX database (115,000 ligands) was downloaded and compounds were prepared using LigPrep. The optimized ligand dataset was docked into the BACE-1 through sequential application of Glide HTVS, SP and XP methods that penalizes more stringently for minor steric classes subsequently. Finally, seven leads were reported and ranked based on XPGscore with better binding affinity and good pharmacological properties compared with existing inhibitors. Six leads were proposed for human BACE-1. Among the six, lead 1, with XPGscore -8.051Kcal/mol, would be intriguing for rational drug design against Alzheimer&#x2019;s disease and would be highly encouraging for future Alzheimer&#x2019;s therapy if tested in animal models

Docking studies to explore novel inhibitors against human beta-site APP cleaving enzyme (BACE-1) involved in Alzheimer’s disease