Harnessing computational tools for drug discovery: An integrated computational approach to identify potential BACE-1 inhibitors

Abstract

The hallmark of Alzheimer's disease (AD), a progressive neurodegenerative condition, is the buildup of amyloid-beta (Aβ) plaque, which is mainly caused by β-secretase 1 (BACE-1) activity. BACE-1 inhibition is a potentially effective treatment strategy to lower the progression of AD. In order to find possible BACE-1 inhibitors using a drug repurposing technique, this study uses an integrated computational approach that includes pharmacophore modelling, virtual screening, molecular docking, MM-GBSA, molecular dynamics (MD) simulations, in-silico ADMET profiling, and PBPK modelling. A pharmacophore model, was created with known BACE-1 inhibitors to enable virtual screening of both novel and FDA-approved chemical libraries. Top candidates with good free energy scores and strong binding affinities were found using molecular docking and MM-GBSA calculations. The stability of shortlisted Hits inside the BACE-1 active site was further validated using MD simulations, which showed that some of the important interactions were maintained across a period of 50ns. ADMET and PBPK studies predicted favorable pharmacokinetic and safety profiles for the shortlisted hits, particularly for B2 and B9. These findings identify potential candidates for future experimental validation, offering an inexpensive approach for identification of compounds as potential BACE-1 inhibitors.