Application of molecular framework-based data-mining method in the search for beta-secretase 1 inhibitors through drug repurposing

摘要

Targeting beta-secretase 1, also known as beta-amyloid precursor protein-cleaving enzyme (BACE-1) for the inhibition of amyloid production, has been intensely studied in the last decades in the search for stopping Alzheimer's disease (AD) progression. The chances of finding a druggable BACE-1 inhibitor may be increased by drug repurposing, as this kind of molecules already fulfil certain requirements needed for further advancement. The study describes the development and application of a data-mining method based on molecular frameworks and descriptor values of tested BACE-1 inhibitors, suitable for filtering large compound databases, in order to find molecules with high potency against this protease. A total of 465 compounds extracted from the literature, tested against BACE-1, were analysed for finding molecular descriptor values and frameworks that ensure a high probability of strong inhibition. Resulting conclusions were used for filtering DrugBank database, containing similar to 8700 approved and experimental drugs, obtaining 26 structures characterized by four major Bemis-Murcko frameworks: 2-[3-(2-cyclohexylethyl)cyclohexyl]-decahydronaphthalene, 3-(2-cyclohexylethyl)-1,1 '-bi(cyclohexane), [5-(cyclohexylmethyl)-8-cyclopentyloctyl]cyclohexane and (3-cyclohexylcyclopentyl)cyclohexane. The compounds were further studied by molecular docking using the structure of the closed form of the enzyme, which revealed seven compounds already involved in trials targeting BACE-1 inhibition, confirming the method's specificity. The compounds that afforded the best binding energies were DB06925 (tyrosine-protein kinase inhibitor), DB12285 (Verubecestat) and DB08899 (Enzalutamide). Moreover, docking results indicated several other molecules with high in silico inhibitory potency that can be further studied for developing a potential treatment for AD. Communicated by Ramaswamy H. Sarma