Discovery of selective ACAT2 antagonist via a combination strategy based on deep docking, pharmacophore modelling, and molecular dynamics simulation.

Abstract

Acyl-CoA: cholesterol acyltransferase (ACAT), a pivotal enzyme in the absorption and metabolism of cholesterol, is primarily responsible for intracellular esterification. ACAT inhibition is expected to diminish plasma lipid levels by impeding intestinal cholesterol absorption, thereby preventing the progression of atherosclerotic lesions. A previous study shows that selective inhibition of ACAT2 significantly mitigated hypercholesterolaemia and atherosclerosis in mouse models. Therefore, the need for ACAT2 selective inhibitors becomes particularly urgent. In this study, we established a multilayer virtual screening workflow and subjected biologically evaluated representative compounds to enzyme inhibitory assays. The experimental results indicated that the two compounds, STL565001 (inhibition rate at 25 μM: 75.7 ± 27.8%, selectivity = 6) and STL528213 (inhibition rate at 25 μM: 87.8 ± 12.4%, selectivity = 13), demonstrated robust activity against ACAT2, displaying greater selectivity for ACAT2 than for ACAT1. The molecular mechanisms governing the inhibitory activities of the selected compounds were systematically elucidated using computational approaches. In addition, hotspot residues in ACAT2 that are crucial for ligand binding were successfully identified. In summary, we devised a multilayer screening scheme to expeditiously and efficiently identify compounds with enzyme inhibitory activity, offering novel scaffolds for subsequent drug design centred on ACAT2 targets.