Abstract

Aims: A pharmacophore based in silico study for screening out Human Acyl-CoA cholesterol acyltransferase (ACAT) inhibitors.

Background: Human Acyl-CoA cholesterol acyltransferase (ACAT) plays an important role in catalysis of reaction which converts cholesterol into cholesteryl esters and long-chain fatty acyl coenzyme A. The inhibition of ACAT has therapeutically potential roles in hypercholestrolemia, atherosclerosis and coronary heart disease.

Objective: As no 3D structure of Human Acyl-CoA cholesterol acyltransferase (ACAT) is reported, ligand based design of the inhibitors is required that which converts cholesterol into cholesteryl esters.

Methods: For better understanding of essential chemical features for ACAT inhibition and identifying novel inhibitors, a three-dimensional (3D) chemical-feature-based quantitative QSAR pharmacophore model for available ACAT inhibitors have been developed for first time using Discovery Studio 2.5.

Results: The best model (Hypo1) having lowest total cost (84.14), highest cost difference (69.67), highest correlation coefficient (0.94), and lowest RMS (1.15Å), constitutes of one hydrogen bond acceptor, one hydrogen bond donor, two hydrophobic aromatic and one hydrophobic aliphatic feature. The pharmacokinetic properties and toxicities of top 10 active hits obtained from virtual screening were predicted for ZINC33073636 and ZINC33073625.

Conclusion: These studies thus provide a pharmacophore model, which will be helpful in designing novel human ACAT inhibitors.

Keywords: Hypercholesterolemia, ACAT, pharmacophore, virtual screening, ADMET, PCA.

Graphical Abstract