A Computational Study of Green Tea Extracts and their Derivatives as Potential Inhibitors for Squalene Monooxygenase.

Abstract

According to the World Health Organisation, cardiovascular complications have been recognized as the leading course of death between 2000 and 2019. Cardiovascular complications are caused by excess LDL cholesterol in the body or arteries that can build up to form a plaque. There are drugs currently in clinical use called statins that target HMGCoA reductase. However, these drugs result in several side effects. This work investigated using computational approaches to lower cholesterol by investigating green tea extracts as an inhibitors for squalene monooxygenase (the second-rate-controlling step in cholesterol synthesis). Pharmacophore modeling was done to identify possible pharmacophoric sites based on the pIC50 values. The best hypothesis generated by pharmacophore modeling was further validated by atom-based 3D QSAR, where 70% of the data set was treated as the training set. Prior molecular docking ADMET studies were done to investigate the physiochemical properties of these molecules. Glide docking was performed, followed by molecular dynamics to evaluate the protein conformational changes. Pharmacophore results suggest that the best molecules to interact with the biological target should have at least one hydrogen acceptor (A5), two hydrogen donors (D9 and D10), and two benzene rings (R14 and R15) for green tea polyphenols and theasinensin A. ADMET result shows that all molecules in this class have low oral adsorption. Molecular docking results showed that some green tea polyphenols have good binding affinities, with most of these structures having a docking score of less than -10 kcal/mol. Molecular dynamics further illustrated that the best-docked ligands perfectly stay within the active site over a 100 ns simulation. The results obtained from this study suggest that green tea polyphenols have the potential for inhibition of squalene monooxygenase, except for theasinensin A.