Shalini John

Publications

2 Discovery of Human HMG-Coa Reductase Inhibitors Using Structure-Based Pharmacophore Modeling Combined with Molecular Dynamics Simulation Methodologies

Authors: Keun Woo Lee, Minky Son, Chanin Park, Ayoung Baek, Shalini John

Abstract:

3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) catalyzes the conversion of HMG-CoA to mevalonate using NADPH and the enzyme is involved in rate-controlling step of mevalonate. Inhibition of HMGR is considered as effective way to lower cholesterol levels so it is drug target to treat hypercholesterolemia, major risk factor of cardiovascular disease. To discover novel HMGR inhibitor, we performed structure-based pharmacophore modeling combined with molecular dynamics (MD) simulation. Four HMGR inhibitors were used for MD simulation and representative structure of each simulation were selected by clustering analysis. Four structure-based pharmacophore models were generated using the representative structure. The generated models were validated used in virtual screening to find novel scaffolds for inhibiting HMGR. The screened compounds were filtered by applying drug-like properties and used in molecular docking. Finally, four hit compounds were obtained and these complexes were refined using energy minimization. These compounds might be potential leads to design novel HMGR inhibitor.

Keywords: molecular dynamics simulation, Anti-hypercholesterolemia drug, HMGR inhibitor, Structure-based pharmacophore modeling

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1 Molecular Dynamic Simulation and Receptor-based Pharmacophore Modeling on Human Renin for Discovery of Novel Inhibitors

Authors: Keun Woo Lee, Minky Son, Chanin Park, Shalini John, Sundarapandian Thangapandian, Yuno Lee, Young-sik Sohn

Abstract:

Hypertension is characterized with stress on the heart and blood vessels thus increasing the risk of heart attack and renal diseases. The Renin angiotensin system (RAS) plays a major role in blood pressure control. Renin is the enzyme that controls the RAS at the rate-limiting step. Our aim is to develop new drug-like leads which can inhibit renin and thereby emerge as therapeutics for hypertension. To achieve this, molecular dynamics (MD) simulation and receptor-based pharmacophore modeling were implemented, and three rennin-inhibitor complex structures were selected based on IC50 value and scaffolds of inhibitors. Three pharmacophore models were generated considering conformations induced by inhibitor. The compounds mapped to these models were selected and subjected to drug-like screening. The identified hits were docked into the active site of renin. Finally, hit1 satisfying the binding mode and interaction energy was selected as possible lead candidate to be used in novel renin inhibitors.

Keywords: molecular dynamics simulation, Structure-based pharmacophore modeling, Renin inhibitor

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