In silico approach for identification of potential tetracyclic triterpenoids from mushroom as HMG-CoA reductase inhibitor

Abstract

Cardiovascular disease is estimated to be responsible for one-third of all global deaths annually. It occurs mostly due to hyperlipidemia, a condition where excessive cholesterol deposits in blood vessels. A favorable target for treating hyperlipidemia involves the crucial role of inhibition of a specific enzyme known as 3-Hydroxy-3-methylglutaryl coenzyme A reductase (HMG-CoA reductase). The primary goal of this present study is to identify potential HMG-CoA reductase inhibitors containing tetracyclic triterpene nucleus derived from mushrooms. A library of 86 myco-constituents bearing a tetracyclic triterpene scaffold was prepared and screened to identify potential HMG-CoA reductase inhibitors targeting proteins 1HW8 and 1HW9. For this purpose, molecular docking, ADME prediction, and molecular dynamics (MD) simulation studies were performed on this in-house prepared database. The virtual screening results exhibited M_02(c) as the best hit with promising SP Glide scores compared to standard statin drugs. In order to assess the stability and interactions, a 100 ns MD simulation was performed. Further, M_02(c) was also analysed for MMGBSA binding energy to access and validate the thermodynamic stability of the protein-ligand complex. The results of this study revealed that M_02(c) is a promising hit molecule and may emerge as a potent HMG-CoA reductase inhibitor in preventing and treating hyperlipidemia.