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

Abstract

In silico approach for identification of potential tetracyclic triterpenoids from mushroom as HMG-CoA reductase inhibitor Rishav Mazumder a, Deijy Choudhury a, Alekhya Sarkar b, Ashmita Ghosh c, Sudhan Debnath d, Bimal Debnath b, Rajat Ghosh a,* a In Silico Drug Design Lab., Department of Pharmacy, Tripura University (A Central University), Suryamaninagar, 799022, Tripura, India b Department of Forestry and Biodiversity, Tripura University (A Central University), Suryamaninagar, 799022, Tripura, India c Department of Biotechnology, School of Engineering and Technology, Techno India University Tripura, Maheshkhola, Anandanagar, Agartala, 799004, Tripura, India d Department of Chemistry, Netaji Subhash Mahavidyalaya, Udaipur, Tripura, 799114, India A R T I C L E I N F O Handling Editor: Prof A Angelo Azzi Keywords: Mushroom Triterpenoid HMG-CoA reductase Docking Simulation ADME A B S T R A C T 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.