Rapid structure-based Identification of Potential SARS-CoV-2 Main Protease Inhibitors

Abstract

The COVID-19 outbreak has thrown the world into an unprecedented crisis. It has posed a challenge to scientists around the globe who are working tirelessly to combat this pandemic. We herein report a set of molecules that may serve as possible inhibitors of the SARS-CoV-2 main protease. To identify these molecules, we followed a combinatorial structure-based strategy, which includes high-throughput virtual screening, molecular docking and WaterMap calculations. The study was carried out using Protein Data Bank structures 5R82 and 6Y2G. DrugBank, Enamine, Natural product and Specs databases, along with a few known antiviral drugs, were used for the screening. WaterMap analysis aided in the recognition of high-potential molecules that can efficiently displace binding-site waters. This study may help the discovery and development of antiviral drugs against SARS-CoV-2.

In Silico Design of New Dual Inhibitors of SARS-CoV-2 MPRO through Ligand- and Structure-Based Methods

“…QSAR and/or pharmacophore modelling approaches combined with molecular docking, MD simulations and free binding energy MM/PBSA allowed for the design of new derivatives with promising SARS-CoV-2 M PRO inhibition activity [23][24][25][26][27][28][29][30][31][32].…”

“…Furthermore, from this point of view, it should be evidenced as the integration of non-covalent and covalent docking protocols leading to compounds with optimal interaction both with the catalytic residue and to the other clefts in the binding site [25,35,36]. In fact, in the past three years, a great number of Structure-Based Virtual Screenings (SBVSs) facilitated the identification of some efficacious SARS-CoV-2 M PRO covalent and/or noncovalent inhibitors; overall, this was possible thankfully to the large database of solved SARS-CoV-2 M PRO crystallographic structures deposited in the Protein Data Bank (PDB) [25,27,30,31].…”