In silico identification and molecular dynamic simulations of derivatives of 6,6-dimethyl-3-azabicyclo[3.1.0]hexane-2-carboxamide against main protease 3CLpro of SARS-CoV-2 viral infection

Abstract

Context: The unavailability of target-specific antiviral drugs for SARS-CoV-2 viral infection kindled the motivation to virtually design derivatives of 6,6-dimethyl-3-azabicyclo[3.1.0]hexane-2-carboxamide as potential antiviral inhibitors against the concerned virus. The molecular docking and molecular dynamic results revealed that the reported derivatives have a potential to act as antiviral drug against SARS-CoV-2. The reported hit compounds can be considered for in vitro and in vivo analyses.

Methods: Fragment-based drug designing was used to model the derivatives. Furthermore, DFT simulations were carried out using B3LYP/6-311G** basis set. Docking simulations were performed by using a combination of empirical free energy force field with a Lamarckian genetic algorithm under AutoDock 4.2. By the application of AMBER14 force field and SPCE water model, molecular dynamic simulations and MM-PBSA were calculated for 100 ns.

Keywords: Boceprevir; Main protease 3CLpro; Molecular docking; Molecular dynamic.