Modeling and Study of Anti-coronavirus Activity of 6,7-Dimethoxyquinazoline-4(3H)-one Derivatives in Relation to SARS-COV-2 by in silico and in vitro Methods

Abstract

The pandemic of the new coronavirus infection SARS-CoV-2 (COVID-19) has put a significant strain on the healthcare system and revealed the need to develop effective medicines for the treatment of this disease. The research results presented in the article are devoted to the development of new compounds with anti-coronavirus action against SARS-CoV-2, which are derivatives of 6,7-dimethoxykinazoline-4(3H)-one. In silico, the research was carried out by the molecular docking method in the freely distributed Autodock 4.0 program. The virtual structures of the simulated compounds were constructed in the HyperChem 8.0.4 program, and the final optimization of the geometry of virtual structures was calculated in the ORCA 4.1 program using the density functional theory (UB3LYP) method and the base set 6-311G**. The main protease (identification number 7K6D) and papain-like (identification number 7LBR) protease SARS-Cov-2 were used to predict antiviral activity. In vitrostudies were carried out by multiple dilutions of the analyzed compounds using a chromogenic substrate. It follows from the results that the newly synthesized derivatives of 6,7-dimethoxyquinazoline-4(3H)-one should be considered as promising candidates for the development of new antiviral drugs. The most pronounced antiviral activity is observed in substance 8c containing a glycyltryptophan residue. It is worth noting that the proposed algorithm for searching for innovative antiviral drugs in silico agrees quite well with the results of the in vitro experiment.