Newly Identified COVID-19 Drug Candidates Based on Computational Strategies.

The COVID-19 has raised a public health catastrophe in early 2020 worldwide. Despite several approved vaccines that have repressed the pandemic and decreased the mortality rate since then, attempts to discover an effective antiviral drug have not indicated reliable results. In this research, in silico studies (virtual screening and molecular docking) were performed based on quinoline structure to identify novel drug candidates against SARS-CoV-2 before laboratory evaluations. A chemical library consisting of 548 compounds was collected from literature mining of five databases to select the best ligands interacting with three target proteins of SARS-CoV-2, including the main protease, spike protein, and chimeric receptor-binding domain in a complex of human angiotensin-converting enzyme 2. The top five compounds that presented suitable binding energy against each target protein are reported in detail for the first time. Notably, new compound N-4-(6-methyl-3-pyridinyl) phenyl)-9-acridinamine showed high affinity to all selected proteins. These identified compounds will help in speeding up the drug development against COVID-19. The emerging coronavirus disease (COVID-19) distributes promptly in the world wide. Virtual screening, molecular docking base on quinoline scaffold are able to be used to identify novel drugs candidate against COVID-19. Some new quinolone -based compounds with low energy binding were selected as the inhibitors of SARS-CoV-2 main protease site, spike protein, and RBD/ACE2. [ABSTRACT FROM AUTHOR]