COVID-19: In silico identification of potent ?-ketoamide inhibitors targeting the main protease of the SARS-CoV-2

The COVID-19 has been creating a global crisis, causing countless deaths and unbearable panic. Despite the progress made in development of vaccine, there is an urge need for discovery antivirals that may better work at different stages SARS-CoV-2 reproduction. main protease (Mpro) crucial therapeutic target due to its critical function virus replication. ?-ketoamide derivatives represent important class inhibitors against Mpro SARS-CoV. While 99% sequence similarity between SARS-CoV proteases, anti-SARS-CoV compounds have huge demonstration's prospect their effectiveness SARS-CoV-2. In this study, we applied various computational approaches investigate inhibition potency novel designed ?-ketoamide-based compounds. regard, set 21 ?-ketoamides was employed construct QSAR model, using genetic algorithm-multiple linear regression (GA-MLR), as well pharmacophore fit model. Based on GA-MLR 713 new molecules were reduced 150 promising hits, which later subject established Among compounds, best selected (3 hits) with greater score further studied via molecular docking, dynamic simulations along Absorption, distribution, metabolism, excretion, toxicity (ADMET) analysis. Our approach revealed three hit could serve potential target.