Structure-based lead optimization of peptide-based vinyl methyl ketones as SARS-CoV-2 main protease inhibitors.

Despite several major achievements in the development of vaccines and antivirals, the fight against SARS-CoV-2 and the health problems accompanying COVID-19 are still ongoing. SARS-CoV-2 main protease (Mpro), an essential viral cysteine protease, is a crucial target for the development of antiviral agents. A virtual screening analysis of in-house cysteine protease inhibitors against SARS-CoV-2 Mpro allowed us to identify two hits (i.e., 1 and 2) bearing a methyl vinyl ketone warhead. Starting from these compounds, we herein report the development of Michael acceptors targeting SARS-CoV-2 Mpro, which differ from each other for the warhead and for the amino acids at the P2 site. The most promising vinyl methyl ketone-containing analogs showed sub-micromolar activity against the viral protease. SPR38, SPR39, and SPR41 were fully characterized, and additional inhibitory properties towards hCatL, which plays a key role in the virus entry into host cells, were observed. SPR39 and SPR41 exhibited single-digit micromolar EC50 values in a SARS-CoV-2 infection model in cell culture.

Lead Discovery of SARS-CoV-2 Main Protease Inhibitors through Covalent Docking-Based Virtual Screening.

During almost all 2020, coronavirus disease 2019 (COVID-19) pandemic has constituted the major risk for the worldwide health and economy, propelling unprecedented efforts to discover drugs for its prevention and cure. At the end of the year, these efforts have culminated with the approval of vaccines by the American Food and Drug Administration (FDA) and the European Medicines Agency (EMA) giving new hope for the future. On the other hand, clinical data underscore the urgent need for effective drugs to treat COVID-19 patients. In this work, we embarked on a virtual screening campaign against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Mpro chymotrypsin-like cysteine protease employing our in-house database of peptide and non-peptide ligands characterized by different types of warheads acting as Michael acceptors. To this end, we employed the AutoDock4 docking software customized to predict the formation of a covalent adduct with the target protein. In vitro verification of the inhibition properties of the most promising candidates allowed us to identify two new lead inhibitors that will deserve further optimization. From the computational point of view, this work demonstrates the predictive power of AutoDock4 and suggests its application for the in silico screening of large chemical libraries of potential covalent binders against the SARS-CoV-2 Mpro enzyme.