Interaction of small molecules with the SARS-CoV-2 papain-like protease: In silico studies and in vitro validation of protease activity inhibition using an enzymatic inhibition assay.

The SARS-CoV-2 virus is causing COVID-19, an ongoing pandemic, with extraordinary global health, social, and political implications. Currently, extensive research and development efforts are aimed at producing a safe and effective vaccine. In the interim, small molecules are being widely investigated for antiviral effects. With respect to viral replication, the papain-like (PL) and main proteases (M), are critical for processing viral replicase polypeptides. Further, the PL possesses deubiquitinating activity affecting key signalling pathways, including inhibition of interferon and innate immune antagonism. Therefore, inhibition of PL activity with small molecules is an important research direction. Our aim was to focus on identification of potential inhibitors of the protease activity of SARS-CoV-2 PL. We investigated 300 small compounds derived predominantly from our OliveNet™ library (222 phenolics) and supplemented with synthetic and dietary compounds with reported antiviral activities. An initial docking screen, using the potent and selective noncovalent PL inhibitor, GRL-0617 as a control, enabled a selection of 30 compounds for further analyses. From further in silico analyses, including docking to scenes derived from a publicly available molecular dynamics simulation trajectory (100 μs PDB 6WX4; DESRES-ANTON-11441075), we identified lead compounds for further in vitro evaluation using an enzymatic inhibition assay measuring SARS-CoV-2 PL protease activity. Our findings indicate that hypericin possessed inhibition activity, and both rutin and cyanidin-3-O-glucoside resulted in a concentration-dependent inhibition of the PL, with activity in the micromolar range. Overall, hypericin, rutin, and cyanidin-3-O-glucoside can be considered lead compounds requiring further characterisation for potential antiviral effects in appropriate model systems.