Conserved interactions required for in vitro inhibition of the main protease of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)

The COVID-19 pandemic caused by the SARS-CoV-2 requires a fast development of antiviral drugs. SARS-CoV-2 viral main protease (Mpro, also called 3C-like protease, 3CLpro) is a potential target for drug design. Crystal and co-crystal structures of the SARS-CoV-2 Mpro have been solved, enabling the rational design of inhibitory compounds. In this study we analyzed the available SARS-CoV-2 and the highly similar SARS-CoV-1 crystal structures. We identified within the active site of the Mpro, in addition to the inhibitory ligands interaction with the catalytic C145, two key H-bond interactions with the conserved H163 and E166 residues. Both H-bond interactions are present in almost all co-crystals and are likely to occur also during the viral polypeptide cleavage process as suggested from docking of the Mpro cleavage recognition sequence. We screened in silico a library of 6,900 FDA-approved drugs (ChEMBL) and filtered using these key interactions and selected 29 non-covalent compounds predicted to bind to the protease. Additional screen, using DOCKovalent was carried out on DrugBank library (11,414 experimental and approved drugs) and resulted in 6 covalent compounds. The selected compounds from both screens were tested in vitro by a protease activity inhibition assay. Two compounds showed activity at the 50M concentration range. Our analysis and findings can facilitate and focus the development of highly potent inhibitors against SARS-CoV-2 infection.

An automatic pipeline for the design of irreversible derivatives identifies a potent SARS-CoV-2 Mpro inhibitor.

Designing covalent inhibitors is a task of increasing importance in drug discovery. Efficiently designing irreversible inhibitors, though, remains challenging. Here, we present covalentizer, a computational pipeline for creating irreversible inhibitors based on complex structures of targets with known reversible binders. For each ligand, we create a custom-made focused library of covalent analogs. We use covalent docking, to dock these tailored covalent libraries and to find those that can bind covalently to a nearby cysteine while keeping some of the main interactions of the original molecule. We found ~11,000 cysteines in close proximity to a ligand across 8,386 protein-ligand complexes in the PDB. Of these, the protocol identified 1,553 structures with covalent predictions. In prospective evaluation against a panel of kinases, five out of nine predicted covalent inhibitors showed IC50 between 155 nM - 4.2 M. Application of the protocol to an existing SARS-CoV-1 Mpro reversible inhibitor led to a new acrylamide inhibitor series with low micromolar IC50 against SARS-CoV-2 Mpro. The docking prediction was validated by 11 co-crystal structures. This is a promising lead series for COVID-19 antivirals. Together these examples hint at the vast number of covalent inhibitors accessible through our protocol.