RT Journal Article SR Electronic T1 An automatic pipeline for the design of irreversible derivatives identifies a potent SARS-CoV-2 Mpro inhibitor JF bioRxiv FD Cold Spring Harbor Laboratory SP 2020.09.21.299776 DO 10.1101/2020.09.21.299776 A1 Daniel Zaidman A1 Paul Gehrtz A1 Mihajlo Filep A1 Daren Fearon A1 Jaime Prilusky A1 Shirly Duberstein A1 Galit Cohen A1 David Owen A1 Efrat Resnick A1 Claire Strain-Damerell A1 Petra Lukacik A1 Covid-Moonshot Consortium A1 Haim Barr A1 Martin A. Walsh A1 Frank von Delft A1 Nir London YR 2020 UL http://biorxiv.org/content/early/2020/09/21/2020.09.21.299776.abstract AB 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 μM. 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.Competing Interest StatementThe authors have declared no competing interest.