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

Journal article

Designing covalent inhibitors is increasingly important, although it remains challenging. Here, we present covalentizer, a computational pipeline for identifying irreversible inhibitors based on structures of targets with non-covalent binders. Through covalent docking of tailored focused libraries, we identify candidates that can bind covalently to a nearby cysteine while preserving the interactions of the original molecule. We found ∼11,000 cysteines proximal to a ligand across 8,386 complexes in the PDB. Of these, the protocol identified 1,553 structures with covalent predictions. In a prospective evaluation, five out of nine predicted covalent kinase inhibitors showed half-maximal inhibitory concentration (IC₅₀) values between 155 nM and 4.5 μM. Application against an existing SARS-CoV M^pro reversible inhibitor led to an acrylamide inhibitor series with low micromolar IC₅₀> values against SARS-CoV-2 M^pro. The docking was validated by 12 co-crystal structures. Together these examples hint at the vast number of covalent inhibitors accessible through our protocol.

Authors: Zaidman, D; Gehrtz, P; Filep, M; Fearon, D; Gabizon, R

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Cell Press
• Journal: Cell Chemical Biology
• Volume: 28
• Issue: 12
• Pages: 1795-1806
• Place of publication: United States
• Publication date: 2021-06-25
• Acceptance date: 2021-05-27
• DOI: 10.1016/j.chembiol.2021.05.018
• EISSN: 2451-9448
• ISSN: 2451-9456
• Pmid: 34174194
• Language: English
• Keywords: irreversible inhibitors; covalent inhibitors; covalent docking; computer-aided drug discovery; DOCKovalent; COVID-19; SARS-CoV-2; Mpro