Monday, June 28, 2021

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

Zaidman, Daniel; Gehrtz, Paul; Filep, Mihajlo; Fearon, Daren; Gabizon, Ronen; Douangamath, Alice; Prilusky, Jaime; Duberstein, Shirly; Cohen, Galit; Owen, C. David ; Resnick, Efrat; Strain-Damerell, Claire ; Lukacik, Petra ; Barr, Haim; Walsh, Martin A.; von Delft, Frank; London, Nir

Cell Chemical Biology, 2021


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 Mpro reversible inhibitor led to an acrylamide inhibitor series with low micromolar IC50 values against SARS-CoV-2 Mpro. The docking was validated by 12 co-crystal structures. Together these examples hint at the vast number of covalent inhibitors accessible through our protocol.

Oncogenic KRAS G12C: Kinetic and Redox Characterization of Covalent Inhibition

Minh V. Huynh, Derek Parsonage, Tom E. Forshaw, Venkat R. Chirasani, G. Aaron Hobbs, Hanzhi Wu, Jingyun Lee, Cristina M. Furdui, Leslie B. P...