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

Abstract

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.

Keywords: COVID-19; DOCKovalent; M(pro); SARS-CoV-2; computer-aided drug discovery; covalent docking; covalent inhibitors; irreversible inhibitors.

Graphical abstract

Figure 1

An overview of the covalentizer computational protocol The protocol comprises four consecutive steps. (A) Fragmentation: the molecule is broken and divided into fragments (red arrows) using synthetically accessible bonds (Lewell et al., 1998). Murcko scaffolds (Bemis and Murcko, 1996) of the fragments (blue arrows) are also added to the list of fragments. (B) Electrophilic diversification: for each substructure, a library of potential electrophilic analogs is generated, a few hundred compounds in size. We used four kinds of nitrogen-based electrophiles ranging in reactivity: vinyl sulfones, chloroacetamides, acrylamides, and propynamides. We also considered various linkers between the fragment and the electrophile. (C) Docking: the target structure is then docked against its appropriate analog library using all available cysteine rotamers. Finally, RMSD calculation: for each docked compound, an RMSD is calculated between the MCS (maximal common substructure) of the reversible compound and the covalent analog found by covalentizer. We show examples of predictions with increasing RMSDs, for binders of (1) nitrate reductase from Ulva prolifera (PDB: 5YLY; You et al., 2018), (2) human mineralocorticoid receptor (PDB: 5HCV; Lotesta et al., 2016), and (3) human progesterone receptor (PDB: 1A28; Williams and Sigler, 1998).

Figure 2

Covalentizer successfully recapitulates known covalent kinase inhibitors Examples of covalent kinase inhibitors (green) for which covalentizer was able to find a substructure match (magenta) under the 1.5 Å threshold. (A) ERK2, PDB: 4ZZO (Ward et al., 2015). (B) EphB3, PDB: 5L6P (Kung et al., 2016). (C) EGFR (T790M), PDB: 4I24 (Gajiwala et al., 2013). (D) JAK3, PDB: 5TOZ (Telliez et al., 2016). The electrophiles span acrylamides (A, D), a substituted acrylamide (C) and chloroacetamide (B).

Figure 3

PDB-wide application of covalentizer identifies candidate irreversible inhibitors for more than 1,500 structures (A) We filtered the PDB for structures that had only protein chains (no DNA/RNA), and contained a small molecule of at least 300 Da. This threshold was set to ensure some minimal initial fit/binding affinity to the target, as well as to filter out non-ligand small molecules, such as crystallization reagents. We used a PyMOL-based script to filter only the structures in which at least one ligand atom is <6 Å away from the sulfur atom of a cysteine residue. This cysteine also has to be free (no disulfide or other covalent modifications). After running the covalentizer protocol and filtering only for results with <1.5 Å RMSD of the MCS between the reversible ligand and the covalent analog generated by covalentizer, there were 1,553 structures for which at least one such prediction was obtained. (B) The top 1% of results have an RMSD under 0.5 Å; 23% are between 0.5 and 1 Å, and 76% are between 1 and 1.5 Å. (C) The distribution of the four electrophiles used is balanced, with 29% chloroacetamides, 27% acrylamides, 24% vinylsulfones, and 20% propynamides.

Figure 4

Prospective prediction identifies irreversible kinase inhibitors (A) Chemical structures and in vitro kinase activity assay IC₅₀ values for nine prospective covalentizer predictions. See Figure S2 for the parent compounds, pose predictions, and RMSD values. (B) Dose-response curves for each of the nine compounds. Each compound was tested against its corresponding target kinase. For compound 1, n = 3; for compounds 2, 4, 5, and 9, n = 2; error bars represent standard deviation. (C) Deconvoluted mass spectra obtained by intact protein LC/MS of recombinant ERK2 (10 μM) incubated with 100 μM of 1 or 2 for 3 h at room temperature, shows full irreversible binding by both compounds.

Figure 5

Computational prediction and experimental validation of an irreversible SARS-CoV-2 M^pro inhibitor (A) The covalentizer prediction of 10 (magenta) overlaid on the non-covalent compound it is based on (ML188 (Jacobs et al., 2013); green; PDB: 3V3M). The protocol suggested to substitute the furanyl moiety of ML188 with an acrylamide to bind the catalytic cysteine. The RMSD between the covalent fragment and the original reversible inhibitor is 0.65 Å. (B) The crystal structure of 12, one of the covalent analogs of 10 (PDB: 5RH5; cyan) overlaid on ML188 (green). (C) Overlay of all the 12 crystal structures of compound 10 analogs, all exhibiting the same predicted binding mode. PDB: 5RGT, 5RH5, 5RH6, 5RH7, 5RH9, 5RL0, 5RL1, 5RL2, 5RL3, 5RL4, 5RL5, and 7NW2. For individual structures see Data S3F. (D) The chemical structures of ML188 and 10. (E) Chemical structure of Ugi compounds exploring the S3 pocket, with the R group that is shown in the crystal structure in (B). (F) Deconvoluted mass spectra obtained by intact protein LC/MS of recombinant SARS-CoV-2 M^pro 2 μM incubated with 2–200 μM 10 for 1.5 h at room temperature. We should note we did not detect multiple labeling events by this compound. (G) Further analogs of 10 with their associated biochemical potencies. (H) The dose-response curves for the seven compounds shown in (G) (n = 2, error bars represent standard deviation).