From noncovalent fragments to covalent WRN inhibitors

Last week we described the discovery and early optimization of noncovalent inhibitors against the the DNA helicase WRN, an interesting oncology target both for its conformational flexibility as well as a ‘synthetic lethal’ approach to cancer drugs. Today we continue the theme with a Bioorg. Med. Chem. Lett. paper from Geoffrey Smith and colleagues at CHARM Therapeutics.

 

At the time the project began, no specific WRN inhibitors had been reported, but a crystal structure of the ADP-bound form of the protein had been published. The computational tool Fpocket, which we wrote about here, was used to identify several ligandable pockets.

 

To find actual ligands, the researchers crystallographically screened a library of 860 "poised" fragments from Enamine and used PanDDA (see here) to identify binders, even those with low occupancies. Several ligands occupied pockets that had been identified by Fpocket. More interestingly, five fragments bound in a previously cryptic site that had not been predicted. This pocket was formed by rotation of two phenylalanine residues as well as peptide backbone movements, consistent with sites able to support high affinity ligands, as we discussed in 2024. Thus, the focus turned to ligands that bind here.

 

Because of its low occupancy in the crystal, the orientation of compound 3 was ambiguous, so the researchers turned to a machine-learning-based protein-ligand co-folding algorithm called DragonFold. This revealed that the fragment binds in close proximity to a cysteine residue, C727, known to be reactive. Scaffold hopping and addition of a covalent warhead led to compound 4d. While the initial compound 3 showed no activity in a WRN helicase assay, compound 4d showed micromolar activity. Moreover, a crystal structure revealed binding to C727. Further SAR led to molecules such as compound 9b, the most potent WRN inhibitor reported in the paper.

 

Compounds were also tested against the closely related helicase Bloom syndrome protein, or BLM, and most of them were active, though the SAR varied between WRN and BLM. The activity against BLM is odd given that the residue corresponding to C727 is a serine, but the researchers note that the molecules might bind to other cysteine residues in BLM. Although no chemical reactivity data are provided for the ligands, I suspect they are somewhat reactive.

 

Several important lessons can be drawn from this brief paper. The fact that an experimental screen was able to identify cryptic pockets missed in a computational screen justifies empirical approaches. The identification of these pockets is all the more impressive given that pre-formed crystals were sufficiently flexible to undergo significant conformational changes. But computational approaches did prove their utility in refining the binding mode of the ligand. And finally, this is another example of appending a covalent warhead onto a non-covalent ligand.

 

Next week we’ll conclude this WRN trilogy with a covalent-first example.