Integrating Fragment Screening and Covalent Chemistry to Drug DNA-Binding Proteins: RAD52 as a Case Study
Abstract Protein–DNA interfaces are central to genome maintenance but remain challenging targets for small-molecule discovery because they are often broad, polar, solvent-exposed, and lack classical druggable pockets. Here, we establish a structure-guided strategy to chemically target such interfaces by combining the fragment-based identification of DNA-mimetic binders with the covalent capture of a proximal nucleophilic residue. Using the ssDNA-binding groove of RAD52 as a representative model system, an X-ray fragment screen identified carboxylate-containing fragments that recapitulate key phosphate backbone interactions of ssDNA within the conserved DNA-binding groove. Structural analysis revealed a recurrent 2:1 fragment-binding mode that enabled fragment linking and preorganization, yielding reversible inhibitors with nanomolar biochemical activity. Subsequent exploitation of C64, located adjacent to the bound ligand, converted this reversible scaffold into potent covalent inhibitors. Optimization led to the identification of FORX-864, a beyond-rule-of-5 covalent RAD52 chemical probe with low nanomolar ssDNA-displacement activity, efficient covalent target engagement, favorable in vitro properties, and submicromolar inhibition of RAD52-dependent single-strand annealing in cells. This work provides a chemical strategy for targeting DNA-binding proteins through DNA-mimetic fragment recognition, structure-guided preorganization, and covalent stabilization while delivering validated probes to interrogate RAD52 biology.
Authors
- Sotirios K. Sotiriou (ORCID: https://orcid.org/0000-0003-4690-0568)
- Stephan Rempel (ORCID: https://orcid.org/0000-0003-3569-8229)
- Frank T. Zenke (ORCID: https://orcid.org/0000-0002-2226-3755)
- Tarig Bashir
- Hanna Kok
- Lia Mela (ORCID: https://orcid.org/0000-0002-0882-0586)
- Thanos D. Halazonetis (ORCID: https://orcid.org/0000-0001-8384-5030)
- Ronen Gabizon (ORCID: https://orcid.org/0000-0002-3626-5073)
- Olivier Querolle (ORCID: https://orcid.org/0000-0001-9115-4360)
- Alessandro Potenza
- Nir London (ORCID: https://orcid.org/0000-0003-2687-0699)
- A.J. Powell (ORCID: https://orcid.org/0000-0002-0462-2240)
- Almog Nadir
- Isabel A. Barker (ORCID: https://orcid.org/0009-0000-1207-032X)
- James E. J. Mills (ORCID: https://orcid.org/0000-0002-2567-3872)
- Giacomo G. Rossetti (ORCID: https://orcid.org/0000-0002-8272-2925)
- Luca Iacovino (ORCID: https://orcid.org/0000-0002-8720-5644)
- Andreas Goutopoulos
- Anika Kuster (ORCID: https://orcid.org/0000-0002-2521-8765)
- Nicolas Bocquet (ORCID: https://orcid.org/0000-0003-2624-660X)
- Tian Jin (ORCID: https://orcid.org/0000-0003-2168-8548)
- Ulrich Lücking (ORCID: https://orcid.org/0000-0003-2466-5800)
- Jason Clochard
- Zaixu Xu
- Irena Konstantinova
Institutions
- University of Bern (CH)
- WuXi AppTec (China) (CN)
- University Hospital of Bern (CH)
- Diamond Light Source (GB)
- Research Complex at Harwell (GB)
- Institution of Structural Engineers (GB)
Publication Details
- Journal
- Journal of the American Chemical Society
- Published
- 2026-10-08
- DOI
- https://doi.org/10.1021/jacs.6c16278
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00