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Small-molecule inhibitors that target protein-protein interactions in the RAD51 family of recombinases.

ABSTRACT: The development of small molecules that inhibit protein-protein interactions continues to be a challenge in chemical biology and drug discovery. Herein we report the development of indole-based fragments that bind in a shallow surface pocket of a humanised surrogate of RAD51. RAD51 is an ATP-dependent recombinase that plays a key role in the repair of double-strand DNA breaks. It both self-associates, forming filament structures with DNA, and interacts with the BRCA2 protein through a common "FxxA" tetrapeptide motif. We elaborated previously identified fragment hits that target the FxxA motif site and developed small-molecule inhibitors that are approximately 500-fold more potent than the initial fragments. The lead compounds were shown to compete with the BRCA2-derived Ac-FHTA-NH2 peptide and the self-association peptide of RAD51, but they had no effect on ATP binding. This study is the first reported elaboration of small-molecular-weight fragments against this challenging target.

SUBMITTER: Scott DE

PROVIDER: S-EPMC4506530 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature

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Small-molecule inhibitors that target protein-protein interactions in the RAD51 family of recombinases.

Scott Duncan E DE Coyne Anthony G AG Venkitaraman Ashok A Blundell Tom L TL Abell Chris C Hyvönen Marko M

ChemMedChem 20141202 2

The development of small molecules that inhibit protein-protein interactions continues to be a challenge in chemical biology and drug discovery. Herein we report the development of indole-based fragments that bind in a shallow surface pocket of a humanised surrogate of RAD51. RAD51 is an ATP-dependent recombinase that plays a key role in the repair of double-strand DNA breaks. It both self-associates, forming filament structures with DNA, and interacts with the BRCA2 protein through a common "Fx ...[more]

PMID: 25470112

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Project description:Protein-protein interactions play important roles in virtually all cellular processes, making them enticing targets for modulation by small-molecule therapeutics: specific examples have been well validated in diseases ranging from cancer and autoimmune disorders, to bacterial and viral infections. Despite several notable successes, however, overall these remain a very challenging target class. Protein interaction sites are especially challenging for computational approaches, because the target protein surface often undergoes a conformational change to enable ligand binding: this confounds traditional approaches for virtual screening. Through previous studies, we demonstrated that biased "pocket optimization" simulations could be used to build collections of low-energy pocket-containing conformations, starting from an unbound protein structure. Here, we demonstrate that these pockets can further be used to identify ligands that complement the protein surface. To do so, we first build from a given pocket its "exemplar": a perfect, but nonphysical, pseudoligand that would optimally match the shape and chemical features of the pocket. In our previous studies, we used these exemplars to quantitatively compare protein surface pockets to one another. Here, we now introduce this exemplar as a template for pharmacophore-based screening of chemical libraries. Through a series of benchmark experiments, we demonstrate that this approach exhibits comparable performance as traditional docking methods for identifying known inhibitors acting at protein interaction sites. However, because this approach is predicated on ligand/exemplar overlays, and thus does not require explicit calculation of protein-ligand interactions, exemplar screening provides a tremendous speed advantage over docking: 6 million compounds can be screened in about 15 min on a single 16-core, dual-GPU computer. The extreme speed at which large compound libraries can be traversed easily enables screening against a "pocket-optimized" ensemble of protein conformations, which in turn facilitates identification of more diverse classes of active compounds for a given protein target.

Dataset Information

Small-molecule inhibitors that target protein-protein interactions in the RAD51 family of recombinases.

Publications

Small-molecule inhibitors that target protein-protein interactions in the RAD51 family of recombinases.

Similar Datasets

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