GlueFinder: A Data-Driven Framework for the Rational Discovery of Molecular Glues
Jeffrey Skolnick, Bharath Srinivasan, Hongyi Zhou
TL;DR
GlueFinder is a new computational tool that helps discover molecular glues by identifying suitable binding sites on proteins, enabling the design of targeted protein degraders.
Contribution
GlueFinder introduces a systematic, data-driven platform for identifying ligandable sites for molecular glue discovery, independent of legacy scaffolds or specific ligases.
Findings
GlueFinder predicted candidate glues recruiting 24, 111, and 148 distinct E3 ligases to EGFR, HER2, and KRAS, respectively.
The tool successfully promotes non-native EGFR complexes with diverse proteins, suggesting potential for novel ternary assemblies.
Validation on benchmark structures confirms GlueFinder's effectiveness in identifying glue-mediated complex formation sites.
Abstract
Molecular glues drive targeted protein degradation by stabilizing ternary complexes between proteins of interest and E3 ubiquitin ligases, but their rational design has lagged due to a limited understanding of the rules for interface recognition and an overreliance on a few ligases (e.g., VHL or Cereblon). We introduce GlueFinder, a systematic, unbiased platform that leverages structural bioinformatics to mine the Protein Data Bank for ligand-binding pockets adjacent to the protein interface which are ligandable sites that can nucleate glue-mediated complex formation. After validating its performance on a benchmark of experimentally solved dimeric structures with known and predicted glues, we applied GlueFinder to three therapeutically important targets, EGFR, HER2, and KRAS, and predicted candidate glues that recruit 24, 111, and 148 distinct E3 ligases to these targets, respectively.…
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Taxonomy
TopicsProtein Degradation and Inhibitors · Click Chemistry and Applications · Biochemical and Structural Characterization