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bioRxiv · 10.1101/2025.10.17.683126

GlueFinder: A Data-Driven Framework for the Rational Discovery of Molecular Glues

Skolnick, J.·Srinivasan, B.·Zhou, H.
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Abstract

Molecular glues can drive targeted protein degradation by stabilizing ternary complexes between proteins of interest and E3 ubiquitin ligases, but rational design has lagged due to limited 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 near protein-protein interfaces 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. We further demonstrate that GlueFinder can promote the formation of non-native EGFR complexes, possibly enabling ternary assemblies that would not form on their own. Together, these results establish a general, computation-guided strategy for molecular glue discovery that decouples design from legacy degrader scaffolds and specific ligase dependencies, expands the usable E3 ligase repertoire, and enables rational targeting of interfacial binding pockets. GlueFinder thus broadens both the scope and precision of targeted protein degradation and moves the field toward mechanism-driven, systematic glue development across diverse therapeutic contexts. SignificanceMolecular glues are small molecules that destroy disease-causing proteins by helping them attach to cellular disposal machinery. However, current glue discovery depends on a few known ligases and lacks clear design rules. GlueFinder provides a general, computation-guided method that scans protein structures to find pockets near interfaces where glues can act. Applied to key targets such as EGFR, HER2, and KRAS, it predicts glues that connect many different ligases and even create new protein complexes. By revealing where and how glues can work, GlueFinder expands the range of degradable proteins and accelerates the rational design of future therapeutics.

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Skolnick, J., Srinivasan, B., Zhou, H.. 2025-10-17. GlueFinder: A Data-Driven Framework for the Rational Discovery of Molecular Glues. https://doi.org/10.1101/2025.10.17.683126

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