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A scalable platform to discover and characterize substrates of molecular glue degraders

Nature Biotechnology (2026) Cite this article Molecular glue degraders (MGDs) induce degradation of non-native protein substrates (neo-substrates) through the E3 ubiquitin ligase CRL4CRBN. MGD discovery is largely serendipitous, and the specificity of MGD-mediated target selection remains poorly understood. We developed an MGD discovery pipeline to identify cereblon (CRBN)–MGD neo-substrates and structural determinants of MGD-mediated degradation. […]

By deepak · August 18, 2026 · 2 min read

Nature Biotechnology
(2026) Cite this article

Molecular glue degraders (MGDs) induce degradation of non-native protein substrates (neo-substrates) through the E3 ubiquitin ligase CRL4CRBN. MGD discovery is largely serendipitous, and the specificity of MGD-mediated target selection remains poorly understood. We developed an MGD discovery pipeline to identify cereblon (CRBN)–MGD neo-substrates and structural determinants of MGD-mediated degradation.

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Kozicka, Z. & Thomä, N. Haven’t got a glue: protein surface variation for the design of molecular glue degraders. Cell Chem. Biol. 28, 1032–1047 (2021). This review describes how MGDs reprogram E3 ubiquitin ligases for the degradation of neo-substrates.

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Petzold, G. et al. Mining the CRBN target space redefines rules for molecular glue-induced neosubstrate recognition. Science 389, eadt6736 (2025). This paper investigates the structural motifs that are targeted by the CRBN–MGD interface.

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Diss, G. & Lehner, B. The genetic landscape of a physical interaction. eLife 7, e32472 (2018). This paper describes the development and application of deepPCA.

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Gainza, P. et al. Machine learning to predict de novo protein-protein interactions. Trends Biotechnol. 43, 3056–3070 (2025). This review describes computational prediction of PPIs that have no precedence in nature.

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Source: Read the original article on www.nature.com