AI-Guided Path to VAV1-Targeting Molecular Glues
- VAV1 is a hematopoietic-restricted signaling protein of interest in blood cancers and autoimmune conditions, prompting efforts to target it via induced protein degradation.
- High-throughput, unbiased global proteomics screening identified phenyl-glutarimide degrader compounds that recruit CRBN to selectively degrade VAV1.
- VAV1's C-terminal SH3-2 domain proved essential for ternary complex formation, and structural work uncovered a novel "RT-loop" degron there—distinct from the "G-loop" degrons used by other CRBN glues—validated by mutagenesis.
- An AI-based protein structure-prediction workflow modeled the ternary complex to support this mechanistic finding.
- Free energy perturbation calculations on the predicted structures generated cooperativity scores that correlated with experimental potency, demonstrating a computational strategy to prioritize and optimize molecular glue analogs faster than empirical screening alone.
The real headline isn't the molecule, it's the RT-loop degron. G-loop CRBN neosubstrates have basically been the only playbook since the IMiD era, so a structurally distinct degron sitting in VAV1's SH3-2 domain is a genuine expansion of the addressable degradable proteome, not just one more target on the pile. The phenyl-glutarimide warhead itself is bog-standard IMiD-adjacent chemistry — nothing novel there; the real innovation is in the target-engagement biology, not the medchem. VAV1's hematopoietic-restricted expression is a nice built-in selectivity advantage most degrader programs would kill for. On the FEP/AI ternary angle: cooperativity scores tracking potency across one series is promising, but it's one dataset — I'd want to see it prospectively rank blind analogs before I trust it over empirical SAR.