Structural basis of NSD2 degradation via targeted recruitment of SCF-FBXO22
Robertson, K. C.; Amann, S. J.; Liu, T.; Funk, A. V.; Wang, X.; Grishkovskaya, I.; Tabor, J. R.; Norris-Drouin, J. L.; Arrowsmith, C. H.; Collins, J. L.; Emanuele, M. J.; Haselbach, D.; James, L. I.; Brown, N. G.
Show abstract
Targeted protein degradation (TPD) through the ubiquitin-proteasome system is driven by compound-mediated polyubiquitination of a protein-of-interest by an E3 ubiquitin (Ub) ligase. To date, relatively few E3s have been successfully utilized for TPD and the governing principles of functional ternary complex formation between the E3, degrader, and protein target remain elusive. FBXO22 has recently been harnessed by several groups to target different proteins for degradation. FBXO22 recruitment has been enabled through degraders that covalently modify its cysteine residues. Here, we reveal that the aldehyde derivative of UNC10088 promotes cooperative binding of FBXO22 to NSD2, a histone methyltransferase and oncogenic protein, leading to a cryo-EM structure of the full SKP1-CUL1-F-box (SCF)-FBXO22 complex with NSD2. This structure revealed a conformational change in the FBXO22 loop surrounding C326, further exposing the cysteine for covalent recruitment. Additional medicinal chemistry efforts led to the discovery of benzaldehyde-based non-prodrug degraders that similarly engage C326 of FBXO22 and potently degrade NSD2. Furthermore, unlike many degraders, our molecules recruit NSD2 to a different surface of FBXO22 than the known FBXO22 substrate BACH1, allowing for concurrent complex formation and degradation of both the neosubstrate and endogenous substrates. Overall, we demonstrate the biochemical and structural basis for NSD2 degradation, revealing key principles for efficient and selective TPD by SCFFBXO22.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.