Combinatorial mapping of E3 ubiquitin ligases to their target substrates
Chase C. Suiter, Diego Calderon, David Lee, Melodie Chiu, Shruti Jain, Florence M. Chardon, Choli Lee, Riza M. Daza, Cole Trapnell, Ning Zheng, Jay Shendure
Abstract
E3 ubiquitin ligases (E3s) confer specificity of protein degradation through ubiquitination of substrate proteins. Yet, the vast majority of the >600 human E3s have no known substrates. To identify proteolytic E3-substrate pairs at scale, we developed combinatorial mapping of E3 targets (COMET), a framework for testing the role of many E3s in degrading many candidate substrates within a single experiment. We applied COMET to SCF ubiquitin ligase subunits that mediate degradation of target substrates (6,716 F-box-ORF [open reading frame] combinations) and E3s that degrade short-lived transcription factors (TFs) (26,028 E3-TF combinations). Our data suggest that many E3-substrate relationships are complex rather than 1:1 associations. Finally, we leverage deep learning to predict the structural basis of E3-substrate interactions and probe the strengths and limits of such models. Looking forward, we consider the practicality of transposing this framework, i.e., computational structural prediction of all possible E3-substrate interactions, followed by multiplex experimental validation.