Multi-scale classification decodes the complexity of the human E3 ligome

E3 ubiquitin ligases are essential enzymes that target specific proteins for degradation, maintaining cellular health by removing damaged or unwanted proteins. Despite their therapeutic potential, a comprehensive framework for understanding the relationships among diverse E3 ligases has been lacking. Here, we classify the "human E3 ligome"–an extensive set of catalytic human E3s–by integrating multi-layered data, including protein sequences, domain architectures, 3D structures, functions, and expression patterns. Our classification is based on a metric-learning paradigm and uses a weakly supervised hierarchical framework to capture authentic relationships across E3 families and subfamilies. It extends the categorization of E3s into RING, HECT, and RBR classes, successfully explains their functional segregation, distinguishes between multi-subunit complexes and standalone enzymes, and maps E3s to substrates and potential drug interactions. Our analysis provides a global view of E3 biology, opening new strategies for drugging E3-substrate networks, including drug repurposing and designing new E3 handles.