Protein stability in cells is governed by short amino acid sequences called “degrons.” However, our understanding of degrons—especially how they interact with E3 ligases—remains limited, posing a major challenge to predicting and controlling protein half-life in living systems. While significant progress has been made in studying simple degrons at the protein ends (N- and C-degrons), research on more complex and widely distributed “internal” degrons is still lacking, mainly due to inadequate tools.
To overcome this barrier, we have developed a new dual-indicator protein stability platform, enhanced by AlphaFold structural predictions and machine-learning algorithms, to identify both known and disease-associated degrons throughout the human proteome. This platform has the potential to reshape our understanding of protein regulation in both healthy and disease states, while also enabling novel strategies to manipulate protein stability for medical, research, and bioengineering applications.