Identifying 14-3-3 interactome binding sites with deep learning.

ABSTRACT: Protein-protein interactions are at the heart of biological processes. Understanding how proteins interact is key for deciphering their roles in health and disease, and for therapeutic interventions. However, identifying protein interaction sites, especially for intrinsically disordered proteins, is challenging. Here, we developed a deep learning framework to predict potential protein binding sites to 14-3-3 - a 'central hub' protein holding a key role in cellular signaling networks. After systematically testing multiple deep learning approaches to predict sequence binding to 14-3-3, we developed an ensemble model that achieved a 75% balanced accuracy on external sequences. Our approach was applied prospectively to identify putative binding sites across medically relevant proteins (ranging

SUBMITTER: van Weesep L 

PROVIDER: S-EPMC12360161 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature