Ferguson et al. develop DeorphaNN, a graph neural network integrating active-state GPCR-peptide structural predictions, interatomic interactions, and deep learning embeddings to prioritize putative peptide agonists for experimental screening. DeorphaNN improves agonist prioritization over AlphaFold and general protein-protein interaction models.

G protein-coupled receptors (GPCRs) are important cell surface receptors involved in numerous physiological processes. Although peptides are the cognate ligands for many of these receptors, identifyin...