A.-R. Kim, A. Comjean, A. Veal, J. Rodiger, M. Han, Y. Hu, N. Perrimon
Protein-protein interactions (PPIs) are fundamental to cellular function. Yet most Drosophila PPIs remain structurally uncharacterized despite the wealth of genetic and biochemical data available for this organism. Here we present FlyPredictome, a structural interactome based on 1.5 million pairwise AlphaFold-Multimer predictions. Using a local confidence metric performing robustly on interactions involving flexible and disordered proteins, we systematically assess experimentally reported Drosophila PPIs and predict direct binding interfaces at residue-level resolution. Testing their functional relevance, we find that phenotype-associated missense mutations are enriched at predicted interaction interfaces. Building on these predictions, we construct an evidencesupported PPI network, revealing modular organization from signaling pathways to individual protein complexes. We further predict higher-order complexes for nearly 400 of these modules with AlphaFold3, matching available cryo-EM structures and extending to unresolved assemblies. Fly-Predictome is available as an open, interactive database that maps interactions to residue-level binding surfaces, providing a structural foundation for interaction discovery in Drosophila.