Abstract
<jats:p> The <jats:italic>Drosophila</jats:italic> Estrogen Related Receptor (dERR) is an orphan nuclear receptor that regulates developmental metabolism, yet the protein cofactors that modulate its activity remain poorly defined. Here, we used the AI based FlyPredictome platform to identify candidate dERR interaction partners and evaluate their predicted structural interfaces. Among the highest confidence interactors is the transcription factor Sima, which represents the <jats:italic>Drosophila</jats:italic> ortholog of HIF1α, an interaction that was reciprocally identified in both dERR and Sima/HIF1α interaction datasets. Structural modeling predicted binding between the dERR ligand binding domain and a conserved LXXLL motif in Sima/HIF1α. Notably, the predicted dERR/Sima interaction interface encompasses residues previously shown experimentally to be essential for binding, providing independent structural support for this biologically relevant protein protein interaction. </jats:p>