Shapechain: Revealing Oxytocin-Receptor Structural Mimicry with AI Validation

Identifying structural mimicry in receptor-ligand interactions is vital for drug discovery. We introduce ShapeChain, a tool that converts protein sequences into symbolic geometric forms for rapid human detection of conserved motifs. Using ShapeChain on oxytocin (CYIQNCPLG) and its receptor (P30559), we identified a conserved receptor segment, MFASTYLLL (positions 123-131), with significant geometric similarity to oxytocin. AlphaFold2 predictions, validated by ChimeraX MatchMaker and measured with our Protein Prediction Quality Index (PPQI), show that MFASTYLLL achieves a PPQI of approximately 75.38, compared to oxytocin's 48.50. These results suggest that MFASTYLLL is a structurally robust element that may aid receptor activation and reflect coevolutionary trends. Our framework combines symbolic sequence analysis with AI-driven structural validation, offering a scalable method for motif identification and receptor-ligand modeling.