A Multi-Angle Approach to Predict Peptide-GPCR Complexes: The N/OFQ-NOP System as a Successful AlphaFold Application Case Study

With nearly 700 structures solved and a growingnumber of customized structure prediction algorithms beingdeveloped at a fast pace, G protein-coupled receptors (GPCRs)are an optimal test case for validating new approaches for theprediction of receptor active state and ligand bioactiveconformation complexes. In this study, we leveraged theavailability of hundreds of peptide GPCRs in the active state andboth classical homology and artificial intelligence (AI) basedprotein modeling combined with docking and AI-based peptidestructure prediction approaches to predict the nociceptin/orphaninFQ-NOP receptor active state complex (N/OFQ-NOPa). The InSilico generated hypotheses were validated via the design, synthesis,and pharmacological characterization of novel linear N/OFQ(1−13)-NH2 analogues, leading to the discovery of a novel antagonist(3B; pKB = 6.63) bearing a single ring-constrained residue in place of the Gly2−Gly3 motif of the N/OFQ message sequence(FGGF). While the experimental validation was ongoing, the availability of the Cryo-EM structure of the predicted complex enabledus to unambiguously validate the generated hypotheses. To the best of our knowledge, this is the first example of a peptide−GPCRcomplex predicted with atomistic accuracy (full complex Cα RMSD < 1.0 Å) and of the N/OFQ message moiety being successfullymodified with a rigid scaffold.