Molecular modeling methodologies (molecular dynamics, conformational searching, Monte Carlo) used data from the crystalized structure of bovine rhodopsin (excluding the intracellular and extracellular domains) to develop a model of the delta-opioid receptor; i.e., computer-direced mutagenesis to ensure the sequence coincided with that of the opioid receptor by exchanging specific in that 7-transmembrane protein. A variety of delta agonists and antagonists based on the Dmt-Tic pharmacophores, previous modeled from X-ray diffraction analyses of three compounds, as well as mu agonists which should have very low affinity with the delta-opioid receptor, were docked into the proposed binding pocket. This was delineated by the minimized molecular model fit of the ligands and refelcted their known biological activities and receptor affinities. Conformational changes in the peptides was initially examined by 1-H NMR (COSY, NOESY, HOHAHA, ROESY, DQF-COSY experiments), CD under variying solvent and temperature conditions in Kobe Gakuin University, Japan. In terms of the ligands, the aromatic ring distance may be a singularly important characteristic of delta antagonists and agonists providing a "receptor-bound conformation" in spite of the inherent flexibility of the peptide. As anticipated, mu agonists exhibited a poor fit in the delta receptor pocket region, confirming the application of this methodology. The topographical features observed with the Dmt-Tic pharmacophore differentiate it from all other peptides and its interaction with select side-chains in the receptor pocket. The data suggest that the presumed receptor-bound conformation of the peptide ligand and receptor involves stacking between aromatic rings and hydrogen bonding and that mu agonists poorly interacted with those residues specific for delta ligands. Thus, intra-ring distance of delta-opioid antagonists may portend biological differences. Peptide analogues with dual receptor binding characteristics or selectivity for the mu opioid receptor equally assisted in the application of molecular modeling in a predictive mode. Thus, model of the delta receptor and our delta- and mu-opioid antagonist and agonist pharmacophores will serve as scaffolds in the design of new potent ligands.