Refined 3D models of the transmembrane domains of the cloned delta, mu and kappa opioid receptors belonging to the superfamily of G-protein coupled receptors (GPCRs) were constructed from a multiple sequence alignment using the alpha carbon template of rhodopsin recently reported. Other key steps in the procedure were relaxation of the 3D helix bundle by unconstrained energy optimization and assessment of the stability of the structure by performing unconstrained molecular dynamics simulations of the energy optimized structure. The results were stable ligand-free models of the TM domains of the three opioid receptors. The ligand-free delta receptor was then used to develop a systematic and reliable procedure to identify and assess putative binding sites that would be suitable for similar investigation of the other two receptors and GPCRs in general. To this end, a non-selective, 'universal' antagonist, naltrexone, and agonist, etorphine, were used as probes. These ligands were first docked in all sites of the model delta opioid receptor which were sterically accessible and to which the protonated amine of the ligands could be anchored to a complementary proton-accepting residue. Using these criteria, nine ligand-receptor complexes with different binding pockets were identified and refined by energy minimization. The properties of all these possible ligand-substrate complexes were then examined for consistency with known experimental results of mutations in both opioid and other GPCRs. Using this procedure, the lowest energy agonist-receptor and antagonist-receptor complexes consistent with these experimental results were identified. These complexes were then used to probe the mechanism of receptor activation by identifying differences in receptor conformation between the agonist and the antagonist complex during unconstrained dynamics simulation. The results lent support to a possible activation mechanism of the mouse delta opioid receptor similar to that recently proposed for several other GPCRs. They also allowed the selection of candidate sites for future mutagenesis experiments.