Delta opioid receptor (DOR) is an attractive target for the treatment of brain disorders and design of selective and effective ligands is very important. Computer-assisted design of compounds could help much in this field if there is a good receptor model and appropriate algorithm for the corresponding receptor-ligand system. The aim of the present study was to find the most appropriate scoring functions and the model for docking of endogenous enkephalins and their analogues with delta-opioid receptor (DOR) that correlated well with preliminary data from in vitro bioassay such as: IC50 - potency, KA - affinity, erel - efficacy. The capabilities of the four scoring functions, available in GOLD5.2 were explored with the following three different models of DOR: a) a theoretical model (ePDB id: 1ozc); b) a model obtained with homology modeling (Model B); and c) a crystal structure of human DOR (PDB id: 4ej4). Enkephalin analogues were consistently docked with each of the receptor models with each of the four scoring function. The analysis of the obtained results shows that after the docking with Model B the values of the scoring functions correlate negatively with the data from in vitro tests at the highest degree. Furthermore, the use of the ASP scoring function enable more precise docking of the test ligands as correlation coefficients were: ASP score/IC50 = - 0.86, and obtained correlation has a biological sense. Much higher value of fitness function is, the lower the value of concentration is, and i.e. its potency is greater.