Melanocyte-inhibiting factor (MIF-1) is the first hypothalamic tripeptide which has been demonstrated to act not only in the brain but also in the pituitary. Tyr-MIF-1 acts as an opiate agonist. It binds selectively and with a high affinity to the l-opioid receptor when compared with the d-and jopioid receptors. A large number of analogues of MIF-1 and Tyr-MIF-1, containing various modifiers in their structures, have been synthesized and their analgesic effect was determined by various in vivo tests. The aim of current study was:(1) to synthesize new MIF-1 and Tyr-MIF-1 analogues containing sulfoarginine (sArg) and norsulfoarginine (NsArg) in the second and third position, respectively; (2) with the help of docking procedures to find the relationship between structure and biological activity of MIF-1 and Tyr-MIF-1 analogues previously synthesized and biologically tested; (3) using found correlation to predict the biological effect of newly synthesized analogues. New analogues of MIF-1 and Tyr-MIF-1 were synthesized using methods of peptide synthesis in solution. Docking was performed with GOLD 5.0 and a correlation between the obtained docking data and the values from in vivo test was found. Some structure-activity relationships were determined. According to the correlation, we made assumptions about the biological effect of sArg and NsArg containing MIF-1 and Tyr-MIF-1. A computational approach could be very useful in the elucidation of the structure-activity relationship and in the design of new analogues with desired biological effect.
Mu-opioid receptor (MOR) is an attractive target for <em>in silico</em> docking experiments. Many potent analgesics currently in use act through the MOR. The main objective of the present work was to find the polynomial function for modelling of the structure-activity relationship of a series of MOR analogues and the results of the molecular docking with MOR (PDBid:4dkl). The relationship of the biological activity of the ligands with the ChemScore function and with the total energy (MolDock function) was modelled with first- to third-degree polynomials and surface fitted method, assessed by least squares method. The finding, established in the paper, suggests that the third order polynomial could be successfully used for modelling of the relationship between the biological effect of the MOR analogues and results from docking procedure. Analysis and comparison of the data from in vitro tests and docking studies could help to understand better the relationship between in vitro biological effects and docking studies and to answer whether the models of the biological macromolecules (in our case MOR) correspond to the real 3D structure.
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