Moleküler Modelleme Yöntemleri İle Bazı Fitokimyasalların Opioid Reseptörüyle Bağlanma Aktivitelerinin Araştırılması
Özet
Around the world 255 million people using drugs. According to frequency of use substances lifelong Turkey in the year 2011 held on drug addiction research it has been identified as 2.7%. Opioid drugs are classified as natural (morphine, heroin, codein...) , semi-synthetic (oxycodone, buprenorfine...) and synthetic (methadone, fentanyl....).
Main reason of opioid dependece is interaction of opiates such as morphine with mü opioid receptor (MOR) which is G-protein receptor. It is a target structure for drugs used opioid treatment Currently agonist and antagonist drugs are used for the different steps of treatment. Because of their side effects, new drugs have been studied for.
There are some experimental studies that some plant (hypericum perforatum, peganum harmala, papaver rose and nigella sativa) are useful for the treatment of dependency but its mechanism was not understood and it is not known which phytochemicals have what effects on.
Our aim is to identify agonist and/or antagonist properties of 31 phytochemicals obtained from four plants which are hypericum perforatum, papaver rose, peganum harmala and nigella sativa for two targets by using AutoDock Vina program.
In the first point of the study, validation of AutoDock Vina program was done for re-docking and cross-docking of agonist and antagonist ligand mu opioid receptor having pdb code 4DKL and 5C1M. According to redocking calculation results , RMSD values are 1.0 Å and 1.2 Å for respectively for 4DKL and 5C1M. Since RMSD values are smaller than 2.0 Å , it is shown that AutoDock Vina programme is suitable for chosen protein-ligand system.
In the second part, geometry optimisation of 31 phytochemicals obtained from four plants was done by using DFT/B3LYP/6-31 G (d,p) basis set. Docking calculations of there compounds to active site of mu opioid receptor was studied by AutoDock Vina program. After analyzing agonist and antagonist properties of 31 phytochemicals based on their binding energies, rhoeagenine from papaver rose was found to be the best agonist.
As a result of the research first time carried out in this thesis, the obtained data will contribute to the design of new medicine which may be effective as target structure of MOR.