AVPR2 PROTEİNİNİN HOMOLOJİ TEMELLİ ÜÇ BOYUTLU YAPI MODELLEMESİ
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Proteins are molecules found in all organisms and made up of unique amino acid sequences including many physiological processes directly. The three dimensional structure of a protein can determine the biological importance of that protein and its work within a process. The molecular effect of mutations on the structure and function of proteins is important. Any change in the protein sequence (deletion, insertion or mutation) can affect a specific or a whole area by disrupting the balance of interaction forces within the protein. These changes in the protein structures are assessed using bioinformatics tools today. Bioinformatics form a multidisciplinary connection including genetics, structural biology and biochemistry. Homology based modeling studies, an area of bioinformatics, predicts the three dimensional structure of proteins. Knowing the physico-chemical features of proteins that are worked on and the three dimensional homology modeling studies of proteins are important in assessing the three dimensional structures of proteins. Knowing the three dimensional structure of a mutant or wild type of a protein plays an important role in protein-protein, protein-ligand and doking studies. In accordance with this information, drug design development studies are designed for the treatment of diseases caused by mutations. The aim of this study is to assess the mutant AVPR2 proteins (which were previously functionally analyzed by our group) homology models using bioinformatics tools with their physico-chemical features and mutation function analyses, to provide information to be used for future treatment-oriented docking and modelling studies. For this purpose, wild type AVPR2 and mutant type ΔR67_G69, G107W, ΔR67_G69/G107W, R68W, V162A and T273M models were extracted with Swiss-Prot homology modelling, a bioinformatics tool. Physico-chemical features of wild type and mutant type models are calculated with a programme named ProtParam. Wild type and mutant type models were examined through visualization on the Chimera programme. Generated models were assessed together with physico-chemical calculations and mutation function analyses. As a result, it was determined that mutation function analyses of all models studied as part of the thesis, physico-chemical calculations and generated models support each other. This study will give information to the future studies about docking and modelling researches for treatment strategies when all in-vitro experiments, homology modelling studies and clinical features of the patients are considered together.