M.A. Thesis:

In-Silico Design and identification of efficient chimeric natriuretic peptides

Today, heart problem have been growing and it is a first factor of mortality in our country; therefore, drugs used in this case are so important. Considering that drugs usually have side effects, it is very important to produce the drugs with less side effects. In this study, the design of the natriuretic chimeric peptides and the identification of the most effective forms using computer simulation were investigated. For this reason, firstly PDB form of considered peptides (ANP،BNP،CNP) was delivered from protein information bank and uniport. To connect peptides, we used a flexible linker and to create a third structure, it was done a modeling for every chimeric protein using the BIOVIA Discovery Studio4.1client software. 414 third structures created using the Schrodinger Suites 2a17.1 software to increase the quality of the designed models were minimized in terms of energy. Chimeric proteins using the online tools VERIYY-3D and ERRAT in order to increase the quality and quantity to choose the best designed models were investigated. These software explain the quality of chimeric protein inserted from 0 to 100. In this project, the proteins that based on these tools had a quality more than 50, to continue the process of work were chosen. Docking protein and study of binding energy level of these chimeric proteins was performed using Molsoft ICM-Pro3.8.6a bioinformatics software. Finally, chimeric proteins having binding energy more negative than 88 were selected as the most suitable chimeric proteins.

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