Estimation of protein secondary structure based on artificial neural networks by using peptide bond angles

ABSTRACTMaster ThesisESTIMATION OF PROTEIN SECONDARY STRUCTURE BASED ONARTIFICAL NEURAL NETWORKS BY USING PEPTIDE BOND ANGLESMurat '(0ø5)ÕUDWhQLYHUVLW\Institute of Natural and Applied ScienceComputer Engineering Division2006, Pages : 82Human body is the most complex machine on the earth. Thaht?s why, we can see, hear,breathe, run and enjoy along our life. All the parts of our body constitute from cells. Cells havedifferent sizes and shapes with respect to organs they constitute. There are complex andamazing important structures in the cells and they are called proteins.They are a lot of researchers study on the proteins on the earth. Although theseresearchers, these perfect macromolecules have a lot of undiscovered aspects, and they attractresearchers.Proteins have four different structures such as primary, secondary, tertiary andquaternary. The primary structure consist of amino acids sequences and chain. Proteinsecondary structure refers to certain common repeating structures found in proteins.There are two types of secondary structures: alpha-helix and beta-pleated sheet. Tertiarystructure is the full 3-dimensional folded structure of polypeptide chain. Quaternarystructure is only present if there is more than one polypeptide chain. With multiplepolypeptide chains, quaternary structure is their interconnecitons and organization.In tihs thesis, we studied on the secondary structures of proteins and in order to depictthe secondary structure, we tried to estimate the angle between polypeptide bonds betweenalpha-carbons. At this aim, we used artifical neural networks. The results obatined by usingfeedforward neural network with Levenberg-Marquardt learning algorithm. At theconsequence, we have obtained success rates for three different data set as 70%, 68.42% and49.12%.Keywords: Proteins , Peptides, Artificial Neural Networks.VIII