| Summary: | 碩士 === 國立雲林科技大學 === 資訊管理系碩士班 === 91 === The understanding of protein tertiary structure facilitates the development of new medicine. Therefore, to predict protein tertiary structure is one of important research of studying protein form. Foretime to predict the measure of protein tertiary structure, on the whole we divided into two ways, one is from protein primary structure to predict the solid structure (tertiary structure) directly. In this way some of using a chemical experiment to decide the protein solid structure (tertiary structure) e.g. the x-ray crystallography and nuclear magnetic resonance (NMR), and another one is by theory calculation to decide the protein solid structure (tertiary structure). Chemical experiment can be precise to analyze the protein tertiary structure whereas it is too waste time and isn’t adaptive for all of protein molecule. Thus, it appears the theoretical calculation. But Chemical experiment of protein tertiary structure is more accurate than theoretical calculation. The other way is by protein primary structure to predict protein secondary structure, because it is difficult by protein primary structure directly to predict protein tertiary structure. Hence, it is through prediction and understanding of secondary structure to predict the protein solid structure (tertiary structure).
Amino acid of protein area constructs protein secondary structure. How amino acid of protein area forms protein secondary structure that because the certain amino acid of area to construct the chemical action that is hydrogen bonding. Because of forming the secondary structure through one area of amino acid of protein. Some amino acid of the area could construct hydrogen bonding; the relation between some amino acid in this area will attract each other, then it forms to construct the kind of secondary structure.
In what kind of length of amino acid of protein area and which position of amino acid of protein could construct the particular protein secondary structure, it is not having a rule to induce. Moreover, it is different from the past prediction of secondary structure. It expects to find in the dataset of experiment and it finds out just some of key amino acid of area could form the secondary structure. Through arranging template to discover some rule about shape of protein secondary structure and it will be having some contribution the prediction of protein tertiary structure.
Instrument of this research is back-propagation network that belongs supervisory learning algorithm and be applied in every domain. In the research is not only training back-propagation network to observe the classified act of protein secondary structure but also using the experimental result to get the back- propagation network model of topmost classified accurate rate and progressing the experiment of finding template. Finally, it aims at template to arrange and offers the discovering of the research.
Keywords: back-propagation network，amino acid，protein secondary structure，protein tertiary structure
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