The Research Of Protein3D Structure Prediction Method Based On Secondary Structure

Nowadays, the forecasting3D space structure of the biology protein is the focus in biology domain. The protein folding structure has determined it’s biological function to a great extent, and the3D space structure of the protein has determined the function of protein biological function. In order to know the biological function of the biology in detail, we must far study the3D space structure of the protein, and afford a efficient algorithm to describe the space structure of the protein form the case of study at last.There is two kinds of aminophenol in the protein sequence, the one is hydrophobe aminophenol, the other is hydrophile aminophenol. The characteristic in the aminophenol is be showed:the hydrophile aminophenol is be closed as soon as possible. In recent years, according to this feature, scholars invented a lot of protein3D structure prediction models and algorithms. But there are some shortcomings in these prediction methods, need for further improvement in the accuracy, scope, operational efficiency. Through the analysis and comparison of protein structure prediction algorithms and models, author found most of the prediction methods predict the3D structure by the protein primary structure. In addition, secondary structure prediction has a good accuracy rate, the author designed a set of protein3D structure prediction method based on the secondary structure.The method established a database of protein secondary structure based on the Protein Data Bank, and then found association rules between the protein primary structure and secondary structure by Density clustering algorithm. On the other hand, after analysis of the genetic algorithm, improved constraint method and binary encoding method, then Introduced competition in optimal retention policy. The experiments show that this method has an advantage in the long sequence protein prediction compared with other methods.