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http://dx.doi.org/10.6109/jkiice.2016.20.9.1816

Prediction of Protein Secondary Structure Using the Weighted Combination of Homology Information of Protein Sequences  

Chi, Sang-mun (Department of Computer Science and Engineering, Kyungsung University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.20, no.9, 2016 , pp. 1816-1821 More about this Journal
Abstract
Protein secondary structure is important for the study of protein evolution, structure and function of proteins which play crucial roles in most of biological processes. This paper try to effectively extract protein secondary structure information from the large protein structure database in order to predict the protein secondary structure of a query protein sequence. To find more remote homologous sequences of a query sequence in the protein database, we used PSI-BLAST which can perform gapped iterative searches and use profiles consisting of homologous protein sequences of a query protein. The secondary structures of the homologous sequences are weighed combined to the secondary structure prediction according to their relative degree of similarity to the query sequence. When homologous sequences with a neural network predictor were used, the accuracies were higher than those of current state-of-art techniques, achieving a Q3 accuracy of 92.28% and a Q8 accuracy of 88.79%.
Keywords
Protein secondary structure; Homologous protein search; PSI-BLAST; Sequence similarity;
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