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Position-specific residue preference features around the ends of helices and strands and a novel strategy for the prediction of secondary structures

Huazhong University of Science and Technology

(RECEIVED April 7, 2008; ACCEPTED May 23, 2008)

It has been many years since position-specific residue preference around the ends of helix was revealed. However, all the existing secondary structure prediction methods did not exploit this preference feature, resulting in low accuracy in predicting the ends of secondary structures. In this study, we collected a relatively large dataset consisting of 1860 high-resolution, non-homology proteins from PDB, and further analyzed the residue distributions around the ends of regular secondary structures. It was found that there exist position-specific residue preferences (PSRP) around the ends of not only helices but also strands. Based on the unique features, we proposed a novel strategy and developed a tool named E-SSpred that treats the secondary structure as a whole and build models to predict entire secondary structure segments directly by integrating relevant features, which is similar to the approaches widely used in predicting exons and introns of genes from DNA sequences. In E-SSpred, the support vector machine (SVM) method is adopted to model and predict the ends of helices and strands according to the unique residue distributions around them. A simple linear discriminate analysis method is applied to model and predict entire secondary structure segments by integrating end-prediction results, tri-peptide composition and length distribution features of secondary structures, as well as the prediction results of the most famous program PSIPRED. The results of 5-fold cross validation on a widely used dataset demonstrate that the accuracy of E-SSpred in predicting ends of secondary structures is about 10% higher than PSIPRED, and the overall prediction accuracy (Q3 value) of E-SSpred (82.2%) is also better than PSIPRED (80.3%). The E-SSpred web server is available at http://bioinfo.hust.edu.cn/bio/tools/E-SSpred/index.html.

Keywords: Protein structure prediction; Ends of secondary structure; Position-specific residue preference; Secondary structure prediction

¹ E-mail: yhzhou{at}mail.hust.edu.cn

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