Using the Support Vector Machine Algorithm to Predict β-Turn Types in Proteins

Xiaobo Shi,Xiuzhen Hu

doi:10.4236/eng.2013.510b078

Abstract

The structure and function of proteins are closely related, and protein structure decides its function, therefore protein structure prediction is quite important.β-turns are important components of protein secondary structure. So development of an accurate prediction method ofβ-turn types is very necessary. In this paper, we used the composite vector with position conservation scoring function, increment of diversity and predictive secondary structure information as the input parameter of support vector machine algorithm for predicting theβ-turn types in the database of 426 protein chains, obtained the overall prediction accuracy of 95.6%, 97.8%, 97.0%, 98.9%, 99.2%, 91.8%, 99.4% and 83.9% with the Matthews Correlation Coefficient values of 0.74, 0.68, 0.20, 0.49, 0.23, 0.47, 0.49 and 0.53 for types I, II, VIII, I’, II’, IV, VI and nonturn respectively, which is better than other prediction.

Highlights

Protein secondary structure prediction is an intermediate step in overall tertiary structure prediction
We used the composite vector with position conservation scoring function, increment of diversity and predictive secondary structure information as the input parameter of support vector machine algorithm for predicting the β-turn types in the database of 426 protein chains, obtained the overall prediction accuracy of 95.6%, 97.8%, 97.0%, 98.9%, 99.2%, 91.8%, 99.4% and 83.9% with the Matthews Correlation Coefficient values of 0.74, 0.68, 0.20, 0.49, 0.23, 0.47, 0.49 and 0.53 for types I, II, VIII, I’, II’, IV, VI and nonturn respectively, which is better than other prediction
The prediction performance of β-turn types can be greatly improved by using the predictive secondary structure information (PSI) [4,5,7]

Summary

Introduction

Protein secondary structure prediction is an intermediate step in overall tertiary structure prediction. The secondary structure of a protein consists of regular, local regular and non-regular secondary structure. Local regular secondary structure contains tight turns and Ω loops. Tight turns can be divided into δ-, γ-, β-, α- and π-turns according to the number of residues involved [1,2]. Β-turns are the most common and largest number turns, which constitute about 25% of the residues in proteins [1,3,4,5]. According to the ψ/φ values of the central residues i + 1 and i + 2, β-turns are classified into nine types: I, II, VIII, I’, II’, VIa1, VIa2, VIb and IV [3,4,5,6,7]. Β-turn types VIa1, VIa2 and VIb are merged into one type, called type VI [3,5]

Methods

Results

Conclusion