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Prediction of Beta-Turn in Protein Using E-SSpred and Support Vector Machine

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Abstract

β-Turn is a secondary protein structure type that plays an important role in protein configuration and function. Here, we introduced an approach of β-turn prediction that used the support vector machine (SVM) algorithm combined with predicted secondary structure information. The secondary structure information was obtained by using E-SSpred, a new secondary protein structure prediction method. A 7-fold cross validation based on the benchmark dataset of 426 non-homologous protein chains was used to evaluate the performance of our method. The prediction results broke the 80% Q total barrier and achieved Q total = 80.9%, MCC = 0.44, and Q predicted higher 0.9% when compared with the best method. The results in our research are coincident with the conclusion that β-turn prediction accuracy can be improved by inclusion of secondary structure information.

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Abbreviations

SVM:

Support vector machine

PSIPRED:

Position specific iterated prediction

PSI-BLAST:

Position specific iterated-Basic local alignment search tool

PROMOTIF:

A program to identify and analyze structural motifs in protein

AA:

Amino acid

PSSM:

Position-specific scoring matrices

SSE:

Secondary structure elements

H:

Helix

E:

Strand

C:

Coil

nr:

Non-redundant

BTPRED:

Beta-turns prediction

RBF:

Radial basis function

MOLEBRNN:

Prediction of beta-turns and beta-turn types by a novel bidirectional Elman-type recurrent neural network with multiple output layers

BTSVM:

Prediction and analysis of beta-turns in proteins by support vector machine

COUDES:

Chercher Ou` Une De′viation Existe Suˆ rement

KNN:

K-nearest neighbor algorithm

TC:

Tertiary contact

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Acknowledgments

The work was funded by the National Natural Science Foundation of China (No. 20775052). The authors would like to express their cordial thanks to the unknown reviewers for providing comments on the manuscript.

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Authors and Affiliations

  1. College of Chemistry, Key Laboratory of Green Chemistry & Technology, Ministry of Education, Sichuan University, Chengdu, 610064, China

    Lirong Liu, Yaping Fang, Menglong Li & Cuicui Wang

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  1. Lirong Liu
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  2. Yaping Fang
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  3. Menglong Li
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  4. Cuicui Wang
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Correspondence to Menglong Li.

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Liu, L., Fang, Y., Li, M. et al. Prediction of Beta-Turn in Protein Using E-SSpred and Support Vector Machine. Protein J 28, 175–181 (2009). https://doi.org/10.1007/s10930-009-9181-4

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  • DOI: https://doi.org/10.1007/s10930-009-9181-4

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