Biochemistry  Biophysics  Computer Science

TANGLE: TwoLevel Support Vector Regression Approach for Protein Backbone Torsion Angle Prediction from Primary Sequences
Published:
Thursday, February 02, 2012
Author:
Jiangning Song et al.
by Jiangning Song, Hao Tan, Mingjun Wang, Geoffrey I. Webb, Tatsuya Akutsu
Protein backbone torsion angles (Phi) and (Psi) involve two rotation angles rotating around the C_{a}N bond (Phi) and the C_{a}C bond (Psi). Due to the planarity of the linked rigid peptide bonds, these two angles can essentially determine the backbone geometry of proteins. Accordingly, the accurate prediction of protein backbone torsion angle from sequence information can assist the prediction of protein structures. In this study, we develop a new approach called TANGLE (Torsion ANGLE predictor) to predict the protein backbone torsion angles from amino acid sequences. TANGLE uses a twolevel support vector regression approach to perform realvalue torsion angle prediction using a variety of features derived from amino acid sequences, including the evolutionary profiles in the form of positionspecific scoring matrices, predicted secondary structure, solvent accessibility and natively disordered region as well as other global sequence features. When evaluated based on a large benchmark dataset of 1,526 nonhomologous proteins, the mean absolute errors (MAEs) of the Phi and Psi angle prediction are 27.8° and 44.6°, respectively, which are 1% and 3% respectively lower than that using one of the stateoftheart prediction tools ANGLOR. Moreover, the prediction of TANGLE is significantly better than a random predictor that was built on the amino acidspecific basis, with the pvalue<1.46e147 and 7.97e150, respectively by the Wilcoxon signed rank test. As a complementary approach to the current torsion angle prediction algorithms, TANGLE should prove useful in predicting protein structural properties and assisting protein fold recognition by applying the predicted torsion angles as useful restraints. TANGLE is freely accessible at http://sunflower.kuicr.kyotou.ac.jp/~sjn/TANGLE/.
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