Predicting beta-turns and their types using predicted backbone dihedral angles and secondary structures

Kountouris, Petros; Hirst, Jonathan D

Abstract

Background

β-turns are secondary structure elements usually classified as coil. Their prediction is important, because of their role in protein folding and their frequent occurrence in protein chains.

Results

We have developed a novel method that predicts β-turns and their types using information from multiple sequence alignments, predicted secondary structures and, for the first time, predicted dihedral angles. Our method uses support vector machines, a supervised classification technique, and is trained and tested on three established datasets of 426, 547 and 823 protein chains. We achieve a Matthews correlation coefficient of up to 0.49, when predicting the location of β-turns, the highest reported value to date. Moreover, the additional dihedral information improves the prediction of β-turn types I, II, IV, VIII and "non-specific", achieving correlation coefficients up to 0.39, 0.33, 0.27, 0.14 and 0.38, respectively. Our results are more accurate than other methods.

Conclusions

We have created an accurate predictor of β-turns and their types. Our method, called DEBT, is available online at http://comp.chem.nottingham.ac.uk/debt/.

Citation

Kountouris, P., & Hirst, J. D. (2010). Predicting beta-turns and their types using predicted backbone dihedral angles and secondary structures. BMC Bioinformatics, 11, Article 407. https://doi.org/10.1186/1471-2105-11-407

• Journal Article Type: Article
• Acceptance Date: Jul 31, 2010
• Online Publication Date: Jul 31, 2010
• Publication Date: 2010
• Deposit Date: Feb 3, 2024
• Publicly Available Date: Feb 5, 2024
• Journal: BMC Bioinformatics
• Print ISSN: 1471-2105
• Publisher: BioMed Central
• Peer Reviewed: Peer Reviewed
• Volume: 11
• Article Number: 407
• DOI: https://doi.org/10.1186/1471-2105-11-407
• Public URL: https://nottingham-repository.worktribe.com/output/30665116
• Publisher URL: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-407