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Bioinformatics Advance Access published online on October 13, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti715
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received August 19, 2005
Revised October 11, 2005
Accepted October 11, 2005

Applications note

Improving disulfide connectivity prediction with sequential distance between oxidized cysteines

Chi-Hung Tsai 1 1, Bo-Juen Chen 1 1, Chen-hsiung Chan 1, Hsuan-Liang Liu 2, and Cheng-Yan Kao 3*

1 Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan 106
2 Department of Chemical Engineering and Graduate Institute of Biotechnology, National Taipei University of Technology, Taipei, Taiwan 10608
3 Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan 106; Institute for Information Industry, Taipei, Taiwan 106

* To whom correspondence should be addressed.
Cheng-Yan Kao, E-mail: cykao{at}csie.ntu.edu.tw


  Abstract

Summary: Predicting disulfide connectivity precisely helps towards the solution of protein structure prediction. In this study, a descriptor derived from the sequential distance between oxidized cysteines (denoted as DOC) is proposed. An approach using support vector machine (SVM) method based on weighted graph matching was further developed to predict the disulfide connectivity pattern in proteins. When DOC was applied, prediction accuracy of 63% for our SVM models can be achieved, which is significantly higher than those obtained from previous approaches. The results show that using the non-local descriptor DOC coupled with local sequence profiles significantly improves the prediction accuracy. These improvements demonstrate that DOC, with a proper scaling scheme, is an effective feature for the prediction of disulfide connectivity. The method developed in this work is available at the web server PreCys (Prediction of Cys-Cys Linkages of Proteins).

Availability: http://bioinfo.csie.ntu.edu.tw:5433/Disulfide/.

Supplementary Information: Supplementary data, detailed results, tables and information are available at http://bioinfo.csie.ntu.edu.tw:5433/Disulfide/.

1 C-H T. and B-J C. contributed equally to this work.
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