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iPreny-PseAAC: Identify C-terminal Cysteine Prenylation Sites in Proteins by Incorporating Two Tiers of Sequence Couplings into PseAAC

[ Vol. 13 , Issue. 6 ]

Author(s):

Yan Xu, Zu Wang, Chunhui Li and Kuo-Chen Chou   Pages 544 - 551 ( 8 )

Abstract:


Background: Occurring at the cysteine residue in the C-terminal of a protein, prenylation is a special kind of post-translational modification (PTM), which may play a key role for statin in altering immune function. Therefore, knowledge of the prenylation sites in proteins is important for drug development as well as for in-depth understanding the biological process concerned.

Objective: Given a query protein whose C-terminal contains some cysteine residues, which one can be of prenylation or none of them can be prenylated?

Methods: To address this problem, we have developed a new predictor, called “iPreny-PseAAC”, by incorporating two tiers of sequence pair coupling effects into the general form of PseAAC (pseudo amino acid composition).

Results: It has been observed by four different cross-validation approaches that all the important indexes in reflecting its prediction quality are quite high and fully consistent to each other.

Conclusion: It is anticipated that the iPreny-PseAAC predictor holds very high potential to become a useful high throughput tool in identifying protein C-terminal cysteine prenylation sites and the other relevant areas. To maximize the convenience for most experimental biologists, the webserver for the new predictor has been established at http://app.aporc.org/iPreny-PseAAC/, by which users can easily get their desired results without needing to go through the mathematical details involved in this paper.

Keywords:

Autoimmune disease, cysteine prenylation, protein C-terminal, PseAAC, SVM, web-server.

Affiliation:

Department of Information and Computer Science, University of Science and Technology Beijing, Beijing 100083, Department of Information and Computer Science, University of Science and Technology Beijing, Beijing 100083, School of Mathematics and Statistics, Beijing Institute of Technology, Beijing 100081, Gordon Life Science Institute, Boston, MA 02478

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