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Int. J. Mol. Sci. 2014, 15(5), 7594-7610;

iHyd-PseAAC: Predicting Hydroxyproline and Hydroxylysine in Proteins by Incorporating Dipeptide Position-Specific Propensity into Pseudo Amino Acid Composition

Department of Information and Computer Science, University of Science and Technology Beijing, Beijing 100083, China
Department of Mathematics and Information Science, Binzhou University, Binzhou 256603, China
College of Science, China Agricultural University, Beijing 100083, China
Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah 21589, Saudi Arabia
Gordon Life Science Institute, Boston, MA 02478, USA
Author to whom correspondence should be addressed.
Received: 7 February 2014 / Revised: 4 April 2014 / Accepted: 17 April 2014 / Published: 5 May 2014
(This article belongs to the Collection Proteins and Protein-Ligand Interactions)
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Post-translational modifications (PTMs) play crucial roles in various cell functions and biological processes. Protein hydroxylation is one type of PTM that usually occurs at the sites of proline and lysine. Given an uncharacterized protein sequence, which site of its Pro (or Lys) can be hydroxylated and which site cannot? This is a challenging problem, not only for in-depth understanding of the hydroxylation mechanism, but also for drug development, because protein hydroxylation is closely relevant to major diseases, such as stomach and lung cancers. With the avalanche of protein sequences generated in the post-genomic age, it is highly desired to develop computational methods to address this problem. In view of this, a new predictor called “iHyd-PseAAC” (identify hydroxylation by pseudo amino acid composition) was proposed by incorporating the dipeptide position-specific propensity into the general form of pseudo amino acid composition. It was demonstrated by rigorous cross-validation tests on stringent benchmark datasets that the new predictor is quite promising and may become a useful high throughput tool in this area. A user-friendly web-server for iHyd-PseAAC is accessible at Furthermore, for the convenience of the majority of experimental scientists, a step-by-step guide on how to use the web-server is given. Users can easily obtain their desired results by following these steps without the need of understanding the complicated mathematical equations presented in this paper just for its integrity. View Full-Text
Keywords: PTMs; HyP; HyL; PseAAC; discriminant function algorithm PTMs; HyP; HyL; PseAAC; discriminant function algorithm

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Xu, Y.; Wen, X.; Shao, X.-J.; Deng, N.-Y.; Chou, K.-C. iHyd-PseAAC: Predicting Hydroxyproline and Hydroxylysine in Proteins by Incorporating Dipeptide Position-Specific Propensity into Pseudo Amino Acid Composition. Int. J. Mol. Sci. 2014, 15, 7594-7610.

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