title: OH-PRED: prediction of protein hydroxylation sites by incorporating adapted normal distribution bi-profile Bayes feature extraction and physicochemical properties of amino acids.
abstract: Hydroxylation of proline or lysine residues in proteins is a common post-translational modification event, and such modifications are found in many physiological and pathological processes. Nonetheless, the exact molecular mechanism of hydroxylation remains under investigation. Because experimental identification of hydroxylation is time-consuming and expensive, bioinformatics tools with high accuracy represent desirable alternatives for large-scale rapid identification of protein hydroxylation sites. In view of this, we developed a supporter vector machine-based tool, OH-PRED, for the prediction of protein hydroxylation sites using the adapted normal distribution bi-profile Bayes feature extraction in combination with the physicochemical property indexes of the amino acids. In a jackknife cross validation, OH-PRED yields an accuracy of 91.88% and a Matthew's correlation coefficient (MCC) of 0.838 for the prediction of hydroxyproline sites, and yields an accuracy of 97.42% and a MCC of 0.949 for the prediction of hydroxylysine sites. These results demonstrate that OH-PRED increased significantly the prediction accuracy of hydroxyproline and hydroxylysine sites by 7.37 and 14.09%, respectively, when compared with the latest predictor PredHydroxy. In independent tests, OH-PRED also outperforms previously published methods.
authors.affiliation: a Department of Mathematics , Dalian Maritime University , No. 1 Linghai Road, Dalian 116026 , China.
authors.forename: Cang-Zhi
authors.initials: CZ
authors.lastname: Jia
authors.affiliation: a Department of Mathematics , Dalian Maritime University , No. 1 Linghai Road, Dalian 116026 , China.
authors.forename: Wen-Ying
authors.initials: WY
authors.lastname: He
authors.affiliation: b Xiasha Higher Education Zone, College of Life Sciences, Zhejiang Sci-Tech University , 5 Second Avenue, Hangzhou 310018 , China.
authors.forename: Yu-Hua
authors.initials: YH
authors.lastname: Yao
mesh_terms: D000465:Algorithms; D000596:Amino Acids / Q000737:chemistry*; D001499:Bayes Theorem; D019295:Computational Biology; D006801:Humans; D006900:Hydroxylation; D016011:Normal Distribution; D056510:Position-Specific Scoring Matrices; D011506:Proteins / Q000737:chemistry*; D012984:Software; D060388:Support Vector Machine; D064878:Web Browser
chemical_list: D000596:Amino Acids; D011506:Proteins
keywords: ANBPB; SVM; physicochemical properties; protein hydroxylation