Prediction and analysis of protein hydroxyproline and hydroxylysine.

<h4>Background</h4>Hydroxylation is an important post-translational modification and closely related to various diseases. Besides the biotechnology experiments, in silico prediction methods are alternative ways to identify the potential hydroxylation sites.<h4>Methodology/principal...

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Autores principales:	Le-Le Hu, Shen Niu, Tao Huang, Kai Wang, Xiao-He Shi, Yu-Dong Cai
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2010
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/c8fe1e188383442aa40004ed1a731efb
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spelling	oai:doaj.org-article:c8fe1e188383442aa40004ed1a731efb2021-11-18T07:00:52ZPrediction and analysis of protein hydroxyproline and hydroxylysine.1932-620310.1371/journal.pone.0015917https://doaj.org/article/c8fe1e188383442aa40004ed1a731efb2010-12-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21209839/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>Hydroxylation is an important post-translational modification and closely related to various diseases. Besides the biotechnology experiments, in silico prediction methods are alternative ways to identify the potential hydroxylation sites.<h4>Methodology/principal findings</h4>In this study, we developed a novel sequence-based method for identifying the two main types of hydroxylation sites--hydroxyproline and hydroxylysine. First, feature selection was made on three kinds of features consisting of amino acid indices (AAindex) which includes various physicochemical properties and biochemical properties of amino acids, Position-Specific Scoring Matrices (PSSM) which represent evolution information of amino acids and structural disorder of amino acids in the sliding window with length of 13 amino acids, then the prediction model were built using incremental feature selection method. As a result, the prediction accuracies are 76.0% and 82.1%, evaluated by jackknife cross-validation on the hydroxyproline dataset and hydroxylysine dataset, respectively. Feature analysis suggested that physicochemical properties and biochemical properties and evolution information of amino acids contribute much to the identification of the protein hydroxylation sites, while structural disorder had little relation to protein hydroxylation. It was also found that the amino acid adjacent to the hydroxylation site tends to exert more influence than other sites on hydroxylation determination.<h4>Conclusions/significance</h4>These findings may provide useful insights for exploiting the mechanisms of hydroxylation.Le-Le HuShen NiuTao HuangKai WangXiao-He ShiYu-Dong CaiPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 5, Iss 12, p e15917 (2010)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Le-Le Hu Shen Niu Tao Huang Kai Wang Xiao-He Shi Yu-Dong Cai Prediction and analysis of protein hydroxyproline and hydroxylysine.
description	<h4>Background</h4>Hydroxylation is an important post-translational modification and closely related to various diseases. Besides the biotechnology experiments, in silico prediction methods are alternative ways to identify the potential hydroxylation sites.<h4>Methodology/principal findings</h4>In this study, we developed a novel sequence-based method for identifying the two main types of hydroxylation sites--hydroxyproline and hydroxylysine. First, feature selection was made on three kinds of features consisting of amino acid indices (AAindex) which includes various physicochemical properties and biochemical properties of amino acids, Position-Specific Scoring Matrices (PSSM) which represent evolution information of amino acids and structural disorder of amino acids in the sliding window with length of 13 amino acids, then the prediction model were built using incremental feature selection method. As a result, the prediction accuracies are 76.0% and 82.1%, evaluated by jackknife cross-validation on the hydroxyproline dataset and hydroxylysine dataset, respectively. Feature analysis suggested that physicochemical properties and biochemical properties and evolution information of amino acids contribute much to the identification of the protein hydroxylation sites, while structural disorder had little relation to protein hydroxylation. It was also found that the amino acid adjacent to the hydroxylation site tends to exert more influence than other sites on hydroxylation determination.<h4>Conclusions/significance</h4>These findings may provide useful insights for exploiting the mechanisms of hydroxylation.
format	article
author	Le-Le Hu Shen Niu Tao Huang Kai Wang Xiao-He Shi Yu-Dong Cai
author_facet	Le-Le Hu Shen Niu Tao Huang Kai Wang Xiao-He Shi Yu-Dong Cai
author_sort	Le-Le Hu
title	Prediction and analysis of protein hydroxyproline and hydroxylysine.
title_short	Prediction and analysis of protein hydroxyproline and hydroxylysine.
title_full	Prediction and analysis of protein hydroxyproline and hydroxylysine.
title_fullStr	Prediction and analysis of protein hydroxyproline and hydroxylysine.
title_full_unstemmed	Prediction and analysis of protein hydroxyproline and hydroxylysine.
title_sort	prediction and analysis of protein hydroxyproline and hydroxylysine.
publisher	Public Library of Science (PLoS)
publishDate	2010
url	https://doaj.org/article/c8fe1e188383442aa40004ed1a731efb
work_keys_str_mv	AT lelehu predictionandanalysisofproteinhydroxyprolineandhydroxylysine AT shenniu predictionandanalysisofproteinhydroxyprolineandhydroxylysine AT taohuang predictionandanalysisofproteinhydroxyprolineandhydroxylysine AT kaiwang predictionandanalysisofproteinhydroxyprolineandhydroxylysine AT xiaoheshi predictionandanalysisofproteinhydroxyprolineandhydroxylysine AT yudongcai predictionandanalysisofproteinhydroxyprolineandhydroxylysine
_version_	1718424069968232448

Prediction and analysis of protein hydroxyproline and hydroxylysine.

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