Incorporating significant amino acid pairs to identify O-linked glycosylation sites on transmembrane proteins and non-transmembrane proteins

<p>Abstract</p> <p>Background</p> <p>While occurring enzymatically in biological systems, O-linked glycosylation affects protein folding, localization and trafficking, protein solubility, antigenicity, biological activity, as well as cell-cell interactions on membrane p...

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Main Authors: Lee Tzong-Yi, Chen Shu-An, Ou Yu-Yen
Format: Article
Language:English
Published: BMC 2010-10-01
Series:BMC Bioinformatics
Online Access:http://www.biomedcentral.com/1471-2105/11/536
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spelling doaj-8431f25bbfba44c29c58df6812bfd8a12020-11-24T21:52:07ZengBMCBMC Bioinformatics1471-21052010-10-0111153610.1186/1471-2105-11-536Incorporating significant amino acid pairs to identify O-linked glycosylation sites on transmembrane proteins and non-transmembrane proteinsLee Tzong-YiChen Shu-AnOu Yu-Yen<p>Abstract</p> <p>Background</p> <p>While occurring enzymatically in biological systems, O-linked glycosylation affects protein folding, localization and trafficking, protein solubility, antigenicity, biological activity, as well as cell-cell interactions on membrane proteins. Catalytic enzymes involve glycotransferases, sugar-transferring enzymes and glycosidases which trim specific monosaccharides from precursors to form intermediate structures. Due to the difficulty of experimental identification, several works have used computational methods to identify glycosylation sites.</p> <p>Results</p> <p>By investigating glycosylated sites that contain various motifs between Transmembrane (TM) and non-Transmembrane (non-TM) proteins, this work presents a novel method, GlycoRBF, that implements radial basis function (RBF) networks with significant amino acid pairs (SAAPs) for identifying O-linked glycosylated serine and threonine on TM proteins and non-TM proteins. Additionally, a membrane topology is considered for reducing the false positives on glycosylated TM proteins. Based on an evaluation using five-fold cross-validation, the consideration of a membrane topology can reduce 31.4% of the false positives when identifying O-linked glycosylation sites on TM proteins. Via an independent test, GlycoRBF outperforms previous O-linked glycosylation site prediction schemes.</p> <p>Conclusion</p> <p>A case study of Cyclic AMP-dependent transcription factor ATF-6 alpha was presented to demonstrate the effectiveness of GlycoRBF. Web-based GlycoRBF, which can be accessed at <url>http://GlycoRBF.bioinfo.tw</url>, can identify O-linked glycosylated serine and threonine effectively and efficiently. Moreover, the structural topology of Transmembrane (TM) proteins with glycosylation sites is provided to users. The stand-alone version of GlycoRBF is also available for high throughput data analysis.</p> http://www.biomedcentral.com/1471-2105/11/536
collection DOAJ
language English
format Article
sources DOAJ
author Lee Tzong-Yi
Chen Shu-An
Ou Yu-Yen
spellingShingle Lee Tzong-Yi
Chen Shu-An
Ou Yu-Yen
Incorporating significant amino acid pairs to identify O-linked glycosylation sites on transmembrane proteins and non-transmembrane proteins
BMC Bioinformatics
author_facet Lee Tzong-Yi
Chen Shu-An
Ou Yu-Yen
author_sort Lee Tzong-Yi
title Incorporating significant amino acid pairs to identify O-linked glycosylation sites on transmembrane proteins and non-transmembrane proteins
title_short Incorporating significant amino acid pairs to identify O-linked glycosylation sites on transmembrane proteins and non-transmembrane proteins
title_full Incorporating significant amino acid pairs to identify O-linked glycosylation sites on transmembrane proteins and non-transmembrane proteins
title_fullStr Incorporating significant amino acid pairs to identify O-linked glycosylation sites on transmembrane proteins and non-transmembrane proteins
title_full_unstemmed Incorporating significant amino acid pairs to identify O-linked glycosylation sites on transmembrane proteins and non-transmembrane proteins
title_sort incorporating significant amino acid pairs to identify o-linked glycosylation sites on transmembrane proteins and non-transmembrane proteins
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2010-10-01
description <p>Abstract</p> <p>Background</p> <p>While occurring enzymatically in biological systems, O-linked glycosylation affects protein folding, localization and trafficking, protein solubility, antigenicity, biological activity, as well as cell-cell interactions on membrane proteins. Catalytic enzymes involve glycotransferases, sugar-transferring enzymes and glycosidases which trim specific monosaccharides from precursors to form intermediate structures. Due to the difficulty of experimental identification, several works have used computational methods to identify glycosylation sites.</p> <p>Results</p> <p>By investigating glycosylated sites that contain various motifs between Transmembrane (TM) and non-Transmembrane (non-TM) proteins, this work presents a novel method, GlycoRBF, that implements radial basis function (RBF) networks with significant amino acid pairs (SAAPs) for identifying O-linked glycosylated serine and threonine on TM proteins and non-TM proteins. Additionally, a membrane topology is considered for reducing the false positives on glycosylated TM proteins. Based on an evaluation using five-fold cross-validation, the consideration of a membrane topology can reduce 31.4% of the false positives when identifying O-linked glycosylation sites on TM proteins. Via an independent test, GlycoRBF outperforms previous O-linked glycosylation site prediction schemes.</p> <p>Conclusion</p> <p>A case study of Cyclic AMP-dependent transcription factor ATF-6 alpha was presented to demonstrate the effectiveness of GlycoRBF. Web-based GlycoRBF, which can be accessed at <url>http://GlycoRBF.bioinfo.tw</url>, can identify O-linked glycosylated serine and threonine effectively and efficiently. Moreover, the structural topology of Transmembrane (TM) proteins with glycosylation sites is provided to users. The stand-alone version of GlycoRBF is also available for high throughput data analysis.</p>
url http://www.biomedcentral.com/1471-2105/11/536
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