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Computational Prediction of O-linked Glycosylation Sites that Preferentially Map on Intrinsically Disordered Regions of Extracellular Proteins
College of Information Science and Engineering, Ritsumeikan University/Noji-higashi 1-1-1, Kusatsu, Shiga 525-8577, Japan
College of Life Sciences, Ritsumeikan University/Noji-higashi 1-1-1, Kusatsu, Shiga 525-8577, Japan
Center for Information Biology & DNA Data Bank of Japan, National Institute of Genetics/Yata 1111, Mishima, Shizuoka 411-8540, Japan
Department of Bioinformatics, Maebashi Institute of Technology/Kamisadori 460-1, Maebashi, Gunma 371-0816, Japan
* Author to whom correspondence should be addressed.
Received: 28 October 2010; in revised form: 17 November 2010 / Accepted: 30 November 2010 / Published: 3 December 2010
Abstract: O-glycosylation of mammalian proteins is one of the important posttranslational modifications. We applied a support vector machine (SVM) to predict whether Ser or Thr is glycosylated, in order to elucidate the O-glycosylation mechanism. O-glycosylated sites were often found clustered along the sequence, whereas other sites were located sporadically. Therefore, we developed two types of SVMs for predicting clustered and isolated sites separately. We found that the amino acid composition was effective for predicting the clustered type, whereas the site-specific algorithm was effective for the isolated type. The highest prediction accuracy for the clustered type was 74%, while that for the isolated type was 79%. The existence frequency of amino acids around the O-glycosylation sites was different in the two types: namely, Pro, Val and Ala had high existence probabilities at each specific position relative to a glycosylation site, especially for the isolated type. Independent component analyses for the amino acid sequences around O-glycosylation sites showed the position-specific existences of the identified amino acids as independent components. The O-glycosylation sites were preferentially located within intrinsically disordered regions of extracellular proteins: particularly, more than 90% of the clustered O-GalNAc glycosylation sites were observed in intrinsically disordered regions. This feature could be the key for understanding the non-conservation property of O-glycosylation, and its role in functional diversity and structural stability.
Keywords: protein O-glycosylation; mucin-type; posttranslational modification; support vector machine; clustered and isolated glycosylation sites; intrinsically disordered; extracellular protein; non-conservation property
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MDPI and ACS Style
Nishikawa, I.; Nakajima, Y.; Ito, M.; Fukuchi, S.; Homma, K.; Nishikawa, K. Computational Prediction of O-linked Glycosylation Sites that Preferentially Map on Intrinsically Disordered Regions of Extracellular Proteins. Int. J. Mol. Sci. 2010, 11, 4991-5008.
Nishikawa I, Nakajima Y, Ito M, Fukuchi S, Homma K, Nishikawa K. Computational Prediction of O-linked Glycosylation Sites that Preferentially Map on Intrinsically Disordered Regions of Extracellular Proteins. International Journal of Molecular Sciences. 2010; 11(12):4991-5008.
Nishikawa, Ikuko; Nakajima, Yukiko; Ito, Masahiro; Fukuchi, Satoshi; Homma, Keiichi; Nishikawa, Ken. 2010. "Computational Prediction of O-linked Glycosylation Sites that Preferentially Map on Intrinsically Disordered Regions of Extracellular Proteins." Int. J. Mol. Sci. 11, no. 12: 4991-5008.