Limits...
Computational prediction of O-linked glycosylation sites that preferentially map on intrinsically disordered regions of extracellular proteins.

Nishikawa I, Nakajima Y, Ito M, Fukuchi S, Homma K, Nishikawa K - Int J Mol Sci (2010)

Bottom Line: O-glycosylated sites were often found clustered along the sequence, whereas other sites were located sporadically.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.

View Article: PubMed Central - PubMed

Affiliation: College of Information Science and Engineering, Ritsumeikan University/Noji-higashi 1-1-1, Kusatsu, Shiga 525-8577, Japan; E-Mail: nakajima.yukiko@gmail.com.

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.

Show MeSH
(a) Prediction accuracies of the two SVMs for the clustered glycosylation. The crosses and circles represent the prediction obtained using the SVM trained by the clustered and isolated type, respectively. The input was the sequence information. (b) Prediction accuracies of the two SVMs for the isolated glycosylation. The crosses and circles represent the prediction obtained using the SVM trained by the isolated and clustered type, respectively.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
getmorefigures.php?uid=PMC3100847&req=5

f2-ijms-11-04991: (a) Prediction accuracies of the two SVMs for the clustered glycosylation. The crosses and circles represent the prediction obtained using the SVM trained by the clustered and isolated type, respectively. The input was the sequence information. (b) Prediction accuracies of the two SVMs for the isolated glycosylation. The crosses and circles represent the prediction obtained using the SVM trained by the isolated and clustered type, respectively.

Mentions: The difference between the two types of trained SVMs was demonstrated by comparing their prediction accuracies for both clustered and isolated types. Figure 2(a),(b) shows the prediction accuracies using the two SVMs for the clustered and isolated types, respectively. The input was sequence information. From the results shown in Figure 2, each SVM was specialized for the type used in the training.


Computational prediction of O-linked glycosylation sites that preferentially map on intrinsically disordered regions of extracellular proteins.

Nishikawa I, Nakajima Y, Ito M, Fukuchi S, Homma K, Nishikawa K - Int J Mol Sci (2010)

(a) Prediction accuracies of the two SVMs for the clustered glycosylation. The crosses and circles represent the prediction obtained using the SVM trained by the clustered and isolated type, respectively. The input was the sequence information. (b) Prediction accuracies of the two SVMs for the isolated glycosylation. The crosses and circles represent the prediction obtained using the SVM trained by the isolated and clustered type, respectively.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC3100847&req=5

f2-ijms-11-04991: (a) Prediction accuracies of the two SVMs for the clustered glycosylation. The crosses and circles represent the prediction obtained using the SVM trained by the clustered and isolated type, respectively. The input was the sequence information. (b) Prediction accuracies of the two SVMs for the isolated glycosylation. The crosses and circles represent the prediction obtained using the SVM trained by the isolated and clustered type, respectively.
Mentions: The difference between the two types of trained SVMs was demonstrated by comparing their prediction accuracies for both clustered and isolated types. Figure 2(a),(b) shows the prediction accuracies using the two SVMs for the clustered and isolated types, respectively. The input was sequence information. From the results shown in Figure 2, each SVM was specialized for the type used in the training.

Bottom Line: O-glycosylated sites were often found clustered along the sequence, whereas other sites were located sporadically.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.

View Article: PubMed Central - PubMed

Affiliation: College of Information Science and Engineering, Ritsumeikan University/Noji-higashi 1-1-1, Kusatsu, Shiga 525-8577, Japan; E-Mail: nakajima.yukiko@gmail.com.

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.

Show MeSH