Prediction, conservation analysis, and structural characterization of mammalian mucin-type O-glycosylation sites
Prediction, conservation analysis, and structural characterization of mammalian mucin-type O-glycosylation sites
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DOI：
10.1093/glycob/cwh151
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发表时间：
2005-02-01
期刊：
影响因子：
4.3
通讯作者：
Brunak, S
中科院分区：
文献类型：
--
作者：
Julenius, K;Molgaard, A;Brunak, S
O - GalNAc糖基化是哺乳动物细胞中主要的糖基化类型之一。O - 糖基转移酶的共有识别序列尚不明确，这使得预测方法对于弥补大量已知蛋白质序列与少数经过糖基化状态实验研究的蛋白质之间的差距是必要的。从O - GLYCBASE中提取出了总共86种经过体内O - GalNAc位点实验研究的哺乳动物蛋白质。哺乳动物蛋白质同源性比较表明，糖基化的丝氨酸或苏氨酸比非糖基化的更不太可能被精确保守。对蛋白质数据库进行结构信息分析，获得了12种糖基化结构。所有阳性位点都在卷曲或转角区域被发现。一种使用神经网络方法预测粘蛋白型糖基化位点位置的方法经过了训练。最佳的综合网络使用氨基酸组成、平均表面可及性预测以及序列的替换矩阵图谱编码作为输入。为了提高对孤立（单个）位点的预测，仅针对孤立位点对网络进行了训练。最终的方法结合了来自最佳综合网络和最佳孤立位点网络的预测；这种预测方法正确预测了76%的糖基化残基和93%的非糖基化残基。NetOGlyc 3.1能够预测全新蛋白质的位点而不损失其性能。位点能够从平均特性进行预测以及糖基化位点不被精确保守这一事实表明，在大多数情况下，粘蛋白型糖基化是一种整体性质，而不是非常位点特异性的。NetOGlyc 3.1可在www.cbs.dtu.dk/services/netoglyc获取。
O-GalNAc-glycosylation is one of the main types of glycosylation in mammalian cells. No consensus recognition sequence for the O-glycosyltransferases is known, making prediction methods necessary to bridge the gap between the large number of known protein sequences and the small number of proteins experimentally investigated with regard to glycosylation status. From O-GLYCBASE a total of 86 mammalian proteins experimentally investigated for in vivo O-GalNAc sites were extracted. Mammalian protein homolog comparisons showed that a glycosylated serine or threonine is less likely to be precisely conserved than a nonglycosylated one. The Protein Data Bank was analyzed for structural information, and 12 glycosylated structures were obtained. All positive sites were found in coil or turn regions. A method for predicting the location for mucin-type glycosylation sites was trained using a neural network approach. The best overall network used as input amino acid composition, averaged surface accessibility predictions together with substitution matrix profile encoding of the sequence. To improve prediction on isolated (single) sites, networks were trained on isolated sites only. The final method combines predictions from the best overall network and the best isolated site network; this prediction method correctly predicted 76% of the glycosylated residues and 93% of the nonglycosylated residues. NetOGlyc 3.1 can predict sites for completely new proteins without losing its performance. The fact that the sites could be predicted from averaged properties together with the fact that glycosylation sites are not precisely conserved indicates that mucin-type glycosylation in most cases is a bulk property and not a very site-specific one. NetOGlyc 3.1 is made available at www.cbs.dtu.dk/services/netoglyc.