DeepNGlyPred: A Deep Neural Network-Based Approach for Human N-Linked Glycosylation Site Prediction.

DeepNGlyPred: A Deep Neural Network-Based Approach for Human N-Linked Glycosylation Site Prediction.
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DeepNGlyPred:一种基于深度神经网络的人类N-连接糖基化位点预测方法。

DOI:
10.3390/molecules26237314
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发表时间:
2021-12-02
期刊:
Molecules (Basel, Switzerland)
影响因子:
--
通讯作者:
Kc DB
Kc DB
中科院分区:
其他
文献类型:
--
作者:
Pakhrin SC;Aoki-Kinoshita KF;Caragea D;Kc DB

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蛋白质N-连接糖基化是一种翻译后修饰,在许多生物学过程中起着重要作用。计算预测方法作为糖基化位点表征的补充方法。大多数现有的N-连接糖基化的预测因子利用糖基化位点发生在N-X-[S/T]序列子的信息,其中X是除脯氨酸之外的任何氨基酸。并非所有的N-X-[S/T]序列子都是糖基化的,因此N-X-[S/T]序列子是蛋白质糖基化的必要但不是充分的决定因素。在这方面,仅限于N-X-[S/T]序列的N-连接糖基化位点的计算预测是一个重要的问题。在这里,我们报告了一种基于深度学习的方法DeepNGlyPred,该方法使用基于序列的特征(缺口二肽),预测的结构特征和进化信息编码人类蛋白质组数据集(从N-GlycositeAtlas中提取)中的阳性和阴性序列。DeepNGlyPred在N-GlyDE独立测试集上产生的SN、SP、MCC和ACC分别为88.62%、73.92%、0.60和79.41%,优于比较方法。这些结果表明,DeepNGlyPred是预测局限于N-X-[S/T]序列子的N-连接糖基化位点的稳健计算技术。DeepNGlyPred将成为糖生物学社区的有用资源。
Protein N-linked glycosylation is a post-translational modification that plays an important role in a myriad of biological processes. Computational prediction approaches serve as complementary methods for the characterization of glycosylation sites. Most of the existing predictors for N-linked glycosylation utilize the information that the glycosylation site occurs at the N-X-[S/T] sequon, where X is any amino acid except proline. Not all N-X-[S/T] sequons are glycosylated, thus the N-X-[S/T] sequon is a necessary but not sufficient determinant for protein glycosylation. In that regard, computational prediction of N-linked glycosylation sites confined to N-X-[S/T] sequons is an important problem. Here, we report DeepNGlyPred a deep learning-based approach that encodes the positive and negative sequences in the human proteome dataset (extracted from N-GlycositeAtlas) using sequence-based features (gapped-dipeptide), predicted structural features, and evolutionary information. DeepNGlyPred produces SN, SP, MCC, and ACC of 88.62%, 73.92%, 0.60, and 79.41%, respectively on N-GlyDE independent test set, which is better than the compared approaches. These results demonstrate that DeepNGlyPred is a robust computational technique to predict N-Linked glycosylation sites confined to N-X-[S/T] sequon. DeepNGlyPred will be a useful resource for the glycobiology community.
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发表时间: 2011-08-01
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