ArticleProtein science : a publication of the Protein Society1995
A sequence-coupled vector-projection model for predicting the specificity of GalNAc-transferase.
Article in Protein science : a publication of the Protein Society, 1995. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- RNAm5CPred: Prediction of RNA 5-Methylcytosine Sites Based on Three Different Kinds of Nucleotide Composition.Molecular therapy. Nucleic acids · 2019Article
- iRNAm5C-PseDNC: identifying RNA 5-methylcytosine sites by incorporating physical-chemical properties into pseudo dinucleotide composition.Oncotarget · 2017Article
- iRNA-PseColl: Identifying the Occurrence Sites of Different RNA Modifications by Incorporating Collective Effects of Nucleotides into PseKNC.Molecular therapy. Nucleic acids · 2017Article
- Article
- iPhos-PseEn: identifying phosphorylation sites in proteins by fusing different pseudo components into an ensemble classifier.Oncotarget · 2016Article
- iHyd-PseCp: Identify hydroxyproline and hydroxylysine in proteins by incorporating sequence-coupled effects into general PseAAC.Oncotarget · 2016Article
- iCar-PseCp: identify carbonylation sites in proteins by Monte Carlo sampling and incorporating sequence coupled effects into general PseAAC.Oncotarget · 2016Article
- Prediction of O-glycosylation sites based on multi-scale composition of amino acids and feature selection.Medical & biological engineering & computing · 2015Article
- iHyd-PseAAC: predicting hydroxyproline and hydroxylysine in proteins by incorporating dipeptide position-specific propensity into pseudo amino acid composition.International journal of molecular sciences · 2014Article
- iMethyl-PseAAC: identification of protein methylation sites via a pseudo amino acid composition approach.BioMed research international · 2014Article
- iNitro-Tyr: prediction of nitrotyrosine sites in proteins with general pseudo amino acid composition.PloS one · 2014Article
- Article
- A novel model to predict O-glycosylation sites using a highly unbalanced dataset.Glycoconjugate journal · 2012Article
- Article
- Predicting drug-target interaction networks based on functional groups and biological features.PloS one · 2010Article
- Prediction of mucin-type O-glycosylation sites in mammalian proteins using the composition of k-spaced amino acid pairs.BMC bioinformatics · 2008Article
- Classification of protein quaternary structure by functional domain composition.BMC bioinformatics · 2006Article
- Database analysis of O-glycosylation sites in proteins.Biophysical journal · 2001Article
- Using pair-coupled amino acid composition to predict protein secondary structure content.Journal of protein chemistry · 1999Article
- Structural features of the human salivary mucin, MUC7.Glycoconjugate journal · 1998Article
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Abstract
The specificity of GalNAc-transferase is consistent with the existence of an extended site composed of nine subsites, denoted by R4, R3, R2, R1, R0, R1', R2', R3', and R4', where the acceptor at R0 is either Ser or Thr to which the reducing monosaccharide is being anchored. To predict whether a peptide will react with the enzyme to form a Ser- or Thr-conjugated glycopeptide, a new method has been proposed based on the vector-projection approach as well as the sequence-coupled principle. By incorporating the sequence-coupled effect among the subsites, the interaction mechanism among subsites during glycosylation can be reflected and, by using the vector projection approach, arbitrary assignment for insufficient experimental data can be avoided. The very high ratio of correct predictions versus total predictions for the data in both the training and the testing sets indicates that the method is self-consistent and efficient. It provides a rapid means for predicting O-glycosylation and designing effective inhibitors of GalNAc-transferase, which might be useful for targeting drugs to specific sites in the body and for enzyme replacement therapy for the treatment of genetic disorders.
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