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Ridge regression estimated linear probability model predictions of O-glycosylation in proteins with structural and sequence data

Authors: Rajaram Gana; Sona Vasudevan;

Ridge regression estimated linear probability model predictions of O-glycosylation in proteins with structural and sequence data

Abstract

The likelihood of O-GlcNAc glycosylation in human proteins is predicted using the ridge regression estimated linear probability model (LPM). To achieve this, sequences from three similar post-translational modifications (PTMs) of proteins occurring at, or very near, the S or T site are analyzed: N-glycosylation, O-mucin type (O-GalNAc) glycosylation, and phosphorylation. Results found include: 1) The consensus composite sequon for O-glycosylation does NOT have W on either side of the glycosylation site. 2) The same holds for the consensus sequon for phosphorylation. 3) For LPM estimation, N-glycosylated sequences are found to be good approximations to non-O-glycosylatable sequences. 4) The selective positioning of an amino acid along the sequence, differentiates the PTMs of proteins. 5) Some N-glycosylated sequences are also phosphorylated at the S or T site. 6) ASA values for N-glycosylated sequences are stochastically larger than those for O-GlcNAc glycosylated sequences. 7) Structural attributes (beta turn II, II', helix, beta bridges, beta hairpin, and the phi angle) are significant LPM predictors of O-GlcNAc glycosylation. The LPM with sequence and structural data as explanatory variables yields a Kolmogorov-Smirnov (KS) statistic value of 99%. 8) With only sequence data, the KS statistic erodes to 80%, underscoring the germaneness of structural information, which is sparse on O-glycosylated sequences. With 50% as the cutoff probability for predicting O-GlcNAc glycosylation, this LPM mispredicts 21% of out-of-sample O-GlcNAc glycosylated sequences as not being glycosylated. The 95% confidence interval around this mispredictions rate is 16% to 26%

40 pages

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Keywords

Models, Molecular, Glycosylation, N-glycosylation, Quantitative Biology - Quantitative Methods, Statistics, Nonparametric, 62J05, 62J07, Consensus Sequence, Humans, Amino Acid Sequence, Amino Acids, Phosphorylation, Databases, Protein, Quantitative Methods (q-bio.QM), Probability, O-glycosylation, Analysis of Variance, QH573-671, phosphorylation, Proteins, Logistic Models, linear, FOS: Biological sciences, Linear Models, Cytology, consensus sequon, Protein Processing, Post-Translational, probability model, Research Article

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
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gold
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