Glycosylation is one type of modification that chemically alters proteins by the enzymatic or non-enzymatic addition of glycans. PTMs are essential modifications that occur in higher eukaryotes. The process of post-translational modification (PTM) of proteins has allowed cells to vastly increase the otherwise normal array of functions that proteins carry out. The data indicates the existence of a consensus sequon for O-glycosylation and underscores the germaneness of structural information for predicting the likelihood of O-glycosylation. The 95% confidence interval around this mispredictions rate is 16% to 26%. 8) With only sequence data, the KS statistic erodes to 80%, and 21% of out-of-sample O-GlcNAc glycosylated sequences are mispredicted as not being glycosylated. The LPM with sequence and structural data as explanatory variables yields a Kolmogorov-Smirnov (KS) statistic of 99%. 7) Structural attributes (beta turn II, II´, helix, beta bridges, beta hairpin, and the phi angle) are significant LPM predictors of O-GlcNAc glycosylation.
6) ASA values for N-glycosylated sequences are stochastically larger than those for O-GlcNAc glycosylated sequences. 5) Some N-glycosylated sequences are also phosphorylated at the S/T-site in the N – ~P – S/T sequon. 4) The selective positioning of an amino acid along the sequence, differentiates the PTMs of proteins. 3) For linear probability model (LPM) estimation, N-glycosylated sequences are good approximations to non- O-glycosylatable sequences although N – ~P – S/T is not an absolute inhibitor of O-glycosylation. 2) The consensus sequon for phosphorylation is ~(W–S/T/Y/H–W) although W–S/T/Y/H–W is not an absolute inhibitor of phosphorylation. Results found include: 1) The consensus composite sequon for O-glycosylation is: ~(W–S/T–W), where “~” denotes the “not” operator. Three sequences from similar post-translational modifications (PTMs) of proteins occurring at, or very near, the S/T-site are analyzed: N-glycosylation, O-mucin type ( O-GalNAc) glycosylation, and phosphorylation. In particular, if a binary response is used to distinguish between O-glycosylated and non- O-glycosylated sequences, an appropriate set of non- O-glycosylatable sequences is hard to find. Thus, predicting the likelihood of O-glycosylation with sequence and structural information using classical regression analysis is quite difficult. To-date, no claim regarding finding a consensus sequon for O-glycosylation has been made.