Phosphoproteome sequence analysis and significance: Mining association patterns around phosphorylation sites utilizing MAPRes

Abstract

Phosphorylation, one of the most common protein post-translational modifications (PTMs) on hydroxyl groups of S/T/Y is catalyzed by kinases and involves the presence or absence of certain amino acid residues in the vicinity of the phosphorylation sites. Using MAPRes, we have analyzed the substrate proteins of Phospho.ELM 7.0 and found that there are both general and specific requirements for the presence or absence of particular amino acids in the vicinity of phosphorylated S/T/Y for both of the phosphorylation data, whether or not kinase information was taken into account. Patterns extracted by MAPRes for kinase-specific data have been utilized to find the consensus sequence motifs for various kinases required to catalyze the process of phosphorylation on S/T/Y. These consensus sequences for different kinase groups, families, and individual members are consistent with those described earlier with some novel consensus reported for the first time. A comparison study for the patterns mined by MAPRes with the results of existing prediction methods was performed by searching for these patterns in the vicinity of phosphorylation sites predicted by different available method. This comparison resulted in 87-98% conformity with the results of the predictions by available methods. Additionally, the patterns mined by MAPRes for substrate sites included 61 kinases, the highest number analyzed so far.

Exploring the Sequence Context of Phosphorylatable Amino Acids: The Contribution of the Upgraded MAPRes Tool

“…In silico studies are therefore useful to identify the influence of surrounding amino acids on the modification potential of phosphorylatable Ser/Thr/Tyr residues. The sequence pattern of amino acids in the primary sequence around phosphorylated Ser/Thr/Tyr has been described earlier [Zhu et al, ; Qazi et al, ; Ahmad et al,,, ], but further examination of the biophysical and biochemical properties of surrounding amino acids are critically important to define how amino acids are selected for modification. For instance, MAPRes was utilized to assess the properties (biophysical and biochemical) of amino acids surrounding acetylation sites.…”

“…For instance, MAPRes was utilized to assess the properties (biophysical and biochemical) of amino acids surrounding acetylation sites. The results obtained from such studies stressed the importance of the nature of surrounding residues as well as their properties [Qazi et al, ; Ahmad et al, ; Ahmad et al, ; Iqbal et al, ].…”

“…The total number of records in a dataset that have a certain pattern is the support level of that pattern while the ratio of the support value to the total number of records in a dataset is the confidence level of the pattern. MAPRes has been implemented on different modified protein datasets [Ahmad et al, ; Ahmad et al, ; Iqbal et al, ].…”

In silico prediction and characterization of protein post-translational modifications

“…Reproduced from Figure 1 (panel A), Figure 3 (panel B) and Figure 4 (panel C) in [119]. M A N U S C R I P T phosphorylation general and kinase-specific sites [7] kinase-specificity with indirect relationship [8] phosphorylation and conformational flexibility [9] association patterns around phosphorylation sites [10] random forests [11] relevance units machines [12] sequence with feature selection [13] in eukaryotes [14] in bacteria [15] lysine acetylation support vector machines [16,17] bi-relative adapted binomial score Bayes feature representation [18] logistic regression classifiers [19] solvent accessibility and acetylation [20] PTM crosstalk [21] combination of multiple features [22] position-specificity [23] sequence and functional features [24] characterization of KAT acetylation sites [25] proteome-wide prediction [26] lysine acetylation in context [27] prediction of KAT acetylation sites [28] lysine methylation combination of multiple features [22] conditional random field [29] composition of K-spaced amino acid pairs [30] glycosylation O-glycosylation [31] N-, O-and C-glycosites in eukaryotes [32] in evolutionarily distant eukaryotes [33] O-GlcNAc [34] amidation feature selection [35] -carboxylation random forest [36] scoring matrices based on evolutionary information [37] disulfides feature selection [38] S-glutathionylation protein sequence …”

Charge and Polarity Preferences for N-Glycosylation: A Genome-Wide In Silico Study and Its Implications Regarding Constitutive Proliferation and Adhesion of Carcinoma Cells

“…The statistical analysis of the sequence contexts for N -glycosylation (preferred and non-preferred motifs) is needed to explore the biological relationships between sequence, structure, and function of glycoproteins. MAPRes is a valuable tool to define the significantly preferred and non-preferred amino acids in the vicinity of a N -glycosylation site by resorting to the association rule mining technique ( 12 , 28 ). The association pattern/rule is established between two or more frequently occurring entities that are in correlation.…”