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. 2011;4(2):22-35.
doi: 10.4172/jpb.1000163.

Identification of Novel Phosphorylation Motifs Through an Integrative Computational and Experimental Analysis of the Human Phosphoproteome

Affiliations

Identification of Novel Phosphorylation Motifs Through an Integrative Computational and Experimental Analysis of the Human Phosphoproteome

Ramars Amanchy et al. J Proteomics Bioinform. 2011.

Abstract

Protein phosphorylation occurs in certain sequence/structural contexts that are still incompletely understood. The amino acids surrounding the phosphorylated residues are important in determining the binding of the kinase to the protein sequence. Upon phosphorylation these sequences also determine the binding of certain domains that specifically bind to phosphorylated sequences. Thus far, such 'motifs' have been identified through alignment of a limited number of well identified kinase substrates. RESULTS: Experimentally determined phosphorylation sites from Human Protein Reference Database were used to identify 1,167 novel serine/threonine or tyrosine phosphorylation motifs using a computational approach. We were able to statistically validate a number of these novel motifs based on their enrichment in known phosphopeptides datasets over phosphoserine/threonine/tyrosine peptides in the human proteome. There were 299 novel serine/threonine or tyrosine phosphorylation motifs that were found to be statistically significant. Several of the novel motifs that we identified computationally have subsequently appeared in large datasets of experimentally determined phosphorylation sites since we initiated our analysis. Using a peptide microarray platform, we have experimentally evaluated the ability of casein kinase I to phosphorylate a subset of the novel motifs discovered in this study. Our results demonstrate that it is feasible to identify novel phosphorylation motifs through large phosphorylation datasets. Our study also establishes peptide microarrays as a novel platform for high throughput kinase assays and for the validation of consensus motifs. Finally, this extended catalog of phosphorylation motifs should assist in a systematic study of phosphorylation networks in signal transduction pathways.

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Conflict of interest statement

Conflict of Interest: Jos Joore is VP of Array Technology at PepScan Systems.

Figures

Figure 1
Figure 1
Heat maps for amino acid distribution surrounding known phosphorylated tyrosine (A), serine (B) and threonine (C) peptides in the human phosphoproteome, derived from Human Protein Reference Database. Enrichment or depletion of amino acids at particular positions is shown in red or blue, respectively, and was calculated as described in materials and methods.
Figure 2
Figure 2
A schematic of the direct motif finding approach used in grouping peptide sequences into bins to derive novel phosphorylation motifs.
Figure 3
Figure 3
Distribution curves of select predicted novel phosphotyrosine (A-C) and phosphoserine/threonine (D-F) motifs. The X in red represents the relative risk for the motifs and the area under the curve to the left of X represents the number of permuted sequences with relative risk lesser than the motif under study. The phosphorylated residues are shown in red (pY) or blue (pS/pT).
Figure 4
Figure 4
Distribution curves of select known phosphotyrosine (A-C) and phosphoserine/threonine (D-F) motifs. The X in red represents the relative risk for the motifs and the area under the curve to the left of X represents the number of permuted sequences with relative risk lesser than the motif under study. The phosphorylated residues are shown in red (pY) or blue (pS/pT).
Figure 5
Figure 5
Distribution curves of known (A-C) and novel (D-F) phosphotyrosine motifs with insignificant p-values. The X in red represents the relative risk value for the motif, and the area under the curve to the left of X represents the number of permuted sequences with relative risk lesser than the motif under study.
Figure 6
Figure 6
Distribution curves of known (A-C) and novel (D-F) phosphoserine/threonine motifs with insignificant p-values. The X in red represents the relative risk value for the motif, and the area under the curve to the left of X represents the number of permuted sequences with relative risk lesser than the motif under study.
Figure 7
Figure 7
Peptide microarrays for validation of novel motifs (A) Casein Kinase I (CKI) assay was performed on custom peptide microarrays spotted with peptides from sequences not known to be phosphorylated but containing the predicted motifs. (B) Magnification of a section of the peptide microarray showing two peptides that were significantly phosphorylated. The peptides were spotted in triplicate and are indicated by circles. (C) A kernel distribution curve showing the intensity values calculated from CKI assays from exposure of peptide microarrays to a phosphorimager screen. The blue line represents intensity values of negative controls and the black line represents intensity values of peptides containing novel motifs (D) A bar graph showing the number of peptides containing novel predicted motifs that were spotted on the peptide microarrays and the number of peptides containing novel motifs that were phosphorylated by CKI.

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