Identification of Novel Phosphorylation Motifs Through an Integrative Computational and Experimental Analysis of the Human Phosphoproteome
- *Corresponding Author:
- Dr. Akhilesh Pandey, M.D., Ph.D.,
733 N.Broadway Street, Broadway Research Building
Room 527, Baltimore, Maryland 21205, USA
Fax: (410) 502 7544
E-mail: [email protected]
Received Date: December 28, 2010; Accepted Date: January 28, 2011; Published Date: February 10, 2011
Citation: Amanchy R, Kandasamy K, Mathivanan S, Periaswamy B, Reddy R, et al. (2011) Identification of Novel Phosphorylation Motifs Through an Integrative Computational and Experimental Analysis of the Human Phosphoproteome. J Proteomics Bioinform 4: 022-035. doi: 10.4172/jpb.1000163
Copyright: © 2011 Amanchy R, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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.