<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
Protein phosphorylation is a complex network of signaling and regulatory events that affects virtually every cellular process. Our understanding of the nature of this network as a whole remains limited, largely because of an array of technical challenges in the isolation and high-throughput sequencing of phosphorylated species. In the present work, we demonstrate that a combination of tandem phosphopeptide enrichment methods, high performance MS, and optimized database search/data filtering strategies is a powerful tool for surveying the phosphoproteome. Using our integrated analytical platform, we report the identification of 5,635 nonredundant phosphorylation sites from 2,328 proteins from mouse liver. From this list of sites, we extracted both novel and known motifs for specific Ser/Thr kinases including a “dipolar” motif. We also found that C-terminal phosphorylation was more frequent than at any other location and that the distribution of potential kinases for these sites was unique. Finally, we identified double phosphorylation motifs that may be involved in ordered phosphorylation.
Proteomics, Amino Acid Motifs, Molecular Sequence Data, Mass Spectrometry, Mice, Liver, Animals, Amino Acid Sequence, Phosphorylation, Liver Extracts, Peptides, Algorithms, Signal Transduction
Proteomics, Amino Acid Motifs, Molecular Sequence Data, Mass Spectrometry, Mice, Liver, Animals, Amino Acid Sequence, Phosphorylation, Liver Extracts, Peptides, Algorithms, Signal Transduction
citations 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). | 669 | |
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. | Top 1% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 0.1% |