Current Bioinformatics

Yi-Ping Phoebe Chen
Department of Computer Science and Information Technology
La Trobe University
Melbourne
Australia

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Matching up Phosphosites to Kinases: A Survey of Available Predictive Programs

Author(s): Stefano Toppo, Lorenzo A. Pinna, Mauro Salvi.

Abstract:

Over the past few years, research in phosphoproteomic has assisted a tremendous revolution thanks to instrumental technologies advances in mass spectrometry combined with innovative experimental strategies. This has allowed the identification of thousands of high confidence phosphosites. Presently, almost 60000 non-redundant phosphosites have been identified from ∼10000 non-redundant proteins and about 80% of these phosphosites have been identified from high throughput experiments in the last six years. The vast majority of phosphosites are still functionally uncharacterized and the kinases responsible of their generation are almost unknown. Several computational approaches have been developed to link kinase families with putative substrates and although these are powerful tools, they are not commonly used. Here we discuss about the present approaches and tools developed for predicting the functional link between the kinases and their substrates.

Keywords: Phosphosites, kinase, predictive programs, consensus sequence

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Article Details

VOLUME: 5
ISSUE: 2
Year: 2010
Page: [141 - 152]
Pages: 12
DOI: 10.2174/157489310791268432
Price: $58