Literature DB >> 28159843

Both Intrinsic Substrate Preference and Network Context Contribute to Substrate Selection of Classical Tyrosine Phosphatases.

Anita Palma1, Michele Tinti1, Serena Paoluzi1, Elena Santonico1, Bernd Willem Brandt2, Rob Hooft van Huijsduijnen3, Antonia Masch4, Jaap Heringa2, Mike Schutkowski4, Luisa Castagnoli1, Gianni Cesareni5.   

Abstract

Reversible tyrosine phosphorylation is a widespread post-translational modification mechanism underlying cell physiology. Thus, understanding the mechanisms responsible for substrate selection by kinases and phosphatases is central to our ability to model signal transduction at a system level. Classical protein-tyrosine phosphatases can exhibit substrate specificity in vivo by combining intrinsic enzymatic specificity with the network of protein-protein interactions, which positions the enzymes in close proximity to their substrates. Here we use a high throughput approach, based on high density phosphopeptide chips, to determine the in vitro substrate preference of 16 members of the protein-tyrosine phosphatase family. This approach helped identify one residue in the substrate binding pocket of the phosphatase domain that confers specificity for phosphopeptides in a specific sequence context. We also present a Bayesian model that combines intrinsic enzymatic specificity and interaction information in the context of the human protein interaction network to infer new phosphatase substrates at the proteome level.
© 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Entities:  

Keywords:  Bayesian integration; peptide array; protein-protein interaction; recognition specificity; substrate specificity; systems biology; trapping mutants; tyrosine-protein phosphatase (tyrosine phosphatase)

Mesh:

Substances:

Year:  2017        PMID: 28159843      PMCID: PMC5377807          DOI: 10.1074/jbc.M116.757518

Source DB:  PubMed          Journal:  J Biol Chem        ISSN: 0021-9258            Impact factor:   5.157


  58 in total

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  2 in total

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