Both Intrinsic Substrate Preference and Network Context Contribute to Substrate Selection of Classical Tyrosine Phosphatases.
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 specificityin vivoby 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 thein vitrosubstrate 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.
From the Department of Biology, University of Rome Tor Vergata, 00133 Rome, Italy.
Anita
0000-0002-5971-3676
A
Palma
From the Department of Biology, University of Rome Tor Vergata, 00133 Rome, Italy.
Michele
M
Tinti
From the Department of Biology, University of Rome Tor Vergata, 00133 Rome, Italy.
Serena
S
Paoluzi
From the Department of Biology, University of Rome Tor Vergata, 00133 Rome, Italy.
Elena
E
Santonico
the Centre for Integrative Bioinformatics, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands, and.
Bernd Willem
0000-0001-9701-4190
BW
Brandt
the Geneva Research Center, Merck Serono International, 1202 Geneva, Switzerland.
Rob
0000-0002-2261-9424
R
Hooft van Huijsduijnen
the Institut für Biochemie & Biotechnologie, Martin-Luther-Universität Halle-Wittenberg, 06108 Halle, Germany.
Antonia
A
Masch
the Centre for Integrative Bioinformatics, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands, and.
Jaap
0000-0001-8641-4930
J
Heringa
the Institut für Biochemie & Biotechnologie, Martin-Luther-Universität Halle-Wittenberg, 06108 Halle, Germany.
Mike
M
Schutkowski
From the Department of Biology, University of Rome Tor Vergata, 00133 Rome, Italy.
Luisa
0000-0001-5283-8671
L
Castagnoli
From the Department of Biology, University of Rome Tor Vergata, 00133 Rome, Italy, cesareni@uniroma2.it.
Gianni
0000-0002-9528-6018
G
Cesareni
D000595:Amino Acid Sequence; D001499:Bayes Theorem; D001665:Binding Sites; D006801:Humans; D008954:Models, Biological; D062105:Molecular Docking Simulation; D010748:Phosphopeptides / Q000737:chemistry / Q000378:metabolism*; D010766:Phosphorylation; D011487:Protein Conformation; D000072417:Protein Domains; D060066:Protein Interaction Maps; D017027:Protein Tyrosine Phosphatases / Q000737:chemistry / Q000378:metabolism*; D013379:Substrate Specificity
D010748:Phosphopeptides; D017027:Protein Tyrosine Phosphatases
Bayesian integration; peptide array; protein-protein interaction; recognition specificity; substrate specificity; systems biology; trapping mutants; tyrosine-protein phosphatase (tyrosine phosphatase)