Systematic and quantitative analysis of protein phosphorylation is revealing dynamic regulatory networks underlying cellular responses to environmental cues. However, matching these sites to the kinases that phosphorylate them and the phosphorylation-dependent binding domains that may subsequently bind to them remains a challenge. NetPhorest is an atlas of consensus sequence motifs that covers 179 kinases and 104 phosphorylation-dependent binding domains [Src homology 2 (SH2), phosphotyrosine binding (PTB), BRCA1 C-terminal (BRCT), WW, and 14–3–3]. The atlas reveals new aspects of signaling systems, including the observation that tyrosine kinases mutated in cancer have lower specificity than their non-oncogenic relatives. The resource is maintained by an automated pipe line, which uses phylogenetic trees to structure the currently available in vivo and in vitro data to derive probabilistic sequence models of linear motifs. The atlas is available as a community resource (http://netphorest.info).

Motivation: The 14-3-3 family of phosphoprotein-binding proteins regulates many cellular processes by docking onto pairs of phosphorylated Ser and Thr residues in a constellation of intracellular targets. Therefore, there is a pressing need to develop new prediction methods that use an updated set of 14-3-3-binding motifs for the identification of new 14-3-3 targets and to prioritize the downstream analysis of >2000 potential interactors identified in high-throughput experiments.Results: Here, a comprehensive set of 14-3-3-binding targets from the literature was used to develop 14-3-3-binding phosphosite predictors. Position-specific scoring matrix, support vector machines (SVM) and artificial neural network (ANN) classification methods were trained to discriminate experimentally determined 14-3-3-binding motifs from non-binding phosphopeptides. ANN, position-specific scoring matrix and SVM methods showed best performance for a motif window spanning from −6 to +4 around the binding phosphosite, achieving Matthews correlation coefficient of up to 0.60. Blind prediction showed that all three methods outperform two popular 14-3-3-binding site predictors, Scansite and ELM. The new methods were used for prediction of 14-3-3-binding phosphosites in the human proteome. Experimental analysis of high-scoring predictions in the FAM122A and FAM122B proteins confirms the predictions and suggests the new 14-3-3-predictors will be generally useful.Availability and implementation: A standalone prediction web server is available at http://www.compbio.dundee.ac.uk/1433pred. Human candidate 14-3-3-binding phosphosites were integrated in ANIA: ANnotation and Integrated Analysis of the 14-3-3 interactome database.Contact: cmackintosh@dundee.ac.uk or gjbarton@dundee.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online.

Understanding the consequences on host physiology induced by viral infection requires complete understanding of the perturbations caused by virus proteins on the cellular protein interaction network. The VirusMINT database (http://mint.bio.uniroma2.it/virusmint/) aims at collecting all protein interactions between viral and human proteins reported in the literature. VirusMINT currently stores over 5000 interactions involving more than 490 unique viral proteins from more than 110 different viral strains. The whole data set can be easily queried through the search pages and the results can be displayed with a graphical viewer. The curation effort has focused on manuscripts reporting interactions between human proteins and proteins encoded by some of the most medically relevant viruses: papilloma viruses, human immunodeficiency virus 1, Epstein–Barr virus, hepatitis B virus, hepatitis C virus, herpes viruses and Simian virus 40.

Missense PTPN11 mutations cause Noonan and LEOPARD syndromes (NS and LS), two developmental disorders with pleiomorphic phenotypes. PTPN11 encodes SHP2, an SH2 domain-containing protein tyrosine phosphatase functioning as a signal transducer. Generally, different substitutions of a particular amino acid residue are observed in these diseases, indicating that the crucial factor is the residue being replaced. For a few codons, only one substitution is observed, suggesting the possibility of specific roles for the residue introduced. We analyzed the biochemical behavior and ligand-binding properties of all possible substitutions arising from single-base changes affecting codons 42, 139, 279, 282 and 468 to investigate the mechanisms underlying the invariant occurrence of the T42A, E139D and I282V substitutions in NS and the Y279C and T468M changes in LS. Our data demonstrate that the isoleucine-to-valine change at codon 282 is the only substitution at that position perturbing the stability of SHP2's closed conformation without impairing catalysis, while the threonine-to-alanine change at codon 42, but not other substitutions of that residue, promotes increased phosphopeptide-binding affinity. The recognition specificity of the C-SH2 domain bearing the E139D substitution differed substantially from its wild-type counterpart acquiring binding properties similar to those observed for the N-SH2 domain, revealing a novel mechanism of SHP2's functional dysregulation. Finally, while functional selection does not seem to occur for the substitutions at codons 279 and 468, we point to deamination of the methylated cytosine at nucleotide 1403 as the driving factor leading to the high prevalence of the T468M change in LS.

Summary Members of the SH2 domain family modulate signal transduction by binding to short peptides containing phosphorylated tyrosines. Each domain displays a distinct preference for the sequence context of the phosphorylated residue. We have developed a new high-density peptide chip technology that allows probing the affinity of most SH2 domains for a large fraction of the entire complement of tyrosine phosphopeptides in the human proteome. Using this technique we have experimentally identified thousands of putative SH2- peptide interactions for more than 70 different SH2 domains. By integrating this rich data set with orthogonal context-specific information, we have assembled an SH2 mediated probabilistic interaction network, which we make available as a community resource in the PepSpotDB database. A new predicted dynamic interaction between the SH2 domains of the tyrosine phosphatase SHP2 and the phosphorylated tyrosine in the ERK activation loop was validated by experiments in living cells.