title: PhosphoPICK-SNP: quantifying the effect of amino acid variants on protein phosphorylation.
abstract: BACKGROUND
  Genome-wide association studies are identifying single nucleotide variants (SNVs) linked to various diseases, however the functional effect caused by these variants is often unknown. One potential functional effect, the loss or gain of protein phosphorylation sites, can be induced through variations in key amino acids that disrupt or introduce valid kinase binding patterns. Current methods for predicting the effect of SNVs on phosphorylation operate on the sequence content of reference and variant proteins. However, consideration of the amino acid sequence alone is insufficient for predicting phosphorylation change, as context factors determine kinase-substrate selection.
  
  
  RESULTS
  We present here a method for quantifying the effect of SNVs on protein phosphorylation through an integrated system of motif analysis and context-based assessment of kinase targets. By predicting the effect that known variants across the proteome have on phosphorylation, we are able to use this background of proteome-wide variant effects to quantify the significance of novel variants for modifying phosphorylation. We validate our method on a manually curated set of phosphorylation change-causing variants from the primary literature, showing that the method predicts known examples of phosphorylation change at high levels of specificity. We apply our approach to data-sets of variants in phosphorylation site regions, showing that variants causing predicted phosphorylation loss are over-represented among disease-associated variants.
  
  
  METHODS
  The method is freely available as a web-service at the website http://bioinf.scmb.uq.edu.au/phosphopick/snp.
  
  
  BACKGROUND
  m.boden@uq.edu.au.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: School of Chemistry and Molecular Biosciences, The University of Queensland, St Lucia, Australia.
authors.forename: Ralph
authors.initials: R
authors.lastname: Patrick
authors.affiliation: School of Chemistry and Molecular Biosciences, The University of Queensland, St Lucia, Australia.|Institute for Molecular Bioscience, The University of Queensland, St Lucia, Australia.|Australian Infectious Diseases Research Centre, The University of Queensland, St Lucia, Australia.
authors.forename: Bostjan
authors.initials: B
authors.lastname: Kobe
authors.affiliation: The University of Queensland Diamantina Institute, Translational Research Institute, Woolloongabba, QLD, Australia.
authors.forename: Kim-Anh
authors.initials: KA
authors.lastname: Lê Cao
authors.affiliation: School of Chemistry and Molecular Biosciences, The University of Queensland, St Lucia, Australia.|Institute for Molecular Bioscience, The University of Queensland, St Lucia, Australia.
authors.forename: Mikael
authors.initials: M
authors.lastname: Bodén
mesh_terms: D000595:Amino Acid Sequence; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D010766:Phosphorylation; D010770:Phosphotransferases / Q000378:metabolism*; D020641:Polymorphism, Single Nucleotide; D011485:Protein Binding; D011499:Protein Processing, Post-Translational / Q000235:genetics*; D012984:Software
chemical_list: D010770:Phosphotransferases