Scansite 2.0: proteome-wide prediction of cell signaling interactions using short sequence motifs

By J. Obenauer, Lewis C. Cantley, Michael B. Yaffe. Nucleic Acids Res., 2003

1,718 citations recorded by the source corpus.

Subfields: Molecular Biology, Pharmacology

View Paper: https://www.semanticscholar.org/paper/fb04e214da3820c1ea8decfcf81735a1a859d7f5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

In Pharmacology

Citations in the corpus

Small molecule inhibition of the autophagy kinase ULK1 and identification of ULK1 substrates (2015, methodology): “A position-specific scoring matrix based on ULK1 peptide substrate specificity (Figure 1B) was used to bioinformatically search the human proteome for sites closely matching the ULK1 substrate consensus motif (Obenauer et al., 2003).”
Systematic discovery of in vivo phosphorylation networks. (2007, methodology): “The kinase family likely to be responsible for phosphorylation of a site is predicted by consensus motifs that model the known sequence preferences of kinase catalytic domains (Hjerrild et al., 2004; Obenauer et al., 2003).”
An iterative statistical approach to the identification of protein phosphorylation motifs from large-scale data sets (2005, background): “Only approximately one-tenth of the estimated 500–600 human protein serine, threonine and tyrosine kinases have known consensus sequences for their sites of phosphorylatio”
KinasePhos 2.0: a web server for identifying protein kinase-specific phosphorylation sites based on sequences and coupling patterns (2007, background): “0 (10) identified short protein sequence motifs that are recognized by modular signaling domains, phosphorylated by protein serine/threonine, tyrosine kinases or mediate specific interactions with protein or phospholipid ligands.”
Intrinsic disorder and functional proteomics. (2007, background): “Indeed servers exist for using sequence comparisons to find such functional motifs (127,208).”
DisProt: the Database of Disordered Proteins (2006, methodology): “Another approach, based on sequence comparison rather than analysis of structures in PDB, has been used to systematically identify short, linear motifs that bind to protein partners (20,21,36).”
GPS 2.0, a Tool to Predict Kinase-specific Phosphorylation Sites in Hierarchy *S (2008, methodology): “each kinase based on its known phosphorylation sites (14).”
MoRFpred, a computational tool for sequence-based prediction and characterization of short disorder-to-order transitioning binding regions in proteins (2012, background): “They are characterized by dips in the disorder predictions and higher hydrophobicity and stability when compared to adjacent (in the chain) residues.”
KinasePhos: a web tool for identifying protein kinase-specific phosphorylation sites (2005, background): “0 (5) identified short protein motifs that are recognized by phosphorylation protein serine/threonine or tyrosine kinases.”
Evolutionary and Physiological Importance of Hub Proteins (2006, neutral): “edu [43] using a high stringency cut-off.”
NetworKIN: a resource for exploring cellular phosphorylation networks (2007, methodology): “This network is based on four fundamentally diﬀerent types of evidence: genomic context (gene fusion, gene neighbourhood and phylogentic proﬁles), primary experimental evidence (physical protein interactions and gene co-expression), manually curated We ﬁrst compare these phosphorylation sites to con”