TY - JOUR
T1 - Systematic Discovery of In Vivo Phosphorylation Networks
AU - Linding, Rune
AU - Jensen, Lars Juhl
AU - Ostheimer, Gerard J.
AU - van Vugt, Marcel A.T.M.
AU - Jørgensen, Claus
AU - Miron, Ioana M.
AU - Diella, Francesca
AU - Colwill, Karen
AU - Taylor, Lorne
AU - Elder, Kelly
AU - Metalnikov, Pavel
AU - Nguyen, Vivian
AU - Pasculescu, Adrian
AU - Jin, Jing
AU - Park, Jin Gyoon
AU - Samson, Leona D.
AU - Woodgett, James R.
AU - Russell, Robert B B.
AU - Bork, Peer
AU - Yaffe, Michael B.
AU - Pawson, Tony
N1 - Funding Information:
Thanks to Sara Quirk, Jeff Wrana, John Scott, and Kresten Lindorff-Larsen for commenting on this manuscript. We are further indebted to Giselle Wiggin, Rizaldy Scott, Ivica Letunic, Jennifer Logan, Christian von Mering, Stephen A. Tate (ABI/Sciex), and Andrei Starostine for technical help and advice. This project was supported by the BioSapiens Network of Excellence (LSHG-CT-2003-503265), the EMBRACE project (LHSG-CT-2004-512092), and the GeneFun project (LSHG-CT-2004-503567), all funded by the European Commision FP6 Programme, the Danish Research Council for the Natural Sciences, the Lundbeck Foundation, Genome Canada through Ontario Genomics Institute, and the NIH Integrative Cancer Biology Program grant U54-CA112967-03. R.L. is a Human Frontier Science Program Fellow. M.V.V. is the recipient of a VENI grant from the Dutch Organization for Scientic Research. G.J.O. is the recipient of a Women's Excalibur Postdoctoral Fellowship (PF-06-094-01-CCG) from the American Cancer Society New England Division. J.J. and J.G.P. are recipients of the Canadian Institutes of Health Research postdoctoral fellowships. R.L., L.J.J., and F.D. conceived and designed the computational strategy. L.J.J. and R.L. implemented the algorithm. F.D. curated the MS data sets. R.B.R. collected domain sets. R.L., G.J.O., K.C., L.T., C.J., M.V.V., J.R.W., J.J., P.M., T.P., and M.B.Y. conceived and designed the experiments. G.J.O., V.N., L.T., I.M.M., C.J., M.V.V., J.J., R.L., K.E., K.C., and P.M. performed the experiments. L.D.S. contributed reagents. R.L., A.P., and J.G.P. developed the website. R.L., L.J.J., G.J.O., M.V.V., K.C., R.B.R., P.B., M.B.Y., and T.P. wrote the paper. The authors declare no competing financial interests.
PY - 2007/6/29
Y1 - 2007/6/29
N2 - Protein kinases control cellular decision processes by phosphorylating specific substrates. Thousands of in vivo phosphorylation sites have been identified, mostly by proteome-wide mapping. However, systematically matching these sites to specific kinases is presently infeasible, due to limited specificity of consensus motifs, and the influence of contextual factors, such as protein scaffolds, localization, and expression, on cellular substrate specificity. We have developed an approach (NetworKIN) that augments motif-based predictions with the network context of kinases and phosphoproteins. The latter provides 60%-80% of the computational capability to assign in vivo substrate specificity. NetworKIN pinpoints kinases responsible for specific phosphorylations and yields a 2.5-fold improvement in the accuracy with which phosphorylation networks can be constructed. Applying this approach to DNA damage signaling, we show that 53BP1 and Rad50 are phosphorylated by CDK1 and ATM, respectively. We describe a scalable strategy to evaluate predictions, which suggests that BCLAF1 is a GSK-3 substrate.
AB - Protein kinases control cellular decision processes by phosphorylating specific substrates. Thousands of in vivo phosphorylation sites have been identified, mostly by proteome-wide mapping. However, systematically matching these sites to specific kinases is presently infeasible, due to limited specificity of consensus motifs, and the influence of contextual factors, such as protein scaffolds, localization, and expression, on cellular substrate specificity. We have developed an approach (NetworKIN) that augments motif-based predictions with the network context of kinases and phosphoproteins. The latter provides 60%-80% of the computational capability to assign in vivo substrate specificity. NetworKIN pinpoints kinases responsible for specific phosphorylations and yields a 2.5-fold improvement in the accuracy with which phosphorylation networks can be constructed. Applying this approach to DNA damage signaling, we show that 53BP1 and Rad50 are phosphorylated by CDK1 and ATM, respectively. We describe a scalable strategy to evaluate predictions, which suggests that BCLAF1 is a GSK-3 substrate.
KW - CELLBIO
UR - http://www.scopus.com/inward/record.url?scp=34250743173&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34250743173&partnerID=8YFLogxK
U2 - 10.1016/j.cell.2007.05.052
DO - 10.1016/j.cell.2007.05.052
M3 - Article
C2 - 17570479
AN - SCOPUS:34250743173
SN - 0092-8674
VL - 129
SP - 1415
EP - 1426
JO - Cell
JF - Cell
IS - 7
ER -