Casting a Net for Kinases - Probabilistic Modeling of Cellular Signaling Systems

Rune Linding, Samuel Lunenfeld Research Institute and Massachusetts Institute of Technology

Abstract

Casting a Net for Kinases - Probabilistic Modelling of Cellular Signaling Systems 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, localisation 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 signalling, 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 GSK3 substrate. In my talk I will discuss our strategy for expansion of the NetworKIN framework to comprehensive modelling of mammalian signaling systems.

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