Back

Structural Identification of Major Molecular Determinants for Phosphotyrosine Recognition in Tyrosine Kinases Reveals Tumour Promoting and Suppressive Functions

Cheng, N.; Millan-Barea, L. R.; Creixell, M.; Barr, A. R.; Kong, Y. W.; Joughin, B. A.; Lopez, C. K.; Lengefeld, J.; Clarke, J.; Liu, C.; Sriram, G.; Gonzalez-Robles, T. J.; van de Kooij, B.; Savickas, S.; Schoof, E. M.; Johnson, J. L.; Bakal, C.; Cantley, L. C.; Chiarle, R.; Pritchard, J.; Hubbard, S.; Huntly, B. J. P.; Hemann, M.; Creixell, P.; Yaffe, M. B.

2025-06-11 biochemistry
10.1101/2025.06.10.658871 bioRxiv
Show abstract

Protein tyrosine kinases activate signaling pathways by catalyzing the phosphorylation of tyrosine residues in their substrates. Mounting evidence suggests that, in addition to recognizing phosphorylated tyrosine (pTyr) residues through specific phosphobinding modules, many protein kinases selectively recognize pTyr directly adjacent to the tyrosine residue they phosphorylate and catalyze the formation of twin pTyr-pTyr sites. Here, we demonstrate the importance of this phosphopriming-driven twin pTyr signaling in promoting cell cycle progression through the cell cycle-inhibitory protein p27Kip1. We identify, structurally resolve, and tune two distinct molecular determinants driving the selective recognition of pTyr directly N- and C-terminal to the target phospho-acceptor tyrosine site. We further show structural and biochemical conservation in this recognition, and identify cancer-associated alterations to these determinants that are unable to recognize phosphoprimed substrates. Finally, using an in vivo mouse model of leukemia we show that Bcr-Abl mutants unable to recognize phosphoprimed substrates paradoxically result in enhanced tumor development and progression. These data indicate that Bcr-Abl, like other proto-oncogenes such as Ras or Myc, engages both pro- and anti-oncogenic programs - but in the case of Bcr-Abl, this is accomplished through a mechanism involving traditional and phosphoprimed substrate recognition.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.