World, meet @KinaseLibrary -- comprehensive data sets built on experimental phosphorylation data (including temporal alignment) that are poised to revolutionize many sectors of health. Great talk by @Tomer_M_Yaron of @DanaFarberNews at #AACR26 that sparked the imagination. Kinases: a treasure trove of untapped knowledge and progress.

4/ Through extensive signaling and cell biology experiments (including developing a SHP2 pY62 antibody in collaboration with @CellSignal), we delineate an RTK–SFK–SHP2–MAPK signaling axis. Initially we assumed RTKs themselves phosphorylated Y62, but this was not the case. Analysis using @KinaseLibrary developed by @CantleyLab instead pointed to SRC family kinases (SFKs). Using pharmacologic and genetic approaches we confirmed that SFKs drive SHP2 phosphorylation downstream of RTKs. A key experiment used SFK KO MEFs developed by Philippe Soriano, where SHP2 phosphorylation was essentially abolished, including Y62 as well as the canonical Y542/Y580 sites.

4/ Through extensive signaling and cell biology experiments we delineate an RTK–SFK–SHP2–MAPK signaling axis. Initially we assumed RTKs themselves phosphorylated Y62, but those experiments did not support direct phosphorylation. Analysis using @KinaseLibrary @CantleyLab instead pointed to SRC family kinases (SFKs). Using both pharmacologic and genetic approaches we confirmed that SFKs drive SHP2 phosphorylation downstream of RTKs. A key experiment used MEFs from an SFK KO mouse from Philippe Soriano, where SHP2 phosphorylation was essentially abolished, including Y62 as well as the canonical Y542/Y580 sites.

@CantleyLab Thanks for this open-source tool! In substrate scoring, how should we handle scenarios with multiple competing kinases? Any recommended threshold settings? Checked out the notebook—super useful! 🧪 #phosphoproteomics

Thank you for posting and sharing this. A very valuable tool.

Thanks for sharing this great work and this resource!

great UI design on the site - congrats.

🚀 We just launched the brand-new #KinaseLibrary website, directly connected to the recently released Python package! Explore kinase-substrate relationships, run enrichment analyses, and visualize phosphoproteomics data—no coding required! kinase-library.phosphosite.o… @KinaseLibrary

🚀 TL;DR: pip install kinase-library 🚀 We are excited to introduce #TheKinaseLibrary Python package! 🧵👇 @KinaseLibrary Jared_Johnson @Tomer_M_Yaron @CellSignal pypi.org/project/kinase-libr…

Today @MaayanLab updated #Enrichr maayanlab.cloud/Enrichr/ with a new version of the #KinaseLibrary kinase-library.phosphosite.o… combining data from these two papers: nature.com/articles/s41586-0… & nature.com/articles/s41586-0… #kinome #cellsignaling #CPTAC #CancerResearch

👀👀

Congratulations Tomer!

The tyrosine kinome was my very first rotation project back in October 2017. I used to take the entire time during lab meetings because Jared and Lew would get into a trance looking at matrices. Now our (second) baby is out! 🥳 @KinaseLibrary

Coming very soon -> the @KinaseLibrary #Python package, as well as new features for substrate predictions and enrichment analysis, including continuous enrichment methods, phosphopriming, lysine acetylation and more! 9/9

We are delighted to share the #tyrosine @KinaseLibrary, now in @Nature: nature.com/articles/s41586-0… Tyrosine predictions and enrichment analysis are now available: kinase-library.phosphosite.o… #TheKinaseLibrary #KL #part2 🧵 1/9

The Kinase Library #kinaselibrary