ArticlebioRxiv : the preprint server for biology2024
diaPASEF-Powered Chemoproteomics Enables Deep Kinome Interaction Profiling.
Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Protein-protein interactions (PPIs) underlie most biological functions. Devastating human conditions like cancers, neurological disorders, and infections, hijack PPI networks to initiate disease, and to drive disease progression. Understanding precisely how diseases remodel PPI networks can, therefore, help clarify disease mechanisms and identify therapeutic targets. Protein kinases control most cellular processes through protein phosphorylation. The 518 human kinases, known as the kinome, are frequently dysregulated in disease and highly druggable with ATP-competitive inhibitors. Kinase activity, localization, and substrate recognition are regulated by dynamic PPI networks composed of scaffolding and adapter proteins, other signaling enzymes like small GTPases and E3 ligases, and phospho-substrates. Accordingly, mapping kinase PPI networks can help determine kinome activation states, and, in turn, cellular activation states; this information can be used for studying kinase-mediated cell signaling, and for prioritizing kinases for drug discovery. Previously, we have developed a high-throughput method for kinome PPI mapping based on mass spectrometry (MS)-based chemoproteomics that we named kinobead competition and correlation analysis (kiCCA). Here, we introduce 2
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