Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2024.11.22.624841

diaPASEF-Powered Chemoproteomics Enables Deep Kinome Interaction Profiling

Woods, K.·Rants'o, T. A.·Chan, A. M.·Sapre, T.·Mastin, G. E.·Maguire, K. M.·Ong, S.-E.·Golkowski, M.
View original source ↗Export metadata ↓

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 2nd generation (gen) kiCCA which utilizes data-independent acquisition (dia) with parallel accumulation serial fragmentation (PASEF) MS and a re-designed CCA algorithm with improved selection criteria and the ability to predict multiple kinase interaction partners of the same proteins. Using neuroblastoma cell line models of the noradrenergic-mesenchymal transition (NMT), we demonstrate that 2nd gen kiCCA (1) identified 6.1-times more kinase PPIs in native cell extracts compared to our 1st gen approach, (2) determined kinase-mediated signaling pathways that underly the neuroblastoma NMT, and (3) accurately predicted pharmacological targets for manipulating NMT states. Our 2nd gen kiCCA method is broadly useful for cell signaling research and kinase drug discovery.

Source connections

Explore related subjects

biochemistryPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Woods, K., Rants'o, T. A., Chan, A. M., Sapre, T., Mastin, G. E., Maguire, K. M., Ong, S.-E., Golkowski, M.. 2024-11-22. diaPASEF-Powered Chemoproteomics Enables Deep Kinome Interaction Profiling. https://doi.org/10.1101/2024.11.22.624841

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Impacts of Environmental Nickel and Chromium Exposure on the Blood Proteome of House Sparrows (Passer domesticus) in New Caledonia

New Caledonia holds some of the world's largest ultramafic mineral deposits, and nickel (Ni) smelting operations have created a gradient of Ni and chromium (Cr) contamination across the archipelago. Molecular impacts of Ni and Cr toxicity on wildlife remain largely unexplored. Here, we used the house sparrow (Passer domesticus) as a sentinel species to characterise the blood proteomic response to Ni and Cr exposure near the Doniambo smelter in Noumea. Blood was collected from 52 free-living sparrows across 18 sites classified by soil metal concentration. Plasma and blood cell pellet fractions were analysed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Plasma proteomics identified histidine-rich glycoprotein (HRG) as the most prominent responder, with approximately 2.1-fold elevation in exposed relative to low-exposure birds. HRG contains a conserved histidine-rich region that binds cations including divalent nickel, and paired plasma-liver analysis confirmed hepatic-driven synthesis. Blood cell pellet proteomics revealed that Ni-Cr co-exposure predominantly disrupts the nuclear compartment: histone depletion indicated chromatin collapse, NUP153 dysregulation impaired nuclear pore function, and VRK1/TRIP13 upregulation suggested DNA damage response activation coupled with mitotic checkpoint override. Concurrent RNA processing collapse (DDX17, DHX15, RBMX, ALYREF) and changes in telomere-associated proteins (TERF2IP, hnRNPA1 and VRK1) implicated disrupted genome maintenance. These findings identify HRG as a candidate plasma biomarker of Ni-Cr exposure and reveal a coordinated nuclear toxicity signature linking heavy metal contamination to DNA damage and epigenetic disruption in a free-living vertebrate.

biochemistry↗
bioRxiv2026

Programmable amide bond formation using de novo ligases

Amide bond formation is of central importance in the chemical industry, underpinning the synthesis of small bioactive molecules, macrocycles, peptides and their conjugates. Conventional methods of amide synthesis rely on stoichiometric coupling agents and costly protecting group manipulations. While biocatalysis can alleviate some of these challenges, enzymes typically operate across a narrow range of substrates and their adaptation to new coupling partners requires extensive engineering. Here we show that de novo amide ligases featuring a cysteine catalytic triad can be programmed computationally to operate across diverse substrate classes with high selectivity. We first designed complementary peptide ligases to selectively functionalise either the N-terminus or a single lysine residue of a polypeptide sequence containing 36 competing lysines. Crystal structures of both ligases show excellent agreement with the designs, with structural modelling suggesting that amidation outcompetes hydrolysis because the catalytically competent geometry forms only upon acceptor binding. We then extended our approach to the synthesis of small bioactive molecules by designing stereoselective ligases that mediate a key amide bonding forming step in the synthesis of the preventative HIV therapeutic lenacapavir. These results establish de novo enzyme design as a programmable platform for achieving selective amide bond formations across a wide range of molecular targets.

biochemistry↗
bioRxiv2026

EngA adopts multiple distinct conformational states during ribosome assembly

Ribosome assembly, a highly coordinated and crucial cellular process, is assisted by various assembly factors, including GTPases. EngA, an essential P-loop GTPase, is involved in late-stage assembly of the 50S ribosomal subunit. The structures of 50S ribosome in complex with EngA-bound GMPPNP, and EngA-bound GDP alone, without 50S subunit, have been reported previously. However, the molecular mechanism of EngA GTP hydrolysis-assisted 50S maturation remains poorly understood, and structures of the 50S ribosome in complex with EngA-bound GDP have yet to be deciphered. We have reported cryo- EM structures of the Mycobacterium smegmatis 50S ribosome in complex with EngA-bound GTP{gamma}S or GDP at 2.8 - 3.5 [A] resolution. Structural analysis revealed that EngA and 50S subunit undergo a coordinated structural rearrangement, and an assembly intermediate is formed in which the stem-loop of H80 makes base-pair interactions with the junction of H89 and H90, forming a unique stem-loop-junction (SLJ) motif. EngA-bound GDP adopts distinctly different conformations in its ribosome-bound and unbound states. In summary, this study proposed a multi-state conformational model for EngA-assisted ribosome assembly.

biochemistry↗