1. Illuminating the dark kinome: utilizing multiplex peptide activity arrays to functionally annotate understudied kinases
- Author
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Abdul-rizaq Hamoud, Khaled Alganem, Sean Hanna, Michael Morran, Nicholas Henkel, Ali S. Imami, William Ryan, Smita Sahay, Priyanka Pulvender, Austin Kunch, Taylen O. Arvay, Jarek Meller, Rammohan Shukla, Sinead M. O’Donovan, and Robert McCullumsmith
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Medicine ,Cytology ,QH573-671 - Abstract
Abstract Protein kinases are critical components of a myriad biological processes and strongly associated with various diseases. While kinase research has been a point of focus in biomedical research for several decades, a large portion of the kinome is still considered understudied or “dark,” because prior research is targeted towards a subset of kinases with well-established roles in cellular processes. We present an empirical and in-silico hybrid workflow to extend the functional knowledge of understudied kinases. Utilizing multiplex peptide activity arrays and robust in-silico analyses, we extended the functional knowledge of five dark tyrosine kinases (AATK, EPHA6, INSRR, LTK, TNK1) and explored their roles in schizophrenia, Alzheimer’s dementia (AD), and major depressive disorder (MDD). Using this hybrid approach, we identified 195 novel kinase-substrate interactions with variable degrees of affinity and linked extended functional networks for these kinases to biological processes that are impaired in psychiatric and neurological disorders. Biochemical assays and mass spectrometry were used to confirm a putative substrate of EPHA6, an understudied dark tyrosine kinase. We examined the EPHA6 network and knowledgebase in schizophrenia using reporter peptides identified and validated from the multi-plex array with high affinity for phosphorylation by EPHA6. Identification and confirmation of putative substrates for understudied kinases provides a wealth of actionable information for the development of new drug treatments as well as exploration of the pathophysiology of disease states using signaling network approaches.
- Published
- 2024
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