St. Jude Children’s Research Hospital supports blue-sky ideas that can address critical patient care needs, fundamental basic science questions or gaps in our administrative processes.

We are excited to announce a new blue-sky initiative on “Seeing the Invisible in Protein Kinases”, an interdisciplinary project at the Department of Structural Biology. Our large-scale project aims to leverage ultra-high field NMR to detect and characterize rare conformational states in protein kinases. Such states underpin regulatory, oncogenic and drug-resistance mechanisms and offer new opportunities for therapeutic intervention.

We will extend the breakthrough approaches developed recently by the Kalodimos lab (Science 370, eabc2754, 2020) to study the human kinome. This strategy will be integrated with and complemented by data-science and computational approaches developed by the Babu lab (e.g. Cell 172, 41–54, 2018 and Nature 587, 650–656, 2020), to systematically characterize the conformational landscape of the human kinome.

This initiative is supported by U.S. $50 million in institutional funding. For more information, please read our Strategic Plan.

Join our team

We expect this initiative to have a profound impact on the field, transforming our understanding of protein kinases. We are looking for enthusiastic researchers to join this project in a variety of roles.

For any inquiries, please contact BlueSkyKinases@STJUDE.ORG

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Scientists on this team will express and purify protein kinases from different systems and prepare them for structural analyses.

NMR spectroscopy

Scientists on this team will use ultra-high field NMR instrumentation to detect and structurally characterize distinct conformational states in protein kinases. 


Scientists on this team will construct web portals and curate biological knowledge. Scientists will develop computational tools, including machine learning approaches to analyze and integrate sequences and structural information on protein kinases.

Candidates with Master's or PhD in Computational Biology, Bioinformatics or Computer Science are preferred.