Kinases play a critical role in cellular signaling and are dysregulated in a number of diseases, such as cancer, diabetes, and neurodegeneration. Therapeutics targeting kinases currently account for roughly 50% of cancer drug discovery efforts. The ability to explore human kinase biochemistry and biophysics in the laboratory is essential to designing selective inhibitors and studying drug resistance. Bacterial expression systems are superior to insect or mammalian cells in terms of simplicity and cost effectiveness but have historically struggled with human kinase expression. Following the discovery that phosphatase coexpression produced high yields of Src and Abl kinase domains in bacteria, we have generated a library of 52 His-tagged human kinase domain constructs that express above 2 μg/mL of culture in an automated bacterial expression system utilizing phosphatase coexpression (YopH for Tyr kinases and lambda for Ser/Thr kinases). Here, we report a structural bioinformatics approach to identifying kinase domain constructs previously expressed in bacteria and likely to express well in our protocol, experiments demonstrating our simple construct selection strategy selects constructs with good expression yields in a test of 84 potential kinase domain boundaries for Abl, and yields from a high-throughput expression screen of 96 human kinase constructs. Using a fluorescence-based thermostability assay and a fluorescent ATP-competitive inhibitor, we show that the highest-expressing kinases are folded and have well-formed ATP binding sites. We also demonstrate that these constructs can enable characterization of clinical mutations by expressing a panel of 48 Src and 46 Abl mutations. The wild-type kinase construct library is available publicly via Addgene.
Bibliographical noteFunding Information:
*E-mail: email@example.com. ORCID John D. Chodera: 0000-0003-0542-119X Present Address @S.G.: Caribou Biosciences, Berkeley, CA 94720. Author Contributions ○S.K.A. and D.L.P. contributed equally to this work. ^M.I. and L.R.-L. contributed equally to this work. Conceptualization: J.D.C., D.L.P., S.K.A., M.I., L.R.-L., S.M.H., N.M.L., and M.A.S. Methodology: D.L.P., M.I., L.R.-L., S.M.H., S.K.A., J.D.C., N.M.L., and M.A.S. Software: D.L.P., J.D.C., and S.M.H. Formal analysis: S.K.A., J.D.C., M.I., and S.M.H. Investigation: M.I., L.R.-L., S.G., C.J., S.K.A., and S.M.H. Resources: C.J. and S.G. Data curation: S.K.A., M.I., L.R.-L., D.L.P., and J.M.B. Writing the original draft: S.K.A., L.R.-L., D.L.P., J.D.C., S.G., S.M.H., and M.I. Review and editing: S.K.A., J.D.C., M.I., L.R.-L., S.M.H., S.G., C.J., N.M.L., and M.A.S. Visualization: S.K.A., J.D.C., M.I., and S.M.H. Supervision: J.D.C., N.M.L., and M.A.S. Project administration: S.K.A., J.D.C., M.I., and S.M.H. Funding acquisition: J.D.C. and S.M.H. Funding D.L.P., S.M.H., L.R.-L., S.K.A., M.I., and J.D.C. acknowledge support from the Sloan Kettering Institute. This work was funded in part by the Marie-Joseé and Henry R. Kravis Center for Molecular Oncology, the National Institutes of Health (NIH) (Grant R01 GM121505 and National Cancer Institute Cancer Center Core Grant P30 CA008748), the Functional Genomics Institute (FGI) at the Memorial Sloan Kettering Cancer Center, and a Louis V. Gerstner Young Investigator Award. M.A.S. acknowledges funding support by NIH Grant R35 GM119437. Notes The authors declare the following competing financial interest(s): J.D.C. is a member of the Scientific Advisory Board for Schrodinger, LLC.
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