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Structural Bioinformatics-Based Design of Selective, Irreversible Kinase Inhibitors

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Cohen, Michael S., Zhang, Chao, Shokat, Kevan M., Taunton, Jack·2005·Science

Abstract

The active sites of 491 human protein kinase domains are highly conserved, which makes the design of selective inhibitors a formidable challenge. We used a structural bioinformatics approach to identify two selectivity filters, a threonine and a cysteine, at defined positions in the active site of p90 ribosomal protein S6 kinase (RSK). A fluoromethylketone inhibitor, designed to exploit both selectivity filters, potently and selectively inactivated RSK1 and RSK2 in mammalian cells. Kinases with only one selectivity filter were resistant to the inhibitor, yet they became sensitized after genetic introduction of the second selectivity filter. Thus, two amino acids that distinguish RSK from other protein kinases are sufficient to confer inhibitor sensitivity.

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Metadata

Authors
Cohen, M. S., Zhang, C., Shokat, K. M., & Taunton, J.
Venue
Science
Published
2005-05-27
Volume
308
Issue
5726
Pages
1318-1321
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2114869204
Cited by
506
References
0
FWCI
29.81
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Structural Bioinformatics-Based Design of Selective, Irreversible Kinase Inhibitors. https://app.cochat.ai/papers/10.1126/science1108367
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Cohen, M. S., Zhang, C., Shokat, K. M., & Taunton, J. (2005). Structural Bioinformatics-Based Design of Selective, Irreversible Kinase Inhibitors. Science. https://doi.org/10.1126/science1108367

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.