Cited by 2,466Computational Drug Discovery MethodsProtein Kinase Regulation and GTPase SignalingBioinformatics and Genomic Networks

A quantitative analysis of kinase inhibitor selectivity

Karaman, Mazen W, Herrgard, Sanna, Treiber, Daniel K, Gallant, Paul, Atteridge, Corey E, Campbell, Brian T, Chan, Katrina W, Ciceri, Pietro +13 more·2008·Nature Biotechnology

Abstract

Kinase inhibitors are a new class of therapeutics with a propensity to inhibit multiple targets. The biological consequences of multi-kinase activity are poorly defined, and an important step toward understanding the relationship between selectivity, efficacy and safety is the exploration of how inhibitors interact with the human kinome. We present interaction maps for 38 kinase inhibitors across a panel of 317 kinases representing >50% of the predicted human protein kinome. The data constitute the most comprehensive study of kinase inhibitor selectivity to date and reveal a wide diversity of interaction patterns. To enable a global analysis of the results, we introduce the concept of a selectivity score as a general tool to quantify and differentiate the observed interaction patterns. We further investigate the impact of panel size and find that small assay panels do not provide a robust measure of selectivity.

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Crossref · 10.1038/nbt1358

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  • No correlation was found between frequency of degradation and maximum observed protein abundance fold change for each kinase, with knowledge metrics such as the pubmed score and the number of entries in the PDB.

    “We found no correlation between these variables, consistent with evidence that kinase inhibitor pharmacophores display a high degree of polypharmacology”

    From Mapping the Degradable Kinome Provides a Resource for Expedited Degrader Development (2020) · cites this paper as Karaman et al., 2008

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Authors
Karaman, M. W., Herrgard, S., Treiber, D. K., Gallant, P., Atteridge, C. E., Campbell, B. T., Chan, K. W., Ciceri, P., Davis, M. I., Edeen, P. T., Faraoni, R., Floyd, M., Hunt, J. P., Lockhart, D. J., Milanov, Z. V., Morrison, M. J., Pallares, G., Patel, H. K., Pritchard, S., Wodicka, L. M., & Zarrinkar, P. P.
Affiliations
Tufts University (US)
Corresponding author
Zarrinkar, Patrick P
Venue
Nature Biotechnology
Published
2008-01
Volume
26
Issue
1
Pages
127-132
ISSN
  • 0733-222X (ISSN-L)
  • 1087-0156
  • 1546-1696
OpenAlex
W2100772783
Cited by
2,466
References
35
Citations by year
2026: 62 · 2025: 85 · 2024: 100 · 2023: 106 · 2022: 94 · 2021: 94 · 2020: 113 · 2019: 114 · 2018: 118 · 2017: 126 · 2016: 145 · 2015: 127 · 2014: 159 · 2013: 198 · 2012: 209
FWCI
288.89
Type
journal article
Language
en
Open access
closed
Locations
Nature Biotechnology (publishedVersion)
Funders
Bristol-Myers Squibb
Topics
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Kinase Regulation and GTPase Signaling
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Keywords
kinase inhibitors, kinase selectivity, human kinome, off-target effects, drug safety

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