Comprehensive assay of kinase catalytic activity reveals features of kinase inhibitor selectivity
Open accessAbstract
Small-molecule protein kinase inhibitors are widely used to elucidate cellular signaling pathways and are promising therapeutic agents. Owing to evolutionary conservation of the ATP-binding site, most kinase inhibitors that target this site promiscuously inhibit multiple kinases. Interpretation of experiments that use these compounds is confounded by a lack of data on the comprehensive kinase selectivity of most inhibitors. Here we used functional assays to profile the activity of 178 commercially available kinase inhibitors against a panel of 300 recombinant protein kinases. Quantitative analysis revealed complex and often unexpected interactions between protein kinases and kinase inhibitors, with a wide spectrum of promiscuity. Many off-target interactions occur with seemingly unrelated kinases, revealing how large-scale profiling can identify multitargeted inhibitors of specific, diverse kinases. The results have implications for drug development and provide a resource for selecting compounds to elucidate kinase function and for interpreting the results of experiments involving kinase inhibitors.
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There is an overall reasonable agreement between binding affinities and kinase activity measured by Anastassiadis et al. (2011).
“While some of the observed bindings might not influence the activity of the respective kinases, there is an overall reasonable agreement between binding affinities and kinase activity measured by Anastassiadis et al. (2011) (Figures S2D and S2E).”
From Efficient Parameter Estimation Enables the Prediction of Drug Response Using a Mechanistic Pan-Cancer Pathway Model (2018) · cites this paper as Anastassiadis et al., 2011
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- Authors
- Anastassiadis, T., Deacon, S. W., Devarajan, K., Ma, H., & Peterson, J. R.
- Affiliations
- Fox Chase Cancer Center (US)
- Reaction Biology Corporation (United States) (US)
- Corresponding author
- Peterson, Jeffrey R
- Venue
- Nature Biotechnology
- Published
- 2011-10-30
- Volume
- 29
- Issue
- 11
- Pages
- 1039-1045
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- PMC
- PMC3230241
- OpenAlex
- W2152265294
- Cited by
- 919
- References
- 37
- Citations by year
- 2026: 50 · 2025: 58 · 2024: 55 · 2023: 51 · 2022: 59 · 2021: 64 · 2020: 58 · 2019: 68 · 2018: 59 · 2017: 71 · 2016: 62 · 2015: 72 · 2014: 82 · 2013: 74 · 2012: 34
- FWCI
- 60.56
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Biotechnology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Human Genome Research Institute (R01HG003818)
- National Cancer Institute (R44CA114995, P30CA006927)
- National Institute of General Medical Sciences (R01GM083025)
- 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
- Health Sciences › Medicine › Pathology and Forensic Medicine › Cancer Mechanisms and Therapy
- Keywords
- kinase inhibitors, kinase selectivity, off-target effects, ATP binding site, kinase activity, drug toxicity, kinase function
- MeSH terms
- Catalysis, Enzyme Stability, Humans, Protein Binding, Protein Kinases, Substrate Specificity, Drug Design, Signal Transduction, Protein Kinase Inhibitors, High-Throughput Screening Assays
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