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Cited by 526

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A Method to Identify Serine Kinase Substrates

Open access
Kane, Susan, Sano, Hiroyuki, Liu, Simon C.H., Asara, John M., Lane, William S., Garner, Charles C., Lienhard, Gustav E.·2002·Journal of Biological Chemistry

Abstract

This study describes a method for the identification of the substrates of specific serine kinases. An antibody specific for the phosphomotif generated by the kinase is used to isolate phosphorylated substrates by immunoprecipitation, and the isolated proteins are identified by tandem mass spectrometry of peptides. This method was applied to the identification of substrates for the protein kinase Akt, which specifically phosphorylates the RXRXXS/T motif. 3T3-L1 adipocytes were treated with insulin to activate Akt, and the putative Akt substrate proteins were isolated by immunoprecipitation with an antibody against the phospho form of this motif. This led to the identification of a novel 160-kDa substrate for Akt. The 160-kDa substrate for Akt, which was designated AS160, has a Rab GAP domain. Recombinant AS160 was shown to be a substrate for Akt, and two sites of phosphorylation, both in RXRXXS/T motifs, were identified by mass spectrometry and mutation. Insulin treatment of adipocytes caused AS160 to redistribute from the low density microsomes to the cytosol.

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Metadata

Authors
Kane, S., Sano, H., Liu, S. C. H., Asara, J. M., Lane, W. S., Garner, C. C., & Lienhard, G. E.
Venue
Journal of Biological Chemistry
Publisher
Elsevier BV
Published
2002-06
Volume
277
Issue
25
Pages
22115-22118
ISSN
0021-9258 (ISSN-L)
OpenAlex
W2076075378
Cited by
526
References
1
FWCI
9.58
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: A Method to Identify Serine Kinase Substrates. https://app.cochat.ai/papers/10.1074/jbc.c200198200
The paper
Kane, S., Sano, H., Liu, S. C. H., Asara, J. M., Lane, W. S., Garner, C. C., & Lienhard, G. E. (2002). A Method to Identify Serine Kinase Substrates. Journal of Biological Chemistry. https://doi.org/10.1074/jbc.c200198200

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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.