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Protein kinases
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Identification of Kinase-substrate Pairs Using High Throughput Screening
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Kinase Substrate Profiling Using a Proteome-wide Serine-Oriented Human Peptide Library.

Karl W Barber1,2, Chad J Miller3, Jay W Jun4,5

  • 1Department of Cellular & Molecular Physiology , Yale University , New Haven , Connecticut 06520 , United States.

Biochemistry
|June 20, 2018
PubMed
Summary

A new method, SERIOHL-KILR, rapidly identifies human kinase substrates by analyzing phosphorylated peptides. This technique overcomes limitations of existing methods, enabling direct mapping of substrates for pathway analysis.

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Area of Science:

  • Biochemistry
  • Molecular Biology
  • Proteomics

Background:

  • The human proteome contains over 500 protein kinases and numerous phosphorylation sites, but kinase-substrate relationships are largely unknown.
  • Existing methods for identifying kinase substrates are often technically challenging and use non-human or biased peptide pools.
  • Understanding kinase-substrate interactions is crucial for deciphering cellular signaling pathways.

Purpose of the Study:

  • To introduce and validate a novel method, SERIOHL-KILR (serine-oriented human library-kinase library reactions), for profiling kinase substrate specificity.
  • To identify candidate substrates for serine kinases using a comprehensive library of human peptides.
  • To demonstrate the method's ability to identify kinase-substrate motifs and analyze kinase mutants.

Main Methods:

  • Generation of a purified library of over 100,000 serine-oriented human peptides expressed in Escherichia coli.
  • In vitro kinase reactions followed by liquid chromatography and tandem mass spectrometry to identify phosphorylated peptides.
  • Comparison of SERIOHL-KILR results with a traditional positional scanning peptide library method using Protein Kinase A.
  • Profiling of cancer-associated PKCβ mutants to assess shifts in substrate specificity.

Main Results:

  • SERIOHL-KILR successfully identified predominant motif elements, comparable to established methods, when tested with Protein Kinase A.
  • The method revealed a shift in substrate specificity for cancer-associated PKCβ mutants, likely due to altered kinase-substrate interactions.
  • The technique allows for rapid identification of candidate kinase substrates directly mappable to human sequences.

Conclusions:

  • SERIOHL-KILR is an effective and rapid technique for profiling kinase substrate specificity and identifying novel human kinase substrates.
  • The method overcomes limitations of previous approaches by utilizing a comprehensive, human-derived peptide library.
  • SERIOHL-KILR is adaptable for diverse kinase studies and facilitates direct pathway analysis.