4.4 Article

Kinase Substrate Profiling Using a Proteome-wide Serine-Oriented Human Peptide Library

期刊

BIOCHEMISTRY
卷 57, 期 31, 页码 4717-4725

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.biochem.8b00410

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资金

  1. National Science Foundation Graduate Research Fellowship [DGE-1122492]
  2. National Institutes of Health (NIH) [GM104047]
  3. NIH [GM117230, GM125951, DK017433, CA209992]
  4. Cancer Systems Biology Consortium (CSBC) Summer Research Fellowship
  5. Physical Sciences in Oncology Network (PS-ON) Summer Research Fellowship

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The human proteome encodes >500 protein kinases and hundreds of thousands of potential phosphorylation sites. However, the identification of kinase-substrate pairs remains an active area of research because the relationships between individual kinases and these phosphorylation sites remain largely unknown. Many techniques have been established to discover kinase substrates but are often technically challenging to perform. Moreover, these methods frequently rely on substrate reagent pools that do not reflect human protein sequences or are biased by human cell line protein expression profiles. Here, we describe a new approach called SERIOHL-KILR (serine-oriented human library-kinase library reactions) to profile kinase substrate specificity and to identify candidate substrates for serine kinases. Using a purified library of >100000 serine-oriented human peptides expressed heterologously in Escherichia coli, we perform in vitro kinase reactions to identify phosphorylated human peptide sequences by liquid chromatography and tandem mass spectrometry. We compare our results for protein kinase A to those of a well-established positional scanning peptide library method, certifying that SERIOHL-KILR can identify the same predominant motif elements as traditional techniques. We then interrogate a small panel of cancer-associated PKC beta mutants using our profiling protocol and observe a shift in substrate specificity likely attributable to the loss of key polar contacts between the kinase and its substrates. Overall, we demonstrate that SERIOHL-KILR can rapidly identify candidate kinase substrates that can be directly mapped to human sequences for pathway analysis. Because this technique can be adapted for various kinase studies, we believe that SERIOHL-KILR will have many new victims in the future.

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