Kinase Inhibitor Screening In Self-assembled Human Protein Microarrays

Fernanda Festa, Joshua Labaer

Research output: Contribution to journalArticle

Abstract

The screening of kinase inhibitors is crucial for better understanding properties of a drug and for the identification of potentially new targets with clinical implications. Several methodologies have been reported to accomplish such screening. However, each has its own limitations (e.g., the screening of only ATP analogues, restriction to using purified kinase domains, significant costs associated with testing more than a few kinases at a time, and lack of flexibility in screening protein kinases with novel mutations). Here, a new protocol that overcomes some of these limitations and can be used for the unbiased screening of kinase inhibitors is presented. A strength of this method is its ability to compare the activity of kinase inhibitors across multiple proteins, either between different kinases or different variants of the same kinase. Self-assembled protein microarrays generated through the expression of protein kinases by a human-based in vitro transcription and translation system (IVTT) are employed. The proteins displayed on the microarray are active, allowing for measurement of the effects of kinase inhibitors. The following procedure describes the protocol steps in detail, from the microarray generation and screening to the data analysis.

Original languageEnglish (US)
JournalJournal of visualized experiments : JoVE
Issue number152
DOIs
StatePublished - Oct 23 2019

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Protein Array Analysis
Microarrays
Screening
Phosphotransferases
Proteins
Protein Kinases
Adenosinetriphosphate
Transcription
Adenosine Triphosphate
Testing
Costs and Cost Analysis
Mutation
Costs

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)
  • Chemical Engineering(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)

Cite this

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Kinase Inhibitor Screening In Self-assembled Human Protein Microarrays. / Festa, Fernanda; Labaer, Joshua.

In: Journal of visualized experiments : JoVE, No. 152, 23.10.2019.

Research output: Contribution to journalArticle

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