High-Throughput Identification of Oncogenic Tyrosine Kinase Substrate Preferences to Improve Methods of Detection
Abstract
The use of computational approaches to understand kinase substrate preference has been a powerful tool in the search to develop artificial peptide probes to monitor kinase activity, however, most of these efforts focus on a small portion of the human kinome. The use of high throughput techniques to identify known kinase substrates plays an important role in development of sensitive protein kinase activity assays. The KINATEST-ID pipeline is an example of a computational tool that uses known kinase substrate sequence information to identify kinase substrate preference. This approach was used to design three artificial substrates for ABL, JAK2 and SRC family kinases. These biosensors were used to design ELISA and lanthanide-based assays to monitor in vitro kinase activity. The KINATEST-ID pipeline relies on a high number of reported kinase substrates to predict artificial substrate sequences, however, not all kinases have the sufficient number of known substrates to make an accurate prediction. The adaptation of kinase assay linked with phosphoproteomics technique was used to increase the number of known FLT3 kinase variant substrate sequences. Subsequently, a set of data formatting tools were developed to curate the mass spectrometry data to become compatible with a command line version of the KINATEST-ID pipeline modules. This approach was used to design seven pan-FLT3 artificial substrate (FAStides) sequences. The pair of FAStides that were deemed the most sensitive toward FLT3 kinase phosphorylation were assayed in increasing concentrations of clinically relevant tyrosine kinase inhibitors. To improve the automation of the mass spectrometry data analysis and formatting for use with the KINATEST-ID pipeline, a streamlined process was developed within a bioinformatic platform, GalaxyP. The data formatting tools used to process the FLT3 mass spectrometry data were converted into compatible versions to execute within the GalaxyP framework. This process was used to design four BTK artificial substrates (BAStide) to monitor kinase activity. Additionally, one of the BAStide sequences was designed in the lanthanide chelating motif to develop an antibody-free activity assay for BTK. Lastly, a multicolored time resolved lanthanide assay was designed by labeling SYK artificial substrate and a SRC family artificial substrate to measure the activity of both kinases in the same kinase reaction. This highlighted the functionality of lanthanide-based time resolved assays for potential multiplexing assay development.
Degree
Ph.D.
Advisors
Tao, Purdue University.
Subject Area
Design|Analytical chemistry|Artificial intelligence|Cellular biology|Chemistry|Mathematics|Medicine
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