Chemical biology approaches for in vivo protein kinase substrate identification: PKCε as a model system
File(s)
Author(s)
Davis, Khalil
Type
Thesis
Abstract
The protein kinases are a large family of 538 proteins that, through the catalysis of gamma-phosphate transfer from ATP to their substrate proteins, play a central role in almost all biological signalling pathways. As such, knowledge of kinase substrates is critical for understanding cellular signalling pathways and biological processes in general. Aberrant protein kinase signalling resulting from mutation has been implicated in disease, especially in cancer, for which the protein kinase represents the most commonly mutated family of proteins. However, although a select few kinases have been characterised in relatively high detail, the majority of protein kinases are relatively uncharacterised and indeed almost nothing is known about half of protein kinases. This highlights the pressing need for new unbiased and systematic methods for identifying kinase substrates.
The aim of the work described in this thesis was to develop a method of identifying kinase substrates in their native cellular environment, using PKC as a model. Two approaches were employed that were designed to enable crosslinking of substrates either to the kinase itself or to compounds bound at the catalytic site of the kinase. The latter approach worked with an analogue sensitive form of PKC-epsilon but was found not to label substrates. In contrast, the direct incorporation of photocrosslinking side chains into PKC-epsilon using genetic codon expansion technology proved productive. In this direct labelling strategy, a site was identified that, when AbK was incorporated, led to crosslinking of endogenous proteins. Mass spectrometry analysis of purified crosslinked complexes led to the identification of a novel PKC-epsilon substrate, SERBP1, which was identified to localise to foci in mitosis in a PKC-epsilon-dependent manner. Finally, the use of an alternative photocrosslinker with a cleavable sidechain enabled the identification of several additional potential PKC-epsilon substrates that merit validation and further investigation. It is likely that the technique described in this thesis will prove to be applicable to other protein kinases, where it will prove to be a useful addition to the current repertoire of substrate identification techniques.
The aim of the work described in this thesis was to develop a method of identifying kinase substrates in their native cellular environment, using PKC as a model. Two approaches were employed that were designed to enable crosslinking of substrates either to the kinase itself or to compounds bound at the catalytic site of the kinase. The latter approach worked with an analogue sensitive form of PKC-epsilon but was found not to label substrates. In contrast, the direct incorporation of photocrosslinking side chains into PKC-epsilon using genetic codon expansion technology proved productive. In this direct labelling strategy, a site was identified that, when AbK was incorporated, led to crosslinking of endogenous proteins. Mass spectrometry analysis of purified crosslinked complexes led to the identification of a novel PKC-epsilon substrate, SERBP1, which was identified to localise to foci in mitosis in a PKC-epsilon-dependent manner. Finally, the use of an alternative photocrosslinker with a cleavable sidechain enabled the identification of several additional potential PKC-epsilon substrates that merit validation and further investigation. It is likely that the technique described in this thesis will prove to be applicable to other protein kinases, where it will prove to be a useful addition to the current repertoire of substrate identification techniques.
Version
Open Access
Date Issued
2019-01
Date Awarded
2019-08
Copyright Statement
Creative Commons Attribution NonCommercial Licence
License URL
Advisor
Armstrong, Alan
Parker, Peter
Mann, David
Publisher Department
Department of Chemistry and Life Sciences
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)