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Detecting protease substrates using unnatural amino acids

Final Report Summary - TAGGING PROTEOLYSIS (Detecting protease substrates using unnatural amino acids)

Applying arginylation for proteomics:

The detection and analysis of peptides, and therefore proteins, using electro spray mass spectrometry requires a proton to be secured to a peptide during the ionisation phase. This proton is typically secured via basic amino acids. Basic residues on the C-terminus of a peptide are generated during trypsin digest, while the N-terminus typically lacks basic amino acids. Arginylation is an enzymatic process which adds a basic amino acid to the N-terminus of a peptide. I was able to establish arginylation for proteomics and, as hypothesised, the additional basic residue increased the charge of the peptide. The increase in charge on the N-terminus together with a basic residue on the C-terminus lead to the ability to perform bi-directional peptide sequencing. This 2x coverage is now exploited for exact phospho site determination, as phospho sites are difficult to pin point, especially when there are multiple phosphorylatable amino acids per peptide.

The application of arginylation for proteomics is three-fold: First, theoretical scientists studying proton transfer and peptide backbone cleavage caused by protons can apply arginylation as the conjugation of a basic amino acid to the N-terminus of a peptide provides a tool to generate peptides with both N- and C-terminal basic amino acids. Arginylation enables the theoretical scientists to perform their studies of peptides with basic residues on both termini on a larger more comprehensive scale than synthesizing individual peptides alone. Second, for proteomics research, as arginylation provides an additional charge to peptides which may have previously not been selected for MS/MS fragmentation due to mono charge state, e.g. highly acidic or short peptides. Further, proteomics researchers now have a tool to pin point exactly a phosphorylation site, which is a crucial point of information for the third target group: translational clinical research. Phosphorylation sites are crucial for protein signalling networks to function. A certain phosphorylation site might have a high correlation with disease progression or prognosis. Hence an antibody against the phosphorylation site, determined using arginylation, will be raised and used in a clinical diagnostic setting using ELISA.

Perturbed protein signalling analysis:

Perturbed protein signalling networks are frequently the cause for disease, as the normal flow of information is perturbed. This flow of signalling information is governed by many factors, one of which is the amount of proteins (or nodes) present in the signalling cascade. I have contributed to a collaborative effort to determine protein concentrations using targeted mass spectrometry, namely selected reaction monitoring mass spectrometry. The research shows, that signalling networks are very sensitive to changes in protein concentrations, especially when these changes in protein concentration are close to the original stimuli. The flow of information can be changed by altering protein concentrations within the signalling cascade. The accompanying manuscript (Kiel et al.) is submitted.

From these observations arose the need to further study protein concentrations, not as a function of different cell types as discussed above, but as a function of clinically relevant drug(s) or combinations thereof. In a collaboration with Chris Sander's group from the Sloan Kettering Cancer Center, New York City, United States (US), a prostate cancer cell line was perturbed using a range of clinically relevant drugs with the goal of finding additive and/or synergistic drug combination with the newly approved prostate cancer treatment drug enzalutamide. Results from this study could immediately be translated into the clinic, as all drugs are currently available and approved for treatment of prostate cancer.

List of keywords:
Arginylation, proteomics tool, phosphosite annotation, perturbed network analysis, prostate cancer, enzalutamide

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