New tools for evaluating protein tyrosine sulphation: Tyrosyl Protein Sulphotransferases (TPSTs) are novel targets for RAF protein kinase inhibitors
Bibliographic record
Abstract
ABSTRACT Protein tyrosine sulphation is a post-translational modification (PTM) best known for regulating extracellular protein-protein interactions. Tyrosine sulphation is catalysed by two Golgi-resident enzymes termed Tyrosyl Protein Sulpho Transferases (TPSTs) 1 and 2, which transfer sulphate from the co-factor PAPS (3’-phosphoadenosine 5’-phosphosulphate) to a context-dependent tyrosine in a protein substrate. A lack of quantitative tyrosine sulphation assays has hampered the development of chemical biology approaches for the identification of small molecule inhibitors of tyrosine sulphation. In this paper, we describe the development of a non-radioactive mobility-based enzymatic assay for TPST1 and TPST2, through which the tyrosine sulphation of synthetic fluorescent peptides can be rapidly quantified. We exploit ligand binding and inhibitor screens to uncover a susceptibility of TPST1 and 2 to different classes of small molecules, including the anti-angiogenic compound suramin and the kinase inhibitor rottlerin. By screening the Published Kinase Inhibitor Set (PKIS), we identified oxindole-based inhibitors of the Ser/Thr kinase RAF as low micromolar inhibitors of TPST1/2. Interestingly, unrelated RAF inhibitors, exemplified by the dual BRAF/VEGFR2 inhibitor RAF265, were also TPST inhibitors in vitro . We propose that target-validated protein kinase inhibitors could be repurposed, or redesigned, as more-specific TPST inhibitors to help evaluate the sulphotyrosyl proteome. Finally, we speculate that mechanistic inhibition of cellular tyrosine sulphation might be relevant to some of the phenotypes observed in cells exposed to anionic TPST ligands and RAF protein kinase inhibitors. SUMMARY STATEMENT We develop new assays to quantify tyrosine sulphation by the human tyrosine sulphotransferases TPST1 and 2. TPST1 and 2 catalytic activities are inhibited by protein kinase inhibitors, suggesting new starting points to synthesise (or repurpose) small molecule compounds to evaluate biological TPST using chemical biology.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".