Characterization of HD-PTP phosphatase activity and identification of its substratesbinding partners
Bibliographic record
Abstract
Histidine-Domain-Protein-Tyrosine-Phosphatase (HD-PTP) has been classified as a non-transmembrane protein tyrosine phosphatase (PTP), however, its catalytic activity has not been appropriately characterized. In this thesis, the tyrosine phosphatase activity of HD-PTP was characterized. To do so, the HD-PTP protein was successfully purified using the FLAG-TAG purification system and an enzymatic assay was carried out using the DiFMUP fluorogenic substrate. My results suggest that HD-PTP is an inactive PTP that can be reactivated upon the back mutation of a conserved amino acid located in its catalytic domain motif 9, which diverges from the PTP consensus sequence. Interestingly, the gene which encodes for HD-PTP is located within the tumor suppressor region on the human chromosome 3p21.3. Furthermore, we determined through colony formation assays that the active mutation does not affect the tumor suppressor potential of HD-PTP. Although wild type HD-PTP is an inactive tyrosine phosphatase, it may act as a natural trapping mutant, thus preserving its strong binding potential for phosphorylated signaling proteins. Since the active HD-PTP mutant should have lost its ability to bind phosphorylated signaling proteins, it was used in a substrate trapping experiment to identify potential binding partners. Four putative binding partners were then purified and identified through multidimensional protein identification technique (MudPIT). Lastly, cell lines that stably express HD-PTP were generated for future studies in the identification of binding partners.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".