Effects of FlAsH/Tetracysteine (TC) Tag on PrP Proteolysis and PrPres Formation by TC‐Scanning
Bibliographic record
Abstract
Protein-protein interactions associated with proteolytic processing and aggregation are integral to normal and pathological aspects of prion protein (PrP) biology. Characterization of these interactions requires the identification of amino acid residues involved. The FlAsH/tetracysteine (FlAsH/TC) tag is a small fluorescent tag amenable to insertion at internal sites in proteins. In this study, we used serial FlAsH/TC insertions (TC-scanning) as a probe to characterize sites of protein-protein interaction between PrP and other molecules. To explore this application in the context of substrate-protease interactions, we analyzed the effect of FlAsH/TC insertions on proteolysis of cellular prion protein (PrPsen) in in vitro reactions and generation of the C1 metabolic fragment of PrPsen in live neuroblastoma cells. The influence of FlAsH/TC insertion was evaluated by TC-scanning across the cleavage sites of each protease. The results showed that FlAsH/TC inhibited protease cleavage only within limited ranges of the cleavage sites, which varied from about one to six residues in width, depending on the protease, providing an estimate of the PrP residues interacting with each protease. TC-scanning was also used to probe a different type of protein-protein interaction: the conformational conversion of FlAsH-PrPsen to the prion disease-associated isoform, PrPres. PrP constructs with FlAsH/TC insertions at residues 90-96 but not 97-101 were converted to FlAsH-PrPres, identifying a boundary separating loosely versus compactly folded regions of PrPres. Our observations demonstrate that TC-scanning with the FlAsH/TC tag can be a versatile method for probing protein-protein interactions and folding processes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".