Human iron regulatory protein 2 is easily cleaved in its specific domain: consequences for the haem binding properties of the protein
Bibliographic record
Abstract
Mammalian IRPs (iron regulatory proteins), IRP1 and IRP2, are cytosolic RNA-binding proteins that post-transcriptionally control the mRNA of proteins involved in storage, transport, and utilization of iron. In iron-replete cells, IRP2 undergoes degradation by the ubiquitin/proteasome pathway. Binding of haem to a 73aa-Domain (73-amino-acid domain) that is unique in IRP2 has been previously proposed as the initial iron-sensing mechanism. It is shown here that recombinant IRP2 and the 73aa-Domain are sensitive to proteolysis at the same site. NMR results suggest that the isolated 73aa-Domain is not structured. Iron-independent cleavage of IRP2 within the 73aa-Domain also occurs in lung cancer (H1299) cells. Haem interacts with a cysteine residue only in truncated forms of the 73aa-Domain, as shown by a series of complementary physicochemical approaches, including NMR, EPR and UV-visible absorption spectroscopy. In contrast, the cofactor is not ligated by the same residue in the full-length peptide or intact IRP2, although non-specific interaction occurs between these molecular forms and haem. Therefore it is unlikely that the iron-dependent degradation of IRP2 is mediated by haem binding to the intact 73aa-Domain, since the sequence resembling an HRM (haem-regulatory motif) in the 73aa-Domain does not provide an axial ligand of the cofactor unless this domain is cleaved.
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 | 0.000 |
| 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".