Biochemical and cellular characterization of the CISD3 protein: Molecular bases of cluster release and destabilizing effects of nitric oxide
Bibliographic record
Abstract
The NEET proteins, an important family of iron-sulfur (Fe-S) proteins, have generated a strong interest due to their involvement in diverse diseases such as cancer, diabetes and neurodegenerative disorders. Among the human NEET proteins, CISD3 has been the least studied, and its functional role is still largely unknown. We have investigated the biochemical features of CISD3 at the atomic and in cellulo levels upon challenge with different stress conditions i.e., iron deficiency, exposure to hydrogen peroxide and nitric oxide. The redox and cellular stability properties of the protein agree on a predominance of reduced form of CISD3 in the cells. Upon the addition of iron chelators, CISD3 loses its Fe-S clusters and becomes unstructured, and its cellular level drastically decreases. Chemical shift perturbation measurements suggest that, upon cluster oxidation, the protein undergoes a conformational change at the C-terminal CDGSH domain, which determines the instability of the oxidized state. This redox-associated conformational change may be the source of cooperative electron transfer via the two [Fe 2 S 2 ] clusters in CISD3, which displays a single sharp voltammetric signal at -31 mV vs SHE. Oxidized CISD3 is particularly sensitive to the presence of hydrogen peroxide in vitro , whereas only the reduced form is able to bind nitric oxide. Paramagnetic NMR provides clear evidence that, upon NO binding, the cluster is disassembled but iron ions are still bound to the protein. Accordingly, in cellulo CISD3 is unaffected by oxidative stress induced by hydrogen peroxide but it becomes highly unstable in response to nitric oxide treatment.
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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) | 0.000 | 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".