Nuclear Receptors <i>Homo sapiens</i> Rev-erbβ and <i>Drosophila melanogaster</i> E75 Are Thiolate-Ligated Heme Proteins Which Undergo Redox-Mediated Ligand Switching and Bind CO and NO
Bibliographic record
Abstract
Nuclear receptors E75, which regulates development in Drosophila melanogaster, and Rev-erbbeta, which regulates circadian rhythm in humans, bind heme within their ligand binding domains (LBD). The heme-bound ligand binding domains of E75 and Rev-erbbeta were studied using electronic absorption, MCD, resonance Raman, and EPR spectroscopies. Both proteins undergo redox-dependent ligand switching and CO- and NO-induced ligand displacement. In the Fe(III) oxidation state, the nuclear receptor hemes are low spin and 6-coordinate with cysteine(thiolate) as one of the two axial heme ligands. The sixth ligand is a neutral donor, presumably histidine. When the heme is reduced to the Fe(II) oxidation state, the cysteine(thiolate) is replaced by a different neutral donor ligand, whose identity is not known. CO binds to the Fe(II) heme in both E75(LBD) and Rev-erbbeta(LBD) opposite a sixth neutral ligand, plausibly the same histidine that served as the sixth ligand in the Fe(III) state. NO binds to the heme of both proteins; however, the NO-heme is 5-coordinate in E75 and 6-coordinate in Rev-erbbeta. These nuclear receptors exhibit coordination characteristics that are similar to other known redox and gas sensors, suggesting that E75 and Rev-erbbeta may function in heme-, redox-, or gas-regulated control of cellular function.
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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".