CIA, a Novel Estrogen Receptor Coactivator with a Bifunctional Nuclear Receptor Interacting Determinant
Bibliographic record
Abstract
Coregulators for nuclear receptors (NR) are factors that either enhance or repress their transcriptional activity. Both coactivators and corepressors have been shown to use similar but functionally distinct NR interacting determinants containing the core motifs LxxLL and PhixxPhiPhi, respectively. These interactions occur through a hydrophobic cleft located on the surface of the ligand-binding domain (LBD) of the NR and are regulated by ligand-dependent activation function 2 (AF-2). In an effort to identify novel coregulators that function independently of AF-2, we used the LBD of the orphan receptor RVR (which lacks AF-2) as bait in a yeast two-hybrid screen. This strategy led to the cloning of a nuclear protein referred to as CIA (coactivator independent of AF-2 function) that possesses both repressor and activator functions. Strikingly, we observed that CIA not only interacts with RVR and Rev-ErbAalpha in a ligand-independent manner but can also form complexes with estrogen receptor alpha (ERalpha) and ERbeta in vitro and enhances ERalpha transcriptional activity in the presence of estradiol (E(2)). CIA-ERalpha interactions were found to be independent of AF-2 and enhanced by the antiestrogens EM-652 and ICI 182,780 but not by 4-hydroxytamoxifen and raloxifene. We further demonstrate that CIA-ERalpha interactions require the presence within CIA of a novel bifunctional NR recognition determinant containing overlapping LxxLL and PhixxPhiPhi motifs. The identification and functional characterization of CIA suggest that hormone binding can create a functional coactivator interaction interface in the absence of AF-2.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".