Rational design of an estrogen receptor mutant with altered DNA-binding specificity
Bibliographic record
Abstract
Although artificial C2-H2 zinc fingers can be designed to recognize specific DNA sequences, it remains unclear to which extent nuclear receptor C4 zinc fingers can be tailored to bind novel DNA elements. Steroid receptors bind as dimers to palindromic response elements differing in the two central base pairs of repeated motifs. Predictions based on one amino acid-one base-pair relationships may not apply to estrogen receptors (ERs), which recognize the two central base pairs of estrogen response elements (EREs) via two charged amino acids, each contacting two bases on opposite DNA strands. Mutagenesis of these residues, E203 and K210 in ERalpha, indicated that both contribute to ERE binding. Removal of the electric charge and steric constraints associated with K210 was required for full loss of parental DNA-binding specificity and recognition of novel sequences by E203 mutants. Although some of the new binding profiles did not match predictions, the double mutation E203R-K210A generated as predicted a mutant ER that was transcriptionally active on palindromes of PuGCTCA motifs, but not on consensus EREs. This study demonstrates the feasibility of designing C4 zinc finger mutants with novel DNA-binding specificity, but also uncovers limitations of this approach.
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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".