The induction of folding cooperativity by ligand binding drives the allosteric response of tetracycline repressor
Bibliographic record
Abstract
Tetracycline (Tc) repressor (TetR) undergoes an allosteric transition upon interaction with the antibiotic, Tc, that abrogates its ability to specifically bind its operator DNA. In this work, by performing equilibrium protein unfolding experiments on wild-type TetR and mutants displaying altered allosteric responses, we have delineated a model to explain TetR allostery. In the absence of Tc, we show that the DNA-binding domains of this homodimeric protein are relatively flexible and unfold independently of the Tc binding/dimerization (TBD) domains. Once Tc is bound, however, the unfolding of the DNA binding domains becomes coupled to the TBD domains, leading to a large increase in DNA-binding domain stability. Noninducible TetR mutants display considerably less interdomain folding cooperativity upon binding to Tc. We conclude that the thermodynamic coupling of the TetR domains caused by Tc binding and the resulting rigidification of the DNA-binding domains into a conformation that is incompatible with DNA binding are the fundamental factors leading to the allosteric response in TetR. This allosteric mechanism can account for properties of the whole TetR family of repressors and may explain the functioning and evolution of other allosteric systems. Our model contrasts with the prevalent view that TetR populates two distinct conformations and that Tc causes a switch between these defined conformations.
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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".