Conformation of the Cell Division Regulator MinE: Evidence for Interactions between the Topological Specificity and Anti-MinCD Domains
Bibliographic record
Abstract
Symmetric division of Gram-negative bacteria depends on the combined action of three proteins that ensure correct positioning of the cell division septum, namely, MinC, MinD, and MinE. To achieve this function, MinC and MinD form a membrane-bound complex that blocks cell division at all potential sites. Opposing this inhibition is MinE, which interacts with MinD via its N-terminal anti-MinCD domain to site-specifically counter the action of the MinCD complex. The anti-MinCD domain has been proposed to bind MinD in a helical conformation; however, little is actually known about the structure of this functionally critical region. To understand how MinE can perform its anti-MinCD function, we have therefore investigated the conformation of the full-length MinE from Neisseria gonorrhoeae by solution NMR. Although solubility considerations required the use of sample conditions that limit the observation of amide resonances to regions that are protected from solvent exchange, backbone chemical shifts from both N- and C-terminal domains could be assigned. In contrast to previous models, secondary chemical shift analysis of these solvent-protected regions shows that parts of the N-terminal anti-MinCD domain are stably folded with many functionally important residues localizing to a beta-structure. In addition, this N-terminal domain may be interacting with the C-terminal topological specificity domain, since mutations made in one domain led to NMR spectral changes in both domains. The nonfunctional MinE mutant L22D showed even larger evidence of structural perturbations in both domains, with significant destabilization of the entire MinE structure. Overall, these results suggest that there is an intimate structural association between the anti-MinCD and topological specificity domains, allowing the functional properties of the two domains to be modulated through this interaction.
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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".