Structure–function analysis of the <scp>LytM</scp> domain of <scp>EnvC</scp>, an activator of cell wall remodelling at the <i><scp>E</scp>scherichia coli</i> division site
Bibliographic record
Abstract
Proteins with LytM (Peptidase_M23) domains are broadly distributed in bacteria and have been implicated in a variety of important processes, including cell division and cell-shape determination. Most LytM-like proteins that have been structurally and/or biochemically characterized are metallo-endopeptidases that cleave cross-links in the peptidoglycan (PG) cell wall matrix. Notable exceptions are the Escherichia coli cell division proteins EnvC and NlpD. These LytM factors are not hydrolases themselves, but instead serve as activators that stimulate PG cleavage by target enzymes called amidases to promote cell separation. Here we report the structure of the LytM domain from EnvC, the first structure of a LytM factor implicated in the regulation of PG hydrolysis. As expected, the fold is highly similar to that of other LytM proteins. However, consistent with its role as a regulator, the active-site region is degenerate and lacks a catalytic metal ion. Importantly, genetic analysis indicates that residues in and around this degenerate active site are critical for amidase activation in vivo and in vitro. Thus, in the regulatory LytM factors, the apparent substrate binding pocket conserved in active metallo-endopeptidases has been adapted to control PG hydrolysis by another set of enzymes.
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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 | 0.001 |
| 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".