Identification of Residues in DmsD for Twin-Arginine Leader Peptide Binding, Defined through Random and Bioinformatics-Directed Mutagenesis
Bibliographic record
Abstract
The twin-arginine translocase (Tat) system is used for the targeting and translocation of folded proteins across the cell membrane of most bacteria. Substrates of this system contain a conserved "twin-arginine" (RR) motif within their signal/leader peptide sequence. Many Tat substrates have their own system-specific chaperone called redox enzyme maturation proteins (REMPs). Here, we study the binding of DmsD, the REMP for dimethyl sulfoxide reductase in Escherichia coli, toward the RR-containing leader peptide of the catalytic subunit DmsA. We have used a multipronged approach targeted at the amino acid sequence of DmsD to define residues and regions important for recognition of the DmsA leader sequence. Residues identified through bioinformatics and THEMATICS analysis were mutated using site-directed mutagenesis. These DmsD residue variants were purified and screened with an in vitro dot-blot far-Western assay to analyze the binding to the DmsA leader sequence. Degenerative polymerase chain reaction was also used to produce a bank of random DmsD amino acid mutants, which were then screened by an in vivo bacterial two-hybrid assay. Using this hybrid method, each DmsD variant was classified into one of three groups based on their degree of interaction with the DmsA leader (none, weak, and moderate). The data from both the in vitro and in vivo analyses were then applied to a model structure of DmsD based on the crystal structure of the Salmonella typhimurium homologue. Our results illustrate the positions of important DmsD residues involved in binding the DmsA leader peptide and identify a "hot pocket" of residues important for leader binding on the structure of DmsD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".