Elucidation of eukaryotic elongation factor-2 contact sites within the catalytic domain of Pseudomonas aeruginosa exotoxin A
Bibliographic record
Abstract
Pseudomonas aeruginosa produces the virulence factor, ETA (exotoxin A), which catalyses an ADP-ribosyltransferase reaction of its target protein, eEF2 (eukaryotic elongation factor-2). Currently, this protein-protein interaction is poorly characterized and this study was aimed at identifying the contact sites between eEF2 and the catalytic domain of ETA (PE24H, an ETA from P. aeruginosa, a 24 kDa C-terminal fragment containing a His6 tag). Single-cysteine residues were introduced into the toxin at 21 defined surface-exposed sites and labelled with the fluorophore, IAEDANS [5-(2-iodoacetylaminoethylamino)-1-napthalenesulphonic acid]. Fluorescence quenching studies using acrylamide, and fluorescence lifetime and wavelength emission maxima analyses were conducted in the presence and absence of eEF2. Large changes in the microenvironment of the AEDANS [5-(2-aminoethylamino)-1-naphthalenesulphonic acid] probe after eEF2 binding were not observed as dictated by both fluorescence lifetime and wavelength emission maxima values. This supported the proposed minimal contact model, which suggests that only small, discrete contacts occur between these proteins. As dictated by the bimolecular quenching constant (k(q)) for acrylamide, binding of eEF2 with toxin caused the greatest change in acrylamide accessibility (>50%) when the fluorescence label was near the active site or was located within a known catalytic loop. All mutant proteins showed a decrease in accessibility to acrylamide once eEF2 bound, although the relative change varied for each labelled protein. From these data, a low-resolution model of the toxin-eEF2 complex was constructed based on the minimal contact model with the intention of enhancing our knowledge on the mode of inactivation of the ribosome translocase by the Pseudomonas toxin.
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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".