Insight into the Catalytic Mechanism of Pseudomonas aeruginosa Exotoxin A
Bibliographic record
Abstract
The molecular nature of the protein-protein interactions between the catalytic domain from Pseudomonas aeruginosa exotoxin A (PE24H) and its protein substrate, eukaryotic elongation factor-2 (eEF-2) were probed using a fluorescence resonance energy transfer method. Single cysteine mutant proteins of PE24H were prepared and site-specifically labeled with the donor fluorophore IAEDANS (5-(2-iodoacetylaminoethylamino)-1-napthalenesulfonic acid), whereas eEF-2 was labeled with the acceptor fluorophore fluorescein. The association was found to be independent of ionic strength and of the co-substrate, NAD(+) but dependent upon pH. The lack of requirement for NAD(+) to produce the toxin-eEF-2 complex demonstrates that the catalytic process is a random order mechanism, thereby disputing the current model. The previously observed pH dependence for catalytic function can be assigned to the toxin-eEF-2 binding event, as the pH dependence of binding observed in this study showed a strong correlation with enzymatic activity. The ability of the toxin to bind eEF-2 with bound GTP/GDP was assessed using nonhydrolyzable analogues. The results from the substrate binding and catalytic activity experiments indicate that PE24H is able to interact and bind with eEF-2 in all of its guanyl nucleotide-induced conformational states. Thus, the toxin ribosylates eEF-2 regardless of the nucleotide-charged state of eEF-2. These results represent the first detailed characterization of the molecular details and physiological conditions governing this protein-protein interaction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".