Elongation factor-Tu can repetitively engage aminoacyl-tRNA within the ribosome during the proofreading stage of tRNA selection
Bibliographic record
Abstract
The substrate for ribosomes actively engaged in protein synthesis is a ternary complex of elongation factor Tu (EF-Tu), aminoacyl-tRNA (aa-tRNA), and GTP. EF-Tu plays a critical role in mRNA decoding by increasing the rate and fidelity of aa-tRNA selection at each mRNA codon. Here, using three-color single-molecule fluorescence resonance energy transfer imaging and molecular dynamics simulations, we examine the timing and role of conformational events that mediate the release of aa-tRNA from EF-Tu and EF-Tu from the ribosome after GTP hydrolysis. Our investigations reveal that conformational changes in EF-Tu coordinate the rate-limiting passage of aa-tRNA through the accommodation corridor en route to the peptidyl transferase center of the large ribosomal subunit. Experiments using distinct inhibitors of the accommodation process further show that aa-tRNA must at least partially transit the accommodation corridor for EF-Tu⋅GDP to release. aa-tRNAs failing to undergo peptide bond formation at the end of accommodation corridor passage after EF-Tu release can be reengaged by EF-Tu⋅GTP from solution, coupled to GTP hydrolysis. These observations suggest that additional rounds of ternary complex formation can occur on the ribosome during proofreading, particularly when peptide bond formation is slow, which may serve to increase both the rate and fidelity of protein synthesis at the expense of GTP hydrolysis.
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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) | 0.000 | 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 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".