Aminoglycoside interactions and impacts on the eukaryotic ribosome
Bibliographic record
Abstract
Aminoglycosides are chemically diverse, broad-spectrum antibiotics that target functional centers within the bacterial ribosome to impact all four principle stages (initiation, elongation, termination, and recycling) of the translation mechanism. The propensity of aminoglycosides to induce miscoding errors that suppress the termination of protein synthesis supports their potential as therapeutic interventions in human diseases associated with premature termination codons (PTCs). However, the sites of interaction of aminoglycosides with the eukaryotic ribosome and their modes of action in eukaryotic translation remain largely unexplored. Here, we use the combination of X-ray crystallography and single-molecule FRET analysis to reveal the interactions of distinct classes of aminoglycosides with the 80S eukaryotic ribosome. Crystal structures of the 80S ribosome in complex with paromomycin, geneticin (G418), gentamicin, and TC007, solved at 3.3- to 3.7-Å resolution, reveal multiple aminoglycoside-binding sites within the large and small subunits, wherein the 6'-hydroxyl substituent in ring I serves as a key determinant of binding to the canonical eukaryotic ribosomal decoding center. Multivalent binding interactions with the human ribosome are also evidenced through their capacity to affect large-scale conformational dynamics within the pretranslocation complex that contribute to multiple aspects of the translation mechanism. The distinct impacts of the aminoglycosides examined suggest that their chemical composition and distinct modes of interaction with the ribosome influence PTC read-through efficiency. These findings provide structural and functional insights into aminoglycoside-induced impacts on the eukaryotic ribosome and implicate pleiotropic mechanisms of action beyond decoding.
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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) | 0.001 | 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".