Alternative Conformations and Motions Adopted by 30S Ribosomal Subunits Visualized by Cryo-Electron Microscopy
Bibliographic record
Abstract
ABSTRACT It is only after recent advances in cryo-electron microscopy that is now possible to describe at high resolution structures of large macromolecules that do not crystalize. Purified 30S subunits interconvert between the “active” and “inactive” conformations. The active conformation was described by crystallography in the early 2000s, but the structure of the inactive form at high resolution remains unsolved. Here we used cryo-electron microscopy to obtain the structure of the inactive conformation of the 30S subunit to 3.6Å resolution and study its motions. In the inactive conformation, three nucleotides at the 3’ end of the 16S rRNA cause the region of helix 44 forming the decoding center to adopt an unlatched conformation and the 3’ end of the 16S rRNA positions similarly to the mRNA during translation. Incubation of inactive 30S subunits at 42 °C reverts these structural changes. The position adopted by helix 44 dictates the most prominent motions of the 30S subunit. We found that extended exposures to low magnesium concentrations induces unfolding of large rRNA structural domains. The air-water interface to which ribosome subuints are exposed during sample preparation also peel off some ribosomal proteins. Overall this study provides new insights about the conformational space explored by the 30S ribosomal subunit when the ribosomal particles are free in solution.
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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".