Nonoptimal codon usage influences protein structure in intrinsically disordered regions
Bibliographic record
Abstract
Synonymous codons are not used with equal frequencies in most genomes. Codon usage has been proposed to play a role in regulating translation kinetics and co-translational protein folding. The relationship between codon usage and protein structures and the in vivo role of codon usage in eukaryotic protein folding is not clear. Here, we show that there is a strong codon usage bias in the filamentous fungus Neurospora. Importantly, we found genome-wide correlations between codon choices and predicted protein secondary structures: Nonoptimal codons are preferentially used in intrinsically disordered regions, and more optimal codons are used in structured domains. The functional importance of such correlations in vivo was confirmed by structure-based codon manipulation of codons in the Neurospora circadian clock gene frequency (frq). The codon optimization of the predicted disordered, but not well-structured regions of FRQ impairs clock function and altered FRQ structures. Furthermore, the correlations between codon usage and protein disorder tendency are conserved in other eukaryotes. Together, these results suggest that codon choices and protein structures co-evolve to ensure proper protein folding in eukaryotic organisms.
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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 | 0.001 |
| 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".