Large-scale analysis of conserved rare codon clusters suggests an involvement in co-translational molecular recognition events
Bibliographic record
Abstract
MOTIVATION: An increasing amount of evidence from experimental and computational analysis suggests that rare codon clusters are functionally important for protein activity. Most of the studies on rare codon clusters were performed on a limited number of proteins or protein families. In the present study, we present the Sherlocc program and how it can be used for large scale protein family analysis of evolutionarily conserved rare codon clusters and their relation to protein function and structure. This large-scale analysis was performed using the whole Pfam database covering over 70% of the known protein sequence universe. Our program Sherlocc, detects statistically relevant conserved rare codon clusters and produces a user-friendly HTML output. RESULTS: Statistically significant rare codon clusters were detected in a multitude of Pfam protein families. The most statistically significant rare codon clusters were predominantly identified in N-terminal Pfam families. Many of the longest rare codon clusters are found in membrane-related proteins which are required to interact with other proteins as part of their function, for example in targeting or insertion. We identified some cases where rare codon clusters can play a regulating role in the folding of catalytically important domains. Our results support the existence of a widespread functional role for rare codon clusters across species. Finally, we developed an online filter-based search interface that provides access to Sherlocc results for all Pfam families. AVAILABILITY: The Sherlocc program and search interface are open access and are available at http://bcb.med.usherbrooke.ca
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".