Prediction of a novel RNA binding domain in crocodilepox Zimbabwe Gene 157
Bibliographic record
Abstract
BACKGROUND: Although the crocodilepox virus (CRV) is currently unclassified, phylogenetic analyses suggest that its closest known relatives are molluscum contagiosum virus (MCV) and the avipox viruses. The CRV genome is approximately 190 kb and contains a large number of unique genes in addition to the set of conserved Chordopoxvirus genes found in all such viruses. Upon sequencing the viral genome, others noted that this virus was also unusual because of the lack of a series of common immuno-suppressive genes. However, the genome contains multiple genes of unknown function that are likely to function in reducing the anti-viral response of the host. RESULTS: By using sensitive database searches for similarity, we observed that gene 157 of CRV-strain Zimbabwe (CRV-ZWE) encodes a protein with a domain that is predicted to bind dsRNA. Domain characterization supported this prediction, therefore, we tested the ability of the Robetta protein structure prediction server to model the amino acid sequence of this protein on a well-characterized RNA binding domain. The model generated by Robetta suggests that CRV-ZWE-157 does indeed contain an RNA binding domain; the model could be overlaid on the template protein structure with high confidence. CONCLUSION: We hypothesize that CRV-ZWE-157 encodes a novel poxvirus RNA binding protein and suggest that as a non-core gene it may play a role in host-range determination or function to dampen host anti-viral responses. Potential targets for this CRV protein include the host interferon response and miRNA pathways.
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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 | 0.001 |
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".