Studies of the Interaction of the Viral Suppressor of RNA Silencing Protein p19 with Small RNAs Using Fluorescence Polarization
Bibliographic record
Abstract
Tombusviruses use a 19 kDa protein (p19) as a suppressor of the RNA silencing pathway during infection. The p19 protein binds to short-interfering RNA (siRNA) as a dimer and shows a high selectivity for short duplex RNAs over other RNA species. Since p19 can bind to synthetic and RNA silencing generated small RNAs with little sequence dependence and with size selectivity, this protein has utility as a tool for studying RNA silencing pathways in eukaryotes. However, the ability of p19 to serve as a tool for studying RNA silencing pathways may be complicated by the presence of other endogenous small RNAs such as micro-RNAs (miRNAs). To understand the importance of endogenous small RNA components with respect to p19's ability to bind to siRNAs, we examined the interactions of p19 with human miR-122, a 23-nucleotide duplex miRNA containing several mismatched base pairs that is highly abundant in the liver. The binding characteristics were compared with those of an siRNA optimized against the human kinase CSK. The binding studies were performed using fluorescence polarization experiments on duplex oligonucleotides containing Cy3 dye labels at the 5'-end of one of the strands of RNA as well as electrophoretic gel mobility shift assays. Both methods indicate that the synthetic siRNA with no mismatches in base pairing bound with >3-fold selectivity over that of miR-122. Our results suggest that p19 can distinguish between siRNAs and miRNA species, although the difference in binding constants is not so large that interactions with endogenous miRNAs can be totally ignored.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".