A Novel p19 Fusion Protein as a Delivery Agent for Short-interfering RNAs
Bibliographic record
Abstract
RNA interference (RNAi) is the biological mechanism that allows targeted gene knockdown through the addition of exogenous short-interfering RNAs (siRNAs) to cells and organisms. RNAi has revolutionized cell biology and holds enormous potential for human therapy. One of the major challenges facing RNAi as a therapy is achieving efficient and nontoxic delivery of siRNAs into the cell cytoplasm, since their highly anionic character precludes their passage across the cell membrane unaided. Herein, we report a novel fusion protein between the tombusviral p19 protein, which binds siRNAs with picomolar affinity, and the “TAT” peptide (RKKRRQRRRR), which is derived from the transactivator of transcription (TAT) protein of the human immunodeficiency virus and acts as a cell-penetrating peptide. We demonstrate that this fusion protein, 2x-p19-TAT, delivers siRNAs into the cytoplasm of human hepatoma cells where they elicit potent and sustained gene knockdown activity without toxic effects. RNA interference (RNAi) is the biological mechanism that allows targeted gene knockdown through the addition of exogenous short-interfering RNAs (siRNAs) to cells and organisms. RNAi has revolutionized cell biology and holds enormous potential for human therapy. One of the major challenges facing RNAi as a therapy is achieving efficient and nontoxic delivery of siRNAs into the cell cytoplasm, since their highly anionic character precludes their passage across the cell membrane unaided. Herein, we report a novel fusion protein between the tombusviral p19 protein, which binds siRNAs with picomolar affinity, and the “TAT” peptide (RKKRRQRRRR), which is derived from the transactivator of transcription (TAT) protein of the human immunodeficiency virus and acts as a cell-penetrating peptide. We demonstrate that this fusion protein, 2x-p19-TAT, delivers siRNAs into the cytoplasm of human hepatoma cells where they elicit potent and sustained gene knockdown activity without toxic effects.
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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".