592. A Comparison of Length on the Potency and Toxicity of Small Interfering and Short Hairpin RNAs Targeting a Highly Conserved Site in HIV-1 RNA Coding for the Gag Polyprotein
Bibliographic record
Abstract
Small interfering RNAs (siRNAs) and their precursors, short hairpin RNAs (shRNAs), are being developed for the treatment of HIV-1 infection as drug and gene therapies, respectively. We have previously identified a target site in HIV-1 RNA coding for the Gag polyprotein that was highly conserved across diverse HIV-1 genomes and particularly accessible to a ribozyme. An shRNA targeting this site was also shown to be a potent inhibitor of HIV-1 production from diverse strains. Several studies have shown that the gene silencing effects of siRNAs and shRNAs are highly dependent on their lengths. While optimal lengths have been proposed, conflicting results suggest that empirical data is required to identify the best format for any particular target site. Using the target site identified in our previous study, we designed siRNAs and shRNAs with different lengths to identify the optimal therapeutic format for further development. Symmetrical and asymmetrical siRNAs, with intended sense-strand lengths of 17 to 29 bases, showed a similar trend in potency against HIV-1 production and the most effective molecules had sense-strand lengths of 27 and 29 bases. In contrast, shRNAs with stem lengths of 20 and 21 base pairs were most effective, with a gradual decrease in potency as the stem length was increased to 29 base pairs. To compare potential immune stimulation and toxicity of the different siRNAs designed, cellular proliferation and phosphorylation of protein kinase R (PKR) were evaluated in HEK293T and MCF7 cells. While phosphorylation of PKR was not detected, minor effects on cell proliferation were observed for some siRNAs at concentrations several fold higher compared to their minimum inhibitory concentrations against HIV-1 production in HEK293T cells. Our results are consistent with reports suggesting that longer siRNAs are more potent compared to their sequence matched canonical formats; however, a standard longer siRNA format, with a 25 base pair sense-strand, was not long enough to observe an increase in potency over canonical formats. Our results also suggest that for certain target sites, there is no correlation between the optimal length of siRNAs and shRNAs. Overall, our results highlight the importance of obtaining empirical data on the optimal si/shRNA format for any particular target site, and provide a set of optimized molecules targeting the Gag coding sequence of HIV-1 RNA for further development.
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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".