Selective Inhibition of HIV‐1 Reverse Transcriptase (HIV‐1 RT) RNase H by Small RNA Hairpins and Dumbbells
Bibliographic record
Abstract
We present here the design of a novel class of RNA inhibitors of the RNase H domain of HIV-1 RT, a ribonuclease activity that is essential for viral replication in vivo. Specifically, we show that small RNA hairpins and dumbbells can selectively inhibit the RNase H activity of HIV-1 RT without affecting other cellular RNases H (e.g., E. coli and human RNase H). These results suggest that the inhibitors do not interact with the nucleic acid binding site of RT RNase H, as this region should be well conserved among the various enzymes. The most potent inhibitors displayed IC50 values in the 3-8 microM range. Remarkably, the DNA polymerase activity, an intrinsic property of HIV RT, was not inhibited by the hairpin and dumbbell aptamers, a property not previously observed for any nucleic acid aptamer directed against RT RNase H. The results described here suggest a noncompetitive binding mechanism, as outlined in the differential inhibitory characteristics of each of the nucleic acid aptamers against the bacterial, human, and viral RNase H homologues.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 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".