Small molecule inhibitors of transcriptional cyclin-dependent kinases impose HIV-1 latency, presenting “block and lock” treatment strategies
Bibliographic record
Abstract
Current antiretroviral therapy for HIV-1 infection does not represent a cure for infection as viral rebound inevitably occurs following discontinuation of treatment. The "block and lock" therapeutic strategy is intended to enforce proviral latency and durably suppress viremic reemergence in the absence of other intervention. The transcription-associated cyclin-dependent protein kinases (tCDKs) are required for expression from the 5´ HIV-1 long-terminal repeat, but the therapeutic potential of inhibiting these kinases for enforcing HIV-1 latency has not been characterized. Here, we expanded previous observations to directly compare the effect of highly selective small molecule inhibitors of CDK7 (YKL-5-124), CDK9 (LDC000067), and CDK8/19 (Senexin A), and found each of these prevented HIV-1 provirus expression at concentrations that did not cause cell toxicity. Inhibition of CDK7 caused cell cycle arrest, whereas CDK9 and CDK8/19 inhibitors did not, and could be continuously administered to establish proviral latency. Upon discontinuation of drug administration, HIV immediately rebounded in cells that had been treated with the CDK9 inhibitor, while proviral latency persisted for several days in cells that had been treated with CDK8/19 inhibitors. These results identify the mediator kinases CDK8/CDK19 as potential "block and lock" targets for therapeutic suppression of HIV-1 provirus expression.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".