Small molecule inhibitors of transcriptional Cyclin Dependent Kinases impose HIV-1 latency, presenting “block and lock” treatment strategies
Bibliographic record
Abstract
Abstract Antiretroviral therapy is not a cure for HIV-1 as viral rebound ensues immediately following discontinuation. The block and lock therapeutic strategy seeks to enforce proviral latency and durably suppress viremic reemergence in the absence of antiretroviral therapy. Transcriptional Cyclin Dependent Kinase activity regulates LTR transcription, however, the effect and therapeutic potential of inhibiting these kinases for enforcing HIV-1 latency remains unrecognized. Using newly developed small molecule inhibitors that are highly selective for either CDK7 (YKL-5-124), CDK9 (LDC000067), or CDK8/19 (Senexin A), we found that targeting any one of these kinases prevented HIV-1 expression at concentrations that showed no toxicity. Furthermore, although CDK7 inhibition induced cell cycle arrest, inhibition of CDK9 and/or CDK8/19 did not. Of particular interest, proviral latency as induced by CDK8/19 inhibition was maintained following drug removal while CDK9 inhibitor induced latency rebounded within 24 hrs of discontinuation. Our results indicate that the Mediator complex kinases, CDK8/CDK19, are attractive block and lock targets while sole disruption of P-TEFb is unlikely to be efficacious.
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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) | 0.003 | 0.001 |
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".