The African natural product knipholone anthrone and its analogue anthralin (dithranol) enhance HIV-1 latency reversal
Bibliographic record
Abstract
T cells that harbor latent but replication-competent provirus. The "shock-and-kill" pharmacological ap-proach aims to reactivate provirus expression in the presence of antiretroviral therapy and target virus-expressing cells for elimination. However, no latency reversal agent (LRA) to date effectively clears viral reservoirs in humans, suggesting a need for new LRAs and LRA combinations. Here, we screened 216 compounds from the pan-African Natural Product Library and identified knipholone anthrone (KA) and its basic building block anthralin (dithranol) as novel LRAs that reverse viral latency at low micromolar concentrations in multiple cell lines. Neither agent's activity depends on protein kinase C; nor do they inhibit class I/II histone deacetylases. However, they are differentially modulated by oxidative stress and metal ions and induce distinct patterns of global gene expression from established LRAs. When applied in combination, both KA and anthralin synergize with LRAs representing multiple functional classes. Finally, KA induces both HIV RNA and protein in primary cells from HIV-infected donors. Taken together, we describe two novel LRAs that enhance the activities of multiple "shock-and-kill" agents, which in turn may inform ongoing LRA combination therapy efforts.
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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 | 0.000 |
| 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".