Oxo-aglaiastatin-Mediated Inhibition of Translation Initiation
Bibliographic record
Abstract
Translation is a highly regulated process that is perturbed in human cancers, often through activation of the PI3K/mTOR pathway which impacts directly on the ribosome recruitment phase of translation initiation. While significant research has focused on "drugging" components of the PI3K/mTOR network, efforts have also been directed towards inhibiting eukaryotic initiation factor (eIF) 4F-dependent translation. Small molecule inhibitors of this complex have been identified, characterized, and used to validate the rationale of targeting this step to curtail tumor cell growth and modulate chemotherapy response. One such class of compounds are the rocaglates, secondary metabolites from the plant genus Aglaia, which target the RNA helicase subunit of eIF4F, eIF4A. Here we explore the ability of synthetic derivatives of aglaiastatins and an aglaroxin derivative to target the translation process in vitro and in vivo and find the synthetic derivative oxo-aglaiastatin to possess such activity. Oxo-aglaiastatin inhibited translation in vitro and in vivo and synergized with doxorubicin, ABT-199 (a Bcl-2 antagonist), and dexamethasone when tested on hematological cancer cells. The biological activity of oxo-aglaiastatin was shown to be a consequence of inhibiting eIF4A1 activity.
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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) | 0.001 | 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".