A comparative study of small molecules targeting eIF4A
Bibliographic record
Abstract
The PI3K/Akt/mTOR kinase pathway is extensively deregulated in human cancers. One critical node under regulation of this signaling axis is eukaryotic initiation factor (eIF) 4F, a complex involved in the control of translation initiation rates. eIF4F-dependent addictions arise during tumor initiation and maintenance due to increased eIF4F activity-generally in response to elevated PI3K/Akt/mTOR signaling flux. There is thus much interest in exploring eIF4F as a small molecule target for the development of new anticancer drugs. The DEAD-box RNA helicase, eIF4A, is an essential subunit of eIF4F, and several potent small molecules (rocaglates, hippuristanol, pateamine A) affecting its activity have been identified and shown to demonstrate anticancer activity in vitro and in vivo in preclinical models. Recently, a number of new small molecules have been reported as having the capacity to target and inhibit eIF4A. Here, we undertook a comparative analysis of their biological activity and specificity relative to the eIF4A inhibitor, hippuristanol.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".