Eukaryotic protein synthesis inhibitors identified by comparison of cytotoxicity profiles
Bibliographic record
Abstract
The National Cancer Institute (NCI) Human Tumor Cell Line Anti-Cancer Drug Screen has evaluated the cytotoxicity profiles of a large number of synthetic compounds, natural products, and plant extracts on 60 different cell lines. The data for each compound/extract can be assessed for similarity of cytotoxicity pattern, relative to a given test compound, using an algorithm called COMPARE. In applying a chemical biology approach to better understand the mechanism of eukaryotic protein synthesis, we used these resources to search for novel inhibitors of translation. The cytotoxicity profiles of 31 known protein synthesis inhibitors were used to identify compounds from the NCI database with similar activity profiles. Using this approach, two natural products, phyllanthoside and nagilactone C, were identified and characterized as novel protein synthesis inhibitors. Both compounds are specific for the eukaryotic translation apparatus, function in vivo and in vitro, and interfere with translation elongation. Our results demonstrate the feasibility of utilizing cytotoxicity profiles to identify new inhibitors of translation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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 | 0.001 |
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".