Small-molecule inhibitors prevent the genotoxic and protumoural effects induced by colibactin-producing bacteria
Bibliographic record
Abstract
OBJECTIVE: Colorectal cancers (CRCs) are frequently colonised by colibactin toxin-producing Escherichia coli bacteria that induce DNA damage in host cells and exhibit protumoural activities. Our objective was to identify small molecules inhibiting the toxic effects induced by these colibactin-producing bacteria. DESIGN: A structural approach was adopted for the identification of a putative ligand for the ClbP enzyme involved in the synthesis of colibactin. Intestinal epithelial cells and a CRC mouse model were used to assess the activity of the selected compounds in vitro and in vivo. RESULTS: Docking experiments identified two boron-based compounds with computed ligand efficiency values (-0.8 and -0.9 kcal/mol/atom) consistent with data expected for medicinal chemistry leads. The crystalline structure of ClbP in complex with the compounds confirmed that the compounds were binding to the active site of ClbP. The two compounds (2 mM) suppressed the genotoxic activity of colibactin-producing E coli both in vitro and in vivo. The mean degree of suppression of DNA damage for the most efficient compound was 98±2% (95% CI). This compound also prevented cell proliferation and colibactin-producing E coli-induced tumourigenesis in mice. In a CRC murine model colonised by colibactin-producing E coli, the number of tumours decreased by 3.5-fold in animals receiving the compound in drinking water (p<0.01). CONCLUSIONS: These results demonstrate that targeting colibactin production controls the genotoxic and protumoural effects induced by this toxin.
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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".