Design of novel 4-maleimidylphenyl-hydrazide molecules displaying anti-inflammatory properties: Refining the chemical structure
Bibliographic record
Abstract
The discovery of new drugs possessing multiple biological properties in a single molecular entity is a subject of considerable scrutiny by the scientific community. This strategy can lead to better drug candidates for the treatment of many diseases, including cancer. In our quest for a more efficient bladder cancer treatment, we recently identified a compound readily accessible from para-aminobenzoic acid that showed anti-inflammatory, anti-metastatic as well as anticancer activities. This unique compound called DAB-1 can reduce the size of a tumor in an animal model by 90% within 25 days without apparent side effects. Its structure was modified to provide the molecule 2, a second-generation molecule named DAB-2-28, with enhanced in vitro and in vivo biological properties compared to DAB-1. The prospect of lead optimization is significant. This manuscript describes the synthesis of 2 as well as several higher analogs and reports on their anti-inflammatory activity in addition to their in vitro biological potential against bladder cancer. Amongst the results, it was discovered that the substitution pattern on the hydrazide core significantly affects the anti-inflammatory potential of the molecules. In fact, all the mono-acylated hydrazide derivatives 1, 5, 7, 9 were highly effective inhibiting the production of NO measured by the Griess reagents. By using the MTT assay, the same products displayed slightly lower toxicity (average 90% cell viability) on murine bladder cancer MB49-I cells in comparison to the reference DAB-1 molecule (85%). The best mono-acylated derivative 1 showed about 83% NO production inhibition level in relation to the relative number of viable/proliferating cells, the results are disclosed herein.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".