Synthesis and evaluation of squaramide and thiosquaramide inhibitors of the DNA repair enzyme SNM1A
Bibliographic record
Abstract
SNM1A is a zinc-dependent nuclease involved in the removal of interstrand crosslink lesions from DNA. Inhibition of interstrand crosslink repair enzymes such as SNM1A is a promising strategy for improving the efficacy of crosslinking chemotherapy drugs. Initial studies have demonstrated the feasibility of developing SNM1A inhibitors, but the full potential of this enzyme as a drug target has yet to be explored. Herein, the synthesis of a family of squaramide- and thiosquaramide-bearing nucleoside derivatives and their evaluation as SNM1A inhibitors is reported. A gel electrophoresis assay was used to identify nucleoside derivatives bearing an N-hydroxysquaramide or squaric acid moiety at the 3′-position, and a thymidine derivative bearing a 5′-thiosquaramide, as candidate SNM1A inhibitors. Quantitative IC50 determination showed that a thymidine derivative bearing a 5′-thiosquaramide was the most potent inhibitor, followed by a thymidine derivative bearing a 3′-squaric acid. UV–Vis titrations were carried out to evaluate the binding of the (thio)squaramides to zinc ions, allowing the order of inhibitory potency to be rationalised. The membrane permeability of the active inhibitors was investigated, with several compounds showing promise for future in vivo applications.
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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) | 0.001 | 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) | 0.002 | 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".