Synthesis of Purine and 7‐Deazapurine Nucleoside Analogues of 6‐<i>N</i>‐(4‐Nitrobenzyl)adenosine; Inhibition of Nucleoside Transport and Proliferation of Cancer Cells
Bibliographic record
Abstract
Human equilibrative nucleoside transporter 1 (hENT1) is a prototypical nucleoside transporter protein ubiquitously expressed on the cell surface of almost all human tissue. Given the role of hENT1 in the transport of nucleoside drugs, an important class of therapeutics in the treatment of various cancers and viral infections, efforts have been made to better understand the mechanisms by which hENT1 modulates nucleoside transport. To that end, we report here the design and synthesis of novel tool compounds for the further study of hENT1. The 7-deazapurine nucleoside antibiotic tubercidin was converted into its 4-N-benzyl and 4-N-(4-nitrobenzyl) derivatives by alkylation at N3 followed by a Dimroth rearrangement to the 4-N-isomer or by fluoro-diazotization followed by SN Ar displacement of the 4-fluoro group by a benzylamine. The 4-N-(4-nitrobenzyl) derivatives of sangivamycin and toyocamycin antibiotics were prepared by the alkylation approach. Cross-membrane transport of labeled uridine by hENT1 was inhibited to a weaker extent by the 4-nitrobenzylated tubercidin and sangivamycin analogues than was observed with 6-N-(4-nitrobenzyl)adenosine. Type-specific inhibition of cancer cell proliferation was observed at micromolar concentrations with the 4-N-(4-nitrobenzyl) derivatives of sangivamycin and toyocamycin, and also with 4-N-benzyltubercidin. Treatment of 2',3',5'-O-acetyladenosine with aryl isocyanates gave the 6-ureido derivatives but none of them exhibited inhibitory activity against cancer cell proliferation or hENT1.
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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) | 0.000 | 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) | 0.002 | 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".