Synthesis of 6,8,9 poly-substituted purine analogue libraries as pro-apoptotic inducers of human leukemic lymphocytes and DAPK-1 inhibitors
Bibliographic record
Abstract
A 18-member library of 6,8,9-poly-substituted purines was prepared from pyrimidines, primary alcohols, and N,N-dimethylamides under basic conditions via a novel one-pot synthetic pathway controlled by amide sizes and the novel analogues were tested against two leukemia cell lines: Jurkat (acute T cell leukemia) and K562 (chronic erythroleukemia) cells. Compounds having a benzoxy group at C6 position of the aromatic ring exhibited antiproliferative activity in Jurkat cells whereas all compounds induced a lower effect on K562 cells. Analysis of cell cycle, Annexin-V staining, and cleavage of initiator caspases assays showed that the active purine analogues induce cell death by apoptosis. Based on these results, a new purine derivative was synthesized, 6-benzyloxy-9-tert-butyl-8-phenyl-9H-purine (6d), which displayed the highest activity of the series against Jurkat cell lines. Finally, (33)P-radiolabeled kinase assays using 96 recombinant human kinases known to be involved in apoptotic events were performed. Just one of the kinases tested, DAPK-1, was inhibited 50% or more by the phenotypic hits at 10 μM, suggesting that the inhibition of this target could be responsible for the induction of cell death by apoptosis. In agreement with the phenotypic results, the most active antiproliferative agent, 6d, displayed also the lowest IC50 value against recombinant DAPK1 (2.5 μM), further supporting the potential role of this protein on the observed functional response. DAPK-1 inhibition led by 6d together with its pro-apoptotic properties against the Jurkat line makes it an interesting candidate to further investigate the role of DAPK1 kinase in triggering apoptosis in cancer cells, a role which is attracting recent interest.
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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".