Synthesis, Structure, and Biologic Activity of Some Copper, Nickel, Cobalt, and Zinc Complexes with 2‐Formylpyridine <i>N</i><sup>4</sup>‐Allylthiosemicarbazone
Bibliographic record
Abstract
A series of zinc(II) ([Zn(H2O)(L)Cl] (1)), copper (II) ([Cu(L)Cl] (2), [Cu(L)Br] (3), [Cu2(L)2(CH3COO)2]·4H2O (4)), nickel(II) ([Ni(HL)2]Cl2·H2O (5)), and cobalt(III) ([Co(L)2]Cl (6)) complexes were obtained with 2‐formylpyridine N4‐allylthiosemicarbazone (HL). In addition another two thiosemicarbazones (3‐formylpyridine N4‐allylthiosemicarbazone (HLa) and 4‐formylpyridine N4‐allylthiosemicarbazone (HLb)) have been obtained. The synthesized thiosemicarbazones have been studied using 1H and 13C NMR spectroscopy, IR spectroscopy, and X‐ray diffraction analysis. The composition and structure of complexes were studied using elemental analysis, IR and UV‐Vis spectroscopies, molar conductivity, and magnetic susceptibility measurements. Single crystal X‐ray diffraction analysis elucidated the structure of thiosemicarbazones HL, HLa, and HLb, as well as complexes 4 and 5. The antiproliferative properties of these compounds toward a series of cancer cell lines (HL‐60, HeLa, BxPC‐3, RD) and a normal cell line (MDCK) have been investigated. The nickel complex shows high selectivity (SI > 1000) toward HL‐60 cell line and is the least toxic. The zinc complex shows the highest selectivity toward RD cell line (SI = 640). The copper complexes (2–4) are the most active molecular inhibitors of proliferation of cancer cells, but exhibit not such a high selectivity and are significantly more toxic. Zinc and copper complexes manifest high antibacterial activity. It was found that calculated at B3LYP level of theory different reactivity descriptors of studied compounds strongly correlate with their biological activity.
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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) | 0.000 | 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 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".