Biological effect and molecular docking of anticancer palladium and platinum complexes with morpholine dithiocarbamate on human serum albumin as a blood carrier protein
Bibliographic record
Abstract
with human serum albumin under physiological conditions by using fluorescence, absorption, and circular dichroism spectroscopic techniques. Spectroscopic analysis of the emission quenching at different temperatures demonstrated that the quenching mechanism was static quenching. From the circular dichroism results, thermal stability study, it was found that the interaction of the complexes with human serum albumin caused a conformational change of the protein reversibly. These 2 anticancer Pd and Pt complexes were activated against chronic myelogenous leukemia cell line K562, so that 50% cytotoxic concentration values of 16 and 26 μM for Pd and Pt complexes, respectively, were observed, which were much lower than that of cisplatin (154 μM). Biological activities of both Pd and Pt complexes were also assayed against selective microorganisms by the disc diffusion method. These results showed that the Pd(II) complex is antifungal agent but Pt(II) complex has antibacterial activity. Also, the interaction of both metal derivative complexes was studied by molecular docking. Complementary molecular docking results may be useful to determine the binding mechanism of human serum albumin in pharmaceutical and biophysical studies providing new insight in the novel pharmacology.
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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) | 0.001 | 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 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".