Increasing the Bioavailability of Ru<sup>III</sup> Anticancer Complexes through Hydrophobic Albumin Interactions
Bibliographic record
Abstract
A series of pyridine-based derivatives of the clinically successful Ru(III)-based complexes indazolium [trans-RuCl4(1H-indazole)2] (KP1019) and sodium [trans-RuCl4(1H-indazole)2] (KP1339) have been synthesized to probe the effect of hydrophobic interactions with human serum albumin (hsA) on anticancer activity. The solution behavior and protein interactions of the new compounds were characterized by using electron paramagnetic resonance (EPR) and UV/Vis spectroscopy. These studies have revealed that incorporation of hydrophobic substituents at the 4'-position of the axial pyridine ligand stabilizes non-coordinate interactions with hsA. As a consequence, direct coordination to the protein is inhibited, which is expected to increase the bioavailability of the complexes, thus potentially leading to improved anticancer activity. By using this approach, the lifetimes of hydrophobic protein interactions were extended from 2 h for the unsubstituted pyridine complex, to more than 24 h for several derivatives. Free complexes were tested for their anticancer activity against the SW480 human colon carcinoma cell line, exhibiting low cytotoxicity. Pre-treatment with hsA improved the solubility of every compound and led to some changes in activity. Particularly notable was the difference in activity between the methyl- and dibenzyl-functionalized complexes. The former shows reduced activity after incubation with hsA, indicating reduced bioavailability due to protein coordination. The latter exhibits little activity on its own but, following treatment with hsA, exhibited significant cytotoxicity, which is consistent with its ability to form non-coordinate interactions with the protein. Overall, our studies demonstrate that non-coordinate interactions with hsA are a viable target for enhancing the activity of Ru(III)-based complexes in vivo.
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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".