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Record W2336713818 · doi:10.1021/acs.inorgchem.5b02493

Electrophilic Activation of Oxidized Sulfur Ligands and Implications for the Biological Activity of Ruthenium(II) Arene Anticancer Complexes

2015· article· en· W2336713818 on OpenAlexafffund
Thamayanthy Sriskandakumar, Shirin Behyan, Abraha Habtemariam, Peter J. Sadler, Pierre Kennepohl

Bibliographic record

VenueInorganic Chemistry · 2015
Typearticle
Languageen
FieldMedicine
TopicMetal complexes synthesis and properties
Canadian institutionsUniversity of British Columbia
FundersEngineering and Physical Sciences Research CouncilNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsChemistryElectrophileRutheniumLigand (biochemistry)SolvationMedicinal chemistrySulfurStereochemistryPhotochemistryAdductOxidative additionMoleculeCatalysisOrganic chemistry

Abstract

fetched live from OpenAlex

Surprisingly, the anticancer activity of half-sandwich Ru arene complexes [(η(6)-arene)Ru(en)Cl](+) appears to be promoted and not inhibited by binding to the intracellular thiol glutathione. Labilization of the Ru-S bond allowing DNA binding appeared to be initiated by oxygenation of the thiolate ligand, although oxidation by itself did not seem to weaken the Ru-S bond. In this study, we have investigated the solvation and acidic perturbations of mono (sulfenato) and bis (sulfinato) oxidized species of [(η(6)-arene)Ru(en) (SR)](+) complex in the presence of Brønsted and Lewis acids. Sulfur K-edge X-ray absorption spectroscopy together with density functional theory calculations show that solvation and acidic perturbation of sulfenato species produce a significant decrease in the S3p character of the Ru-S bond (Ru4dσ* ← S1s charge donation). Also there is a drastic fall in the overall ligand charge donation to the metal center in both sulfenato and sulfinato species. Our investigation clearly shows that mono oxidized sulfenato species are most susceptible to ligand exchange, hence providing a possible pathway for in vivo activation and biological activity.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.236

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.088
GPT teacher head0.300
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2015
Admission routes2
Has abstractyes

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