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Record W2955835283 · doi:10.1039/c9dt02078k

Ruthenium–arene complexes bearing naphthyl-substituted 1,3-dioxoindan-2-carboxamides ligands for G-quadruplex DNA recognition

2019· article· en· W2955835283 on OpenAlexaff
Laura A. Hager, Stephan Mokesch, Claudia Kieler, Silvia Alonso‐de Castro, Dina Baier, Alexander Roller, Wolfgang Kandioller, Bernhard K. Keppler, Walter Berger, Luca Salassa, Alessio Terenzi

Bibliographic record

VenueDalton Transactions · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Nucleic Acid Chemistry
Canadian institutionsInstitute of Cancer Research
FundersHorizon 2020HORIZON EUROPE Marie Sklodowska-Curie ActionsSeventh Framework ProgrammeHorizon 2020 Framework ProgrammeEuropean Commission
KeywordsRutheniumBearing (navigation)ChemistryDNACombinatorial chemistryG-quadruplexStereochemistryMedicinal chemistryCatalysisOrganic chemistryBiochemistryComputer science

Abstract

fetched live from OpenAlex

Quadruplex nucleic acids - DNA/RNA secondary structures formed in guanine rich sequences - proved to have key roles in the biology of cancers and, as such, in recent years they emerged as promising targets for small molecules. Many reports demonstrated that metal complexes can effectively stabilize quadruplex structures, promoting telomerase inhibition, downregulation of the expression of cancer-related genes and ultimately cancer cell death. Although extensively explored as anticancer agents, studies on the ability of ruthenium arene complexes to interact with quadruplex nucleic acids are surprisingly almost unknown. Herein, we report on the synthesis and characterization of four novel Ru(ii) arene complexes with 1,3-dioxoindan-2-carboxamides ligands bearing pendant naphthyl-groups designed to bind quadruplexes by both stacking and coordinating interactions. We show how improvements on the hydrolytic stability of such complexes, by substituting the chlorido leaving ligand with pyridine, have a dramatic impact on their interaction with quadruplexes and on their cytotoxicity against ovarian cancer cells.

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 score0.015
Threshold uncertainty score0.973

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 head0.016
GPT teacher head0.242
Teacher spread0.226 · 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

Citations28
Published2019
Admission routes1
Has abstractyes

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