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Record W2792447604 · doi:10.1002/chem.201800289

Transition Metal Ions Promote the Bioavailability of Hydrophobic Therapeutics: Cu and Zn Interactions with RNA Polymerase I Inhibitor CX5461

2018· article· en· W2792447604 on OpenAlexafffund
Kathleen E. Prosser, Ada W.Y. Leung, Shane Harrypersad, Andrew R. Lewis, Marcel B. Bally, Charles J. Walsby

Bibliographic record

VenueChemistry - A European Journal · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Nucleic Acid Chemistry
Canadian institutionsBC Cancer AgencySimon Fraser University
FundersBC Cancer AgencyNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchWestern Canada Research GridCompute Canada
KeywordsBioavailabilityChemistryDenticityCytotoxicityPyrazineSolubilityTransition metalAqueous solutionMoleculeDrugMetal ions in aqueous solutionCombinatorial chemistryCoordination complexSolubilizationBiophysicsMetalInorganic chemistryStereochemistryBiochemistryIn vitroOrganic chemistryPharmacologyBiology

Abstract

fetched live from OpenAlex

Abstract Low aqueous solubility is a major barrier to the clinical application of otherwise promising drug candidates. We demonstrate that this issue can be resolved in medicinal molecules containing potential ligating groups, through the addition of labile transition‐metal ions. Incubation of the chemotherapeutic CX5461 with Cu2+ or Zn2+ enables solubilization at neutral pH but does not affect intrinsic cytotoxicity. Spectroscopic and computational studies demonstrate that this arises from coordination to the pyrazine functionality of CX5461 and may involve bidentate coordination at physiological pH.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.009
GPT teacher head0.223
Teacher spread0.214 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2018
Admission routes2
Has abstractyes

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