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Record W2890040995 · doi:10.1002/chem.201803731

Closing the Loop: Triazolylpyridine Coordination Drives the Self‐Assembly of Metallomacrocycles with Tunable Topologies for Small‐Molecule and Guanine‐Quadruplex Recognition

2018· article· en· W2890040995 on OpenAlexafffund
Caitlin E. Miron, Madelaine R. Colden Leung, Emily Kennedy, Olivier Fleischel, Mona Ashraf Khorasani, Nan Wu, Jean‐Louis Mergny, Anne Petitjean

Bibliographic record

VenueChemistry - A European Journal · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Nucleic Acid Chemistry
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryStereochemistrySelf-assemblyLigand (biochemistry)MoleculeMetal ions in aqueous solutionMetalReceptorOrganic chemistry

Abstract

fetched live from OpenAlex

The 2-(1,2,3-triazol-4-yl)pyridine motif, with its facile "click" synthesis and remarkable coordinative properties, is an attractive chelate for applications in the metal-directed self-assembly of intricate three-dimensional structures. Organic ligands that bear two such chelates bridged by flexible hinge moieties readily undergo self-assembly with metal ions of different coordination geometries to generate a series of topologically diverse metallomacrocycles that can be used for numerous applications. Herein, the synthesis and self-assembly of one such ligand with zinc(II), copper(II), and palladium(II) ions is reported, and the stability of the resulting metallomacrocycles described. An investigation into the use of these metallomacrocycles for the recognition of both small-molecule substrates, such as deoxyguanosine monophosphate, and larger biological assemblies, such as DNA and RNA guanine quadruplexes, is also described.

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 score0.005

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 head0.016
GPT teacher head0.232
Teacher spread0.216 · 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

Citations15
Published2018
Admission routes2
Has abstractyes

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