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Record W2320746036 · doi:10.1021/jo200031u

Recognition Properties of Carboxylic Acid Bioisosteres: Anion Binding by Tetrazoles, Aryl Sulfonamides, and Acyl Sulfonamides on a Calix[4]arene Scaffold

2011· article· en· W2320746036 on OpenAlexafffund
Thomas Pinter, Subrata Jana, Rebecca Courtemanche, Fraser Hof

Bibliographic record

VenueThe Journal of Organic Chemistry · 2011
Typearticle
Languageen
FieldChemistry
TopicSynthesis of Tetrazole Derivatives
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchDurham UniversityMichael Smith Health Research BC
KeywordsChemistrySulfonamideBioisostereTetrazoleSupramolecular chemistryArylContext (archaeology)CalixareneCombinatorial chemistryCarboxylic acidStereochemistryOrganic chemistryChemical synthesisCrystal structureMoleculeAlkyl

Abstract

fetched live from OpenAlex

Tetrazoles and acyl sulfonamides are functional groups that are common in medicinal chemistry but virtually unexplored as recognition elements in supramolecular chemistry. We report here on the anion binding properties of these highly acidic N-H functional groups. We have prepared two new calixarene-based tetrazole-containing hosts, as well as new acetyl sulfonamide and benzoyl sulfonamide hosts. We also report on analogous hosts bearing the better-known aryl sulfonamide functional group as a point of comparison. We find that these hosts are competent anion binders and that the recognition of anions by these groups is highly dependent on their conformational preferences. We also report in detail on the preferred molecular shape of each acid bioisostere as determined by calculations and structural database surveys, and discuss how these shapes impact binding in the context of the reported hosts.

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 score0.001
Threshold uncertainty score0.003

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)0.0010.000

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 head0.037
GPT teacher head0.203
Teacher spread0.166 · 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

Citations61
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Organic ChemistrySame topicSynthesis of Tetrazole DerivativesFrench-language works237,207