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Record W3012338980 · doi:10.1021/acs.joc.0c00220

Bringing a Molecular Plus One: Synergistic Binding Creates Guest-Mediated Three-Component Complexes

2020· article· en· W3012338980 on OpenAlexafffund
S. Maryamdokht Taimoory, Kwaku Twum, Mohadeseh Dashti, Fangfang Pan, Manu Lahtinen, Kari Rissanen, Rakesh Puttreddy, John F. Trant, Ngong Kodiah Beyeh

Bibliographic record

VenueThe Journal of Organic Chemistry · 2020
Typearticle
Languageen
FieldChemistry
TopicCrystallography and molecular interactions
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaJyväskylän YliopistoAcademy of FinlandCompute Canada
KeywordsChemistryCooperativityHydrogen bondNon-covalent interactionsTernary operationCooperative bindingPyridineStoichiometryComponent (thermodynamics)Carboxylic acidMoleculeTernary complexStereochemistryComputational chemistryBinding siteOrganic chemistryThermodynamicsBiochemistry

Abstract

fetched live from OpenAlex

Cethyl-2-methylresorcinarene (A), pyridine (B), and a set of 10 carboxylic acids (Cn) associate to form A·B·Cn ternary assemblies with 1:1:1 stoichiometry, representing a useful class of ternary systems where the guest mediates complex formation between the host and a third component. Although individually weak in solution, the combined strength of the multiple noncovalent interactions organizes the complexes even in a highly hydrogen-bond competing methanol solution, as explored by both experimental and computational methods. The interactions between A·B and Cn are dependent on the pKa values of carboxylic acids. The weak interactions between A and C further reinforce the interactions between A and B, demonstrating positive cooperativity. Our results reveal that the two-component system such as that formed by A and B can form the basis for the development of specific sensors for the molecular recognition of carboxylic acids.

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 categoriesInsufficient payload (model declined to judge)
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 score0.007
Threshold uncertainty score0.999

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 science0.0010.000
Research integrity0.0000.001
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 head0.223
Teacher spread0.207 · 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.

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

Citations13
Published2020
Admission routes2
Has abstractyes

Explore more

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