Modular Solid‐Phase Synthetic Approach To Optimize Structural and Electronic Properties of Oligoboronic Acid Receptors and Sensors for the Aqueous Recognition of Oligosaccharides
Bibliographic record
Abstract
This article describes the design and optimization of the first entirely modular, parallel solid-phase synthetic approach for the generation of well-defined polyamine oligoboronic acid receptors and fluorescence sensors for complex oligosaccharides. The synthetic approach allows an effective building of the receptor polyamine backbone, followed by the controlled diversification of the amine benzylic side chains. This approach enabled the testing, in a modular fashion, of the effect of different arylboronic acid units substituted with unencumbering para electron-withdrawing or electron-donating groups. The feasibility of this approach toward automated synthesis was also investigated with the assembly of a sublibrary of receptors by means of the Irori MiniKan technology. Several sublibraries of anthracene-capped sensors containing two or three arylboronic acids were synthesized, and their binding to a series of model disaccharides was examined in neutral aqueous media. The calculation of association constants by fluorescence titrations confirmed that subtle changes in the structures of the interamine spacers in the polyamine backbone can have a significant effect on the stability of the resulting complexes. Most importantly, this study led to the determination of the preferred electronic characteristics for the arylboronate units, and suggests that a new generation of receptors containing very electron-poor arylboronic acids could lead to a significant improvement of binding affinities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".