Precise Recognition in Water by an <i>Endo</i>‐Functionalized Cavity: Tuning the Complementarity of Binding Sites
Bibliographic record
Abstract
Precise binding towards structurally similar substrates is a common feature of biomolecular recognition. However, achieving such selectivity-especially in distinguishing subtle differences in substrates-with synthetic hosts can be quite challenging. Herein, we report a novel design strategy involving the combination of different rigid skeletons to adjust the distance between recognition sites within the cavity, which allows for the highly selective recognition of hydrogen-bonding complementary substrates, such as 4-chromanone. X-ray single-crystal structures and density functional theory calculations confirmed that the distance of endo-functionalized groups within the rigid cavity is crucial for achieving high binding selectivity through hydrogen bonding. The thermodynamic data and molecular dynamics simulations revealed a significant influence of the hydrophobic cavity on the binding affinity. The new receptor possesses both high selectivity and high affinity, which provide valuable insights for the design of customized receptors.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".