Minimalist Synthetic Host with Stacked Guanidinium Ions Mimics the Weakened Hydration Shells of Protein–protein Interaction Interfaces
Bibliographic record
Abstract
Protein surfaces are complex solutes, and protein-protein interactions are specifically mediated by surface motifs that modulate solvation shells in poorly understood ways. We report herein a supramolecular host that is designed to mimic one of the most important recognition motifs that drives protein-protein interactions, the stacked arginine side chain. We show that it binds its guests and displays good selectivity in the highly competitive medium of pure, buffered water. We use a combination of experimental studies of binding and molecular dynamics simulations to build a cohesive picture of how this biomimetic host achieves the feat. The presence of the stacking element next to the guanidinium groups causes a decrease in the number of host-water hydrogen bonds, a decrease in the density of water around the host, and a decrease in water-water hydrogen bonds near the host. Experimental data using mixed organic/aqueous solvent systems confirm that this host relies on the hydrophobic effect in a way that the two control hosts do not. Our simulations and analysis provide detailed information on the linkage between (de)hydration and binding events in water in a way that could be applied to many aqueous supramolecular systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| 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 source (direct Gemma or distilled Codex), 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".