Does Urea Preferentially Interact with Amide Moieties or Nonpolar Sidechains? A Question Answered Through a Judicious Selection of Model Systems
Bibliographic record
Abstract
The transfer model suggests that urea unfolds proteins mainly by increasing the solubility of the amide backbone, probably through urea-induced increase in hydrogen bonding. Other studies suggest that urea addition increases the magnitude of solvent-solute van der Waals interactions, which increases the solubility of nonpolar sidechains. More recent analyses hypothesize that urea has a similar effect in increasing the solubility of backbone and sidechain groups. In this work, we compare the effects of urea addition on the solvation of amides and alkyl groups. At first, we study the effects of urea addition upon solvent hydrogen bonding acidity and basicity through the perturbation in the fluorescence spectrum of probes 1-AN and 1-DMAN. Our results demonstrate that the solvent's hydrogen bonding properties are minimally affected by urea addition. Subsequently, we show that urea addition does not perturb the intra-molecular hydrogen bonding in salicylic acid significantly. Finally, we investigate how urea preferentially interacts with amide and alkyl groups moieties in water by comparing the effects of urea addition upon the solubility of acetaminophen and 4-tertbutylphenol. We show that urea affects amide and t-butyl solubility (lowers the transfer free energy of both amide (backbone) and alkyl (sidechain) groups) in a similar fashion. In other words, preferential interaction of urea with both moieties contributes to protein denaturation.
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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) | 0.000 | 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".