Volumetric Characterization of Interactions of Glycine Betaine with Protein Groups
Bibliographic record
Abstract
We report the partial molar volumes and adiabatic compressibilities of N -acetyl amino acid amides and oligoglycines at glycine betaine (GB) concentrations ranging from 0 to 4 M. We use these results to evaluate the volumetric contributions of amino acid side chains and the glycyl unit (−CH 2 CONH−) as a function of GB concentration. We analyze the resulting GB dependences within the framework of a statistical thermodynamic model and evaluate the equilibrium constant for the reaction in which a GB molecule binds each of the functionalities under study replacing four water molecules. We calculate the free energy of the transfer of functional groups from water to concentrated GB solutions, Δ G tr, as the sum of a change in the free energy of cavity formation, ΔΔ G C, and the differential free energy of solute–solvent interactions, ΔΔ G I, in a concentrated GB solution and water. Our results suggest that the transfer free energy, Δ G tr, results from a fine balance between the large ΔΔ G C and ΔΔ G I contributions. The range of the magnitudes and the shape of the GB dependence of Δ G tr depend on the identity of a specific solute group. The interplay between ΔΔ G C and ΔΔ G I results in pronounced maxima in the GB dependences of Δ G tr for the Val, Leu, Ile, Trp, Tyr, and Gln side chains as well as the glycyl unit. This observation is in qualitative agreement with the experimental maxima in the T M -versus-GB concentration plots reported for ribonuclease A and lysozyme.
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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".