Formation Constants and Coordination Thermodynamics for Binary and Ternary Complexes of Copper(II), <scp>l</scp>-Hydroxyproline, and an Amino Acid Enantiomer
Bibliographic record
Abstract
While a rich database is available at or near room temperature (288.15 to 298.15 K) defining the chemical equilibria of solutions containing the copper(II) ion and an amino acid, data describing the temperature dependence of reaction thermodynamics for these systems remain scarce. In addition, data defining enthalpy, entropy, and heat capacity changes for the formation of mixed amino acid chelate complexes are extremely limited, hindering our understanding of the driving forces for complex formation and stabilization. Here, protonation constants and concentration-based equilibrium constants for Cu(II)−amino acid complexes are reported from 288.15 to 348.15 K for leucine, valine, proline, phenylalanine, and hydroxyproline in aqueous solutions containing 0.1 M KNO 3 . The logarithmic (ln) values of the protonation and binary stepwise concentration equilibrium constants ( K i ) for each amino acid ligand are found to be linearly dependent on the inverse of temperature, indicating negligible change in heat capacity for each of these protonation and complexation reactions. However, ln( K i ) data for ternary complexes formed between Cu(II), l -hydroxyproline, and any one of the other amino acid enantiomers show a nonlinear dependence on inverse temperature, indicating a negative change in heat capacity. Enthalpy and entropy changes for ternary complex formation are therefore temperature-dependent quantities. Our thermodynamic data, when combined with statistical analysis of reaction stoichiometry, reveal that ternary Cu(II)( d ‘ or l ‘)( l -hydroxyproline) complexes are consistently hyperstable as compared to their parent bis-binary complexes at all solution temperatures studied.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".