Specificity of Disulfide Bond Formation during Thermal Aggregation in Solutions of β-Lactoglobulin B and κ-Casein A
Bibliographic record
Abstract
Heat-induced (90 degrees C, 10 min, pH 6.7) intermolecular disulfide bond formation in 1:1 mixtures of beta-lactoglobulin B (beta-Lg) and kappa-casein A (kappa-CN) was studied by enzymatic digestion with trypsin or glu-C, reverse-phase HPLC, and MALDI-TOF-MS. Observed masses were compared to theoretically calculated masses of disulfide-bonded peptide dimers and trimers, and the number of different masses matching peptide combinations involving each bond was used as a measure of confidence of identification. The beta-Lg cysteine residues 121 or 119 were involved in bonds with both cysteines of kappa-CN and all cysteines of beta-Lg. This agrees with the supposed initiatory role of beta-C121 in heat-induced SH/SS interchange. The largest numbers of matches corresponded to bonds linking beta-C119/C121 with kappa-C11 or with beta-C66. Multiple matches were recorded for beta-C119/C121 bonding with beta-C119/C121, with beta-C160, or with kappa-C88. However, beta-C106 was observed only in bonds with beta-C119/C121 and did not appear to bond to kappa-CN, suggesting it remains buried in the core of the protein.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".