Determination of glycation sites by tandem mass spectrometry in a synthetic lactose‐bovine serum albumin conjugate, a vaccine model prepared by dialkyl squarate chemistry
Bibliographic record
Abstract
RATIONALE: Neoglycoconjugate vaccines synthesized by the squaric acid spacer method allow single point attachment of the carbohydrate antigen to the protein carrier. However, the localization of the carbohydrate antigen sites of conjugation on the protein carrier has been an elusive task difficult to achieve. METHOD: Covalent attachment of the lactose antigen to the bovine serum albumin (BSA) was prepared by the squaric acid method using a hapten:BSA ratio of 20:1. Different reaction times were used during the conjugation reaction and two different lactose-BSA glycoconjugate vaccines were obtained. The carbohydrate antigen hapten:BSA ratios of these lactose-BSA glycoconjugate vaccines were determined by MALDI-TOF/RTOF-MS and the glycation sites in the neoglycoconjugates were determined using nano-LC/ESI-QqTOF-MS/MS analysis of the trypsin and GluC V8 digests of the conjugates. RESULTS: We have identified a total of 15 glycation sites located on the BSA lysine residues for the neoglycoconjugate vaccine formed with a hapten:BSA ratio of 5.1:1, However, the tryptic and GluC V8 digests of the hapten-BSA glycoconjugate with a hapten:BSA ratio of 19.0:1 allowed identification of 30 glycation sites located on the BSA. These last results seem to indicate that this conjugation results in formation of various glycoforms. CONCLUSIONS: It was observed that the number of identified glycation sites increased when the hapten:BSA ratio of glycoconjugate formation increased, and that the location of the glycation sites appears to be mainly on the outer surface of the BSA carrier molecule which is in line with the assumption that the sterically more accessible lysine residues, namely those located on the outer surface of the BSA, would be conjugated preferentially.
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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) | 0.001 | 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 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".