The intrinsic cysteine and histidine residues of the anti-Salmonella antibody Se155-4: a model for the introduction of new functions into antibody-binding sites
Bibliographic record
Abstract
New functions can be incorporated into anti-hapten or anti-protein antibodies by mutating selected residues in the binding-site region either to Cys, to allow alkylation with reagents bearing the desired functional groups, or to His, to create metal-binding sites or to make antigen binding pH-sensitive. However, choosing suitable sites for these mutations has been hampered by the lack of antibodies with these features, to serve as models. Remarkably, the anti-carbohydrate antibody Se155-4, specific for the Salmonella group B lipopolysaccharide, already has a Cys and two pairs of His residues close to the antigen-binding pocket in its structure, and shows pH-dependent antigen binding. We therefore investigated modification of its Cys94L in an scFv version of the antibody with the aims of creating a 'reagentless' fluorescent sensor and attaching a metal-binding group that might confer lyase activity. These groups were successfully introduced, as judged by mass spectrometry, and had only slightly reduced antigen binding in enzyme-linked immunosorbent assay. The fluorescent product was sensitive to addition of antigen in a solution format, unlike a modification of a more distant Cys introduced into the VH CDR4 loop. Two other routes to modulate antigen binding were also explored, metal binding by the His pair alongside the antigen-binding pocket and insertions into CDR4 to extend the antigen-contact area. His residues adjacent to the antigen-binding pocket bound copper, causing a 5-fold decrease in antigen binding. In CDR4 of the VH domain, the preferred insert length was four residues, which gave stable antigen-binding products but did not improve overall antigen affinity.
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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".