Recognition of Lewis X by Anti-Lex Monoclonal Antibody 1G5F6
Bibliographic record
Abstract
Abstract mAbs directed toward the Lewis X (Lex) determinant have been shown to display different specificities, depending on the presentation of Lex to the immune system. Of interest is the murine anti-Lex mAb 1G5F6, generated against the O chain polysaccharide of Helicobacter pylori that contains polymeric Lex structures. The mAb was found to have a higher affinity for polymeric Lex over monomeric Lex. In this study, we explore the recognition of monomeric Lex by 1G5F6 using a panel of Lex analogues in which N-acetyl-d-glucosamine, l-fucose, or d-galactose (d-Gal) are replaced with d-glucose and/or l-rhamnose. Our studies show that all analogues were weaker inhibitors than the Lex Ag, indicating that all three residues are essential in the recognition of Lex by mAb 1G5F6. We explored the involvement of 4″-OH of d-Gal in the binding with 1G5F6 using a panel of 4″-modified Lex analogues. Although the 4″-OH is only involved in a weak polar interaction, we conclude that the d-Gal residue in Lex is primarily involved in aromatic stacking interactions with the Ab binding site. We compared these results to our work with mAb SH1. Although stacking interactions between d-Gal and an aromatic residue was also suggested for SH1, an H-bond involving the 4″-OH was identified that is not found in the binding of 1G5F6 to Lex. Thus, anti-Lex mAbs SH1 and 1G5F6 bind to Lex in different manners, even though the hydrophobic patch displayed by the β-galactoside in Lex is essential in both cases for their binding to Lex.
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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) | 0.002 | 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".