Understanding the Recognition of Lewis X by Anti-Le<sup>x</sup> Monoclonal Antibodies
Bibliographic record
Abstract
The recognition of the Le(x) antigen by the anti-Le(x) monoclonal antibody (mAb) SH1 was studied by ELISA using a panel of 4″-modified Le(x) analogues. We confirmed that these analogues maintained the stacked conformation adopted by natural Le(x) antigen using 1D ROESY experiments and measuring intramolecular distances. Our binding studies show that the 4-OH″ of galactose behaves as an H-bond donor to an electronegative amino acid side chain in the SH1 binding site. While removal of this H-bond leads to reduced inhibition, disturbing the hydrophobic α face of the β-galactosyl residue leads to complete loss of binding to SH1. We compared our results to the crystal structure of the Fab fragment of anti-Le(x) mAb 291-2G3-A complexed with Le(x) (PDB entry 1UZ8 ). While no H-bond involving the 4-OH″ was described, hydrophobic interactions between a tryptophan residue and the β-galactoside α face are observed. We conclude that the hydrophobic α face that is uniquely displayed by β-galactosyl residues is essential to the recognition of the Le(x) antigen by anti-Le(x) antibodies.
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 | 0.000 |
| 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".