Thermodynamic binding studies of cell surface carbohydrate epitopes to galectins-1, -3, and -7: Evidence for differential binding specificities
Bibliographic record
Abstract
Binding of a series of sialylated and non-sialylated cell surface carbohydrates to bovine heart galectin-1, recombinant murine galectin-3, and recombinant human galectin-7 was investigated by isothermal titration microcalori metry (ITC) and hemagglutination inhibition measurements. Galectin-7 shows nearly equal affinities for lactose and Galbeta(14)GlcNAc (LacNAc-II). Galectin-7, however, displays six- and 11-fold weaker affinity for LacNAc-II compared with galectins-1 and -3, respectively. The affinity of galectin-7 for LacNAc-II containing oligosaccharides is also weaker than the other two galectins. ITC measurements show that all three galectins bind to di- and trimeric oligomers of LacNAc-II, which are epitopes found in poly-N-acetyllactosamine chains of glycoprotein receptors, with affinity constants similar to that of LacNAc-II. The binding valencies of the di- and trimeric LacNAc-II oligomers were observed to be one from ITC measurements, indicating formation of 1:1 complexes with all three galectins. Thus, galectins-1, -3, and -7 all possess binding sites that primarily accommodate one LacNAc-II moiety per monomer of protein. Sialylated oligosaccharides show different specificities for the three galectins. While 2,3-sialyl LacNAc-II binds to all three galectins, 2,6-sialyl LacNAc-II fails to bind to any of the galectins; 2,6-sialylated diLacNAc binds well to galectin-3 and galectin-7, but only weakly to galectin-1. Similar results are obtained with 2,6-sialyl lacto-N-neo-tetraose, which has a reducing end lactose moiety. Thus, unlike galectin-1, which predominantly recognizes non-reducing terminal LacNAc-II residues in oligosaccharides, galectins-3 and -7 recognize both non-reducing terminal LacNAc-II residues as well as internal LacNAc-II and lactose residues in sialylated and non-sialylated oligosaccharides.Key words: isothermal titration microcalorimetry, galectins, binding specificities, lectins, carbohydrates.
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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 | 0.001 |
| 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 | 0.001 |
| 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".