Negative Cooperativity Associated with Binding of Multivalent Carbohydrates to Lectins. Thermodynamic Analysis of the “Multivalency Effect”
Bibliographic record
Abstract
Our previous study demonstrated that isothermal titration microcalorimetry (ITC) could be used to determine the thermodynamics of binding of a series of synthetic multivalent carbohydrates to the Man/Glc-specific lectins concanavalin A (ConA) and Dioclea grandiflora lectin (DGL) [Dam, T. K., Roy, R., Das, S. K., Oscarson, S. and Brewer, C. F. (2000) J. Biol. Chem. 275, 14223-14230]. The higher affinities of the multivalent carbohydrates for the two lectins were shown to be due to their greater positive entropy of binding contributions relative to monovalent analogues. In the present study, ITC data from our previous report for binding of di-, tri-, and tetravalent carbohydrate analogues possessing terminal 3,6-di-O-(alpha-D-mannopyranosyl)-alpha-D-mannopyranoside residues to ConA and DGL were subjected to Hill plot analysis. Hill plots of the binding of monovalent methyl 3,6-di-O-(alpha-D-mannopyranosyl)-alpha-D-mannopyranoside to ConA and DGL are linear with slopes near 1.0, demonstrating a lack of binding cooperativity and allosteric transitions in the proteins. However, Hill plots for the binding of the di-, tri-, and tetravalent trimannoside analogues to both lectins are curvilinear with decreasing tangent slopes below 1.0, indicating increasing negative cooperativity upon binding of the analogues to the lectins. The curvilinear Hill plots are consistent with decreasing affinity and functional valencies of the multivalent analogues upon sequential binding of lectin molecules to the carbohydrate epitopes of the analogues. The following paper [Dam, T. K., Roy, R., Pagé, D., and Brewer, C. F. (2002) Biochemistry 41, 1359-1363] provides direct evidence of the decreasing affinity constants of multivalent carbohydrates upon sequential binding of lectin molecules.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".