Multivalent Presentation of Mannose on Hyperbranched Polyglycerol and their Interaction with Concanavalin A Lectin
Bibliographic record
Abstract
We describe the synthesis of multivalent mannose derivatives by using hyperbranched polyglycerols (hPG) as a scaffold with different linker structures. Grafting of protected mannose (Man) units is achieved by using Cu(I) -catalyzed Huisgen click chemistry with either an anomeric azide or propargyl ether onto complementarily functionalized alkyne or azido polymer surfaces. NMR spectroscopy, dynamic light scattering (DLS), IR spectroscopy, size-exclusion chromatography (SEC), and elemental analysis have been used to characterize the hPG-Man compounds. The surface availability and bioactivity of Man-modified polymers were evaluated by using a competitive surface plasmon resonance (SPR)-based binding assay by interactions of the glycopolymers with concanavalin A (Con A), a lectin that binds mannose containing molecules. The results indicated that the novel glycoarchitectures presented in this work are efficient inhibitors of Con A-mannose recognition and resulted in inhibitor concentrations (mean IC(50)) from the micro- to the nanomolar range, whereas the corresponding monovalent mannoside (methyl-Man) requires millimolar concentrations. The results provide an interesting structure-activity relationship for libraries of materials that differ in the linkage of the sugar moiety presented on a biocompatible polyglycerol scaffold.
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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) | 0.000 | 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".