Programmable Chemoenzymatic Assembly of a Bisected and Core‐Fucosylated <i>N</i> ‐Glycan Library Reveals Glycan‐Binding Protein Specificity and Branch Preference
Bibliographic record
Abstract
Abstract Bisected and core‐fucosylated N ‐glycans represent a distinct class of complex biomolecules that are implicated in diverse biological and pathological processes. The structural complexity and synthetic challenges of these glycans hinder comprehensive understanding of their biological functions due to limited access to well‐defined samples. Despite advances in the complex N ‐glycan synthesis, the efficient preparation of bisected and core‐fucosylated asymmetric N ‐glycans with various branches and terminal epitopes remains an unmet challenge. In this study, we report a streamlined divergent chemoenzymatic approach for the programmable synthesis of an asymmetric bisected and core‐fucosylated N ‐glycan library, featuring bi‐, tri‐, and tetra‐antennary structures with variable‐length oligo‐LacNAc extensions and various terminal epitopes. This methodology relies on protecting‐group‐controlled branch extension, glycosyltransferase intrinsic branch selectivity and glyco‐epitope blocking effects, enabling the precise installment of each branch with unique epitopes. These structurally diverse N ‐glycans are printed as a microarray to comprehensively investigate structure–function relationships, revealing that glycan‐binding protein specificities are mediated by distinct branching patterns, oligo‐LacNAc chain length, and terminal epitope presentation. This work provides valuable insights into glycan‐protein interactions and highlights the potential of our approach for advancing glycoscience and biomedical applications.
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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) | 0.001 | 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".