Specificity of Processing α-Glucosidase I Is Guided by the Substrate Conformation
Bibliographic record
Abstract
BACKGROUND: The enzyme “GluI” is key to the synthesis of critical glycoproteins in the cell. RESULTS: We have determined the structure of GluI, and modeled binding with its unique sugar substrate. CONCLUSION: The specificity of this interaction derives from a unique conformation of the substrate. SIGNIFICANCE: Understanding the mechanism of the enzyme is of basic importance and relevant to potential development of antiviral inhibitors. Processing α-glucosidase I (GluI) is a key member of the eukaryotic N-glycosylation processing pathway, selectively catalyzing the first glycoprotein trimming step in the endoplasmic reticulum. Inhibition of GluI activity impacts the infectivity of enveloped viruses; however, despite interest in this protein from a structural, enzymatic, and therapeutic standpoint, little is known about its structure and enzymatic mechanism in catalysis of the unique glycan substrate Glc3Man9GlcNAc2. The first structural model of eukaryotic GluI is here presented at 2-Å resolution. Two catalytic residues are proposed, mutations of which result in catalytically inactive, properly folded protein. Using Autodocking methods with the known substrate and inhibitors as ligands, including a novel inhibitor characterized in this work, the active site of GluI was mapped. From these results, a model of substrate binding has been formulated, which is most likely conserved in mammalian GluI.
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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 | 0.001 | 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".