The T99K variant of glycosylasparaginase shows a new structural mechanism of the genetic disease aspartylglucosaminuria
Bibliographic record
Abstract
Abstract Aspartylglucosaminuria (AGU) is an inherited disease caused by mutations in a lysosomal amidase called aspartylglucosaminidase (AGA) or glycosylasparaginase (GA). This disorder results in an accumulation of glycoasparagines in the lysosomes of virtually all cell types, with severe clinical symptoms affecting the central nervous system, skeletal abnormalities, and connective tissue lesions. GA is synthesized as a single‐chain precursor that requires an intramolecular autoprocessing to form a mature amidase. Previously, we showed that a Canadian AGU mutation disrupts this obligatory intramolecular autoprocessing with the enzyme trapped as an inactive precursor. Here, we report biochemical and structural characterization of a model enzyme corresponding to a new American AGU allele, the T99K variant. Unlike other variants with known 3D structures, this T99K model enzyme still has autoprocessing capacity to generate a mature form. However, its amidase activity to digest glycoasparagines remains low, consistent with its association with AGU. We have determined a 1.5‐Å‐resolution structure of this new AGU model enzyme and built an enzyme–substrate complex to provide a structural basis to analyze the negative effects of the T99K point mutation on KM and kcat of the amidase. It appears that a “molecular clamp” capable of fixing local disorders at the dimer interface might be able to rescue the deficiency of this new AGU variant.
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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 | 0.001 | 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".