Engineering synthetic and recombinant human lysosomal β-glucocerebrosidase for enzyme replacement therapy for Gaucher disease
Bibliographic record
Abstract
Gaucher Disease (GD) is an autosomal recessive, lysosomal storage disease caused by pathogenic variants in the glucocerebrosidase gene, leading to the loss of β-glucocerebrosidase (GCase) enzymatic activity. Enzyme replacement therapy (ERT) with recombinant GCase is the standard of care in GD patients. Our study investigates the combined use of in silico molecular evolution, synthetic biology and gene therapy approaches to develop a new synthetic recombinant enzyme. We engineered four GCases containing missense mutations in the signal peptide (SP) from four selected mammalian species, and compared them with human GCase without missense mutations in the SP. We investigated transcriptional regulation with CMV and hEF1a promoters alongside a GFP control construct in 293-FT human cells. One hEF1a-driven mutant GCase shows a 5.2-fold higher level of transcription than control GCase. In addition, this mutant exhibits up to a sixfold higher activity compared with the mock-control, and the predicted tertiary structure of this mutant GCase aligns with human GCase. We also evaluated conserved and coevolved residues mapped to functionally important positions. Further studies are needed to assess its functionality in a GD animal model. Altogether, our findings provide in vitro evidence of the potential of this engineered enzyme for improved therapeutic effects for GD. Article highlights. Conservation and coevolution analysis of amino acid frequencies in GBA1 homologs of pathogenic variants associated with Gaucher disease, Parkinson’ disease risk or Dementia with Lewy bodies risk.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".