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Record W4286434206 · doi:10.1002/anie.202207974

Pharmacological Chaperones for GCase that Switch Conformation with pH Enhance Enzyme Levels in Gaucher Animal Models

2022· article· en· W4286434206 on OpenAlexafffund
Andrés G. Santana, Kyle Robinson, Chelsea Vickers, Matthew C. Deen, Hong‐Ming Chen, Stephen Zhou, Ben Dai, Maria Fuller, A.B. Boraston, David J. Vocadlo, L. Clarke, Stephen G. Withers

Bibliographic record

VenueAngewandte Chemie International Edition · 2022
Typearticle
Languageen
FieldMedicine
TopicLysosomal Storage Disorders Research
Canadian institutionsB.C. Women's Hospital & Health CentreSimon Fraser UniversityUniversity of VictoriaUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Glycomics NetworkCanadian Institutes of Health Research
KeywordsLysosomeEnzymeMutantLysosomal storage disordersIn vivoChemistryCell biologyBiochemistryBiophysicsBiologyGenetics

Abstract

fetched live from OpenAlex

Gaucher disease is a lysosomal storage disorder caused by mutations which destabilize the native folded form of GCase, triggering degradation and ultimately resulting in low enzyme activity. Pharmacological chaperones (PCs) which stabilize mutant GCase have been used to increase lysosomal activity through improving trafficking efficiency. By engineering their inherent basicity, we have synthesized PCs that change conformation between the ER and the lysosomal environment, thus weakening binding to GCase after its successful trafficking to the lysosome. NMR studies confirmed the conformational change while X-ray data reveal bound conformations and binding modes. These results were further corroborated by cell studies showing increases in GCase activity when using the pH-switchable probe at low dosing. Preliminary in vivo assays with humanized mouse models of Gaucher showed enhanced GCase activity levels in relevant tissues, including the brain, further supporting their potential.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.067
GPT teacher head0.343
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2022
Admission routes2
Has abstractyes

Explore more

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