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Record W4280505633 · doi:10.1080/14756366.2022.2073444

sp <sup>2</sup> -Iminosugars targeting human lysosomal β-hexosaminidase as pharmacological chaperone candidates for late-onset Tay-Sachs disease

2022· article· en· W4280505633 on OpenAlexaff
Manuel González‐Cuesta, Irene Herrera‐González, M. Isabel García‐Moreno, Roger A. Ashmus, David J. Vocadlo, José M. García Fernández, Eiji Nanba, Katsumi Higaki, Carmen Ortiz Mellet

Bibliographic record

VenueJournal of Enzyme Inhibition and Medicinal Chemistry · 2022
Typearticle
Languageen
FieldMedicine
TopicLysosomal Storage Disorders Research
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsIminosugarTay-Sachs diseaseHEXAHexosaminidaseLysosomal storage diseasePiperidineChemical chaperoneEnzymeSandhoff diseaseChemistryBiochemistryLysosomeMutantStereochemistryMedicineDiseaseInternal medicine

Abstract

fetched live from OpenAlex

The late-onset form of Tay-Sachs disease displays when the activity levels of human β-hexosaminidase A (HexA) fall below 10% of normal, due to mutations that destabilise the native folded form of the enzyme and impair its trafficking to the lysosome. Competitive inhibitors of HexA can rescue disease-causative mutant HexA, bearing potential as pharmacological chaperones, but often also inhibit the enzyme O-glucosaminidase (GlcNAcase; OGA), a serious drawback for translation into the clinic. We have designed sp2-iminosugar glycomimetics related to GalNAc that feature a neutral piperidine-derived thiourea or a basic piperidine-thiazolidine bicyclic core and behave as selective nanomolar competitive inhibitors of human Hex A at pH 7 with a ten-fold lower inhibitory potency at pH 5, a good indication for pharmacological chaperoning. They increased the levels of lysosomal HexA activity in Tay-Sachs patient fibroblasts having the G269S mutation, the highest prevalent in late-onset Tay-Sachs disease.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.159
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.023
GPT teacher head0.313
Teacher spread0.291 · 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

Citations13
Published2022
Admission routes1
Has abstractyes

Explore more

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