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Record W2104002701 · doi:10.1073/pnas.1306939110

Human α- <scp>l</scp> -iduronidase uses its own <i>N</i> -glycan as a substrate-binding and catalytic module

2013· article· en· W2104002701 on OpenAlexfundno aff
Nobuo Maita, Takahiro Tsukimura, Takako Taniguchi, Seiji Saito, Kazuki Ohno, Hisaaki Taniguchi, Hitoshi Sakuraba

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2013
Typearticle
Languageen
FieldMedicine
TopicLysosomal Storage Disorders Research
Canadian institutionsnot available
FundersInstitute of GeneticsJapan Society for the Promotion of ScienceNational Institute of Biomedical InnovationUniversity of Tokushima
KeywordsGlycanSubstrate (aquarium)Substrate specificityChemistryBiochemistryBiologyGlycoproteinEnzyme

Abstract

fetched live from OpenAlex

N-glycosylation is a major posttranslational modification that endows proteins with various functions. It is established that N-glycans are essential for the correct folding and stability of some enzymes; however, the actual effects of N-glycans on their activities are poorly understood. Here, we show that human α-l-iduronidase (hIDUA), of which a dysfunction causes accumulation of dermatan/heparan sulfate leading to mucopolysaccharidosis type I, uses its own N-glycan as a substrate binding and catalytic module. Structural analysis revealed that the mannose residue of the N-glycan attached to N372 constituted a part of the substrate-binding pocket and interacted directly with a substrate. A deglycosylation study showed that enzyme activity was highly correlated with the N-glycan attached to N372. The kinetics of native and deglycosylated hIDUA suggested that the N-glycan is also involved in catalytic processes. Our study demonstrates a previously unrecognized function of N-glycans.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.051
GPT teacher head0.329
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations45
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicLysosomal Storage Disorders ResearchFrench-language works237,207