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Record W2049479971 · doi:10.1016/s0014-5793(02)02394-3

A rapid fluorometric assay for the proteolytic activity of SKI‐1/S1P based on the surface glycoprotein of the hemorrhagic fever Lassa virus

2002· article· en· W2049479971 on OpenAlexafffund
Ajoy Basak, Michel Chrétien, Nabil G. Seidah

Bibliographic record

VenueFEBS Letters · 2002
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Outbreaks Research
Canadian institutionsMontreal Clinical Research InstituteOttawa HospitalUniversity of Ottawa
FundersMedical Research CouncilOttawa Hospital Research InstituteUniversity of Ottawa
KeywordsLassa virusGlycoproteinChemistryProteaseMolecular biologyVirusVirologyBiochemistryCleavage (geology)EnzymeBiology

Abstract

fetched live from OpenAlex

The subtilase subtilisin kexin isozyme-1 (SKI-1)/site 1 protease (S1P), has been implicated in the processing of Lassa virus glycoprotein C (GP-C) precursor into GP1 and GP2 that are responsible for viral fusion with the host cell membrane. Here, we studied in vitro the kinetics of this cleavage by hSKI-1 using an intramolecularly quenched fluorogenic (IQF) peptide, Q-GPC(251-263) [Abz-(251)Asp-Ile-Tyr-Ile-Ser-Arg-Arg-Leu-Leu/Gly-Thr-Phe-Thr(263)-3-NitroTyr-Ala-CONH(2)], containing the identified site. The measured V(max (app))/K(m (app)) was compared to those for other IQF SKI-substrates. Q-GPC(251-263) is cleaved 10-fold more efficiently than the previously known best SKI-substrate, Q-hproSKI(134-142). This study confirmed the role of SKI-1 in GP-C processing and provides a novel, rapid and efficient enzymatic assay of SKI-1.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.043
GPT teacher head0.271
Teacher spread0.228 · 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

Citations35
Published2002
Admission routes2
Has abstractyes

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Same venueFEBS LettersSame topicViral Infections and Outbreaks ResearchFrench-language works237,207