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Record W4210450744 · doi:10.1101/2022.01.21.477298

The N764K and N856K mutations in SARS-CoV-2 Omicron BA.1 S protein generate potential cleavage sites for SKI-1/S1P protease

2022· preprint· en· W4210450744 on OpenAlexaff
Halim Maaroufi

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsCleaveProteasesTropismCleavage (geology)ProteaseGlycoproteinBiologySyncytiumCell biologyVirologyTissue tropismChemistryMolecular biologyVirusEnzymeBiochemistry

Abstract

fetched live from OpenAlex

Abstract Spike (S) protein is a key protein in coronaviruses life cycle. SARS-CoV-2 Omicron BA.1 variant of concern (VoC) presents an exceptionally high number of 30 substitutions, 6 deletions and 3 insertions in the S protein. Recent works revealed major changes in the SARS-CoV-2 Omicron biological properties compared to earlier variants of concern (VoCs). Here, these major changes could be explained, at least in part, by the mutations N764K and/or N856K in S2 subunit. These mutations were not previously detected in other VoCs. N764K and N856K generate two potential cleavage sites for SKI-1/S1P serine protease, known to cleave viral envelope glycoproteins. The new sites where SKI-1/S1P could cleave S protein might impede the exposition of the internal fusion peptide for membrane fusion and syncytia formation. Based on the human protein atlas, SKI-1/S1P protease is not found in lung tissues (alveolar cells type I/II and endothelial cells), but present in bronchus and nasopharynx. This may explain why Omicron has change of tissue tropism. Viruses have evolved to use several host proteases for cleavage/activation of envelope glycoproteins. Mutations that allow viruses to change of protease may have a strong impact in host range, cell and tissue tropism, and pathogenesis.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.031
GPT teacher head0.298
Teacher spread0.267 · 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 designSimulation or modeling
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

Citations12
Published2022
Admission routes1
Has abstractyes

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