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Record W4408450720 · doi:10.3390/v17030420

Bunyaviral Cap-Snatching Endonuclease Activity and Inhibition with Baloxavir-like Inhibitors in the Context of Full-Length L Proteins

2025· article· en· W4408450720 on OpenAlexaff
Arlo J. Loutan, Gabrielle Connolly, R Smiley, Arnab K. Chatterjee, Matthias Götte

Bibliographic record

VenueViruses · 2025
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Vectors
Canadian institutionsUniversity of Alberta
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of Health
KeywordsEndonucleaseExonucleasePolymeraseBiologyRNAVirologyRNA polymeraseMolecular biologyVirusDNAGeneticsGene

Abstract

fetched live from OpenAlex

order includes a range of zoonotic viruses, which can cause severe disease in humans. The viral replication machinery is a logical target for the development of direct-acting antivirals. Inhibition of the cap-snatching endonuclease activity of related influenza viruses provides a proof of concept. Using the influenza B virus (IBV) RNA-dependent RNA polymerase complex as a benchmark, we conducted a comparative analysis of endonuclease activities of recombinant full-length bunyaviral L proteins using gel-based assays. The IBV complex demonstrates specific endonucleolytic cleavage and a clear preference for capped substrates. In contrast, severe fever with thrombocytopenia syndrome, Sin Nombre, and Hantaan virus L proteins readily cleave capped and uncapped RNAs to a broader spectrum of RNA fragments. Active site mutants further help to control for the potential of contaminating nucleases, exonuclease activity, and RNA hydrolysis. The influenza cap-snatching inhibitor baloxavir and derivatives have been used to validate this approach. In conclusion, the results of this study demonstrate the importance of assays with single nucleotide resolution and the use of full-length L proteins as a valuable experimental tool to identify selective endonuclease inhibitors.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score0.542

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 communication0.0000.000
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 head0.016
GPT teacher head0.276
Teacher spread0.260 · 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.

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

Citations3
Published2025
Admission routes1
Has abstractyes

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