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Record W2148220420 · doi:10.1073/pnas.0900452106

Proteomic screening of variola virus reveals a unique NF-κB inhibitor that is highly conserved among pathogenic orthopoxviruses

2009· article· en· W2148220420 on OpenAlexaff
Mohamed R. Mohamed, Masmudur M. Rahman, Jerry S. Lanchbury, Donna Shattuck, Chris Neff, Max T. Dufford, Katharine Fagan-Garcia, Michèle Barry, Scott K. Smith, Inger K. Damon, Grant McFadden

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2009
Typearticle
Languageen
FieldMedicine
TopicHerpesvirus Infections and Treatments
Canadian institutionsUniversity of Alberta
FundersU.S. Public Health ServiceAcademy of Finland
KeywordsVariola virusBiologyVirologyVacciniaVirusProteomeTropismGeneGenetics

Abstract

fetched live from OpenAlex

Identification of the binary interactions between viral and host proteins has become a valuable tool for investigating viral tropism and pathogenesis. Here, we present the first systematic protein interaction screening of the unique variola virus proteome by using yeast 2-hybrid screening against a variety of human cDNA libraries. Several protein-protein interactions were identified, including an interaction between variola G1R, an ankryin/F-box containing protein, and human nuclear factor kappa-B1 (NF-kappaB1)/p105. This represents the first direct interaction between a pathogen-encoded protein and NF-kappaB1/p105. Orthologs of G1R are present in a variety of pathogenic orthopoxviruses, but not in vaccinia virus, and expression of any one of these viral proteins blocks NF-kappaB signaling in human cells. Thus, proteomic screening of variola virus has the potential to uncover modulators of the human innate antiviral responses.

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 score0.003

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)0.0010.000

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 head0.056
GPT teacher head0.319
Teacher spread0.262 · 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

Citations63
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicHerpesvirus Infections and TreatmentsFrench-language works237,207