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Record W2398607656 · doi:10.1021/acsinfecdis.5b00083

Profiling Kinase Activity during Hepatitis C Virus Replication Using a Wortmannin Probe

2015· article· en· W2398607656 on OpenAlexafffund
Geneviève F. Desrochers, Allison R. Sherratt, David R. Blais, Neda Nasheri, Zhibin Ning, Daniel Figeys, Natalie K. Goto, John Paul Pezacki

Bibliographic record

VenueACS Infectious Diseases · 2015
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsUniversity of OttawaNational Research Council Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsKinomeWortmanninKinaseCell biologyBiologyViral replicationHepatitis C virusViral life cycleVirologyVirus

Abstract

fetched live from OpenAlex

To complete its life cycle, the hepatitis C virus (HCV) induces changes to numerous aspects of its host cell. As kinases act as regulators of many pathways utilized by HCV, they are likely enzyme targets for virally induced inhibition or activation. Herein, we used activity-based protein profiling (ABPP), which allows for the identification of active enzymes in complex protein samples and the quantification of their activity, to identify kinases that displayed differential activity in HCV-expressing cells. We utilized an ABPP probe, wortmannin-yne, based on the kinase inhibitor wortmannin, which contains a pendant alkyne group for bioconjugation using bioorthogonal chemistry. We observed changes in the activity of kinases involved in the mitogen-activated protein kinase pathway, apoptosis pathways, and cell cycle control. These results establish changes to the active kinome, as reported by wortmannin-yne, in the proteome of human hepatoma cells actively replicating HCV. The observed changes include kinase activity that affect viral entry, replication, assembly, and secretion, implying that HCV is regulating the pathways that it uses for its life cycle through modulation of the active kinome.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score0.884

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.060
GPT teacher head0.358
Teacher spread0.298 · 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 designObservational
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

Citations9
Published2015
Admission routes2
Has abstractyes

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