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Record W2146274115 · doi:10.3390/v2081734

Core as a Novel Viral Target for Hepatitis C Drugs

2010· article· en· W2146274115 on OpenAlexaff
A. Donny Strosberg, Smitha Kota, Virginia Takahashi, John K. Snyder, Guillaume Mousseau

Bibliographic record

VenueViruses · 2010
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsSmiths Detection (Canada)
FundersNational Institute of Neurological Disorders and Stroke
KeywordsVirologyCore (optical fiber)Hepatitis CViral hepatitisMedicineComputer science

Abstract

fetched live from OpenAlex

Hepatitis C virus (HCV) infects over 130 million people worldwide and is a major cause of liver disease. No vaccine is available. Novel specific drugs for HCV are urgently required, since the standard-of-care treatment of pegylated interferon combined with ribavirin is poorly tolerated and cures less than half of the treated patients. Promising, effective direct-acting drugs currently in the clinic have been described for three of the ten potential HCV target proteins: NS3/NS4A protease, NS5B polymerase and NS5A, a regulatory phosphoprotein. We here present core, the viral capsid protein, as another attractive, non-enzymatic target, against which a new class of anti-HCV drugs can be raised. Core plays a major role in the virion's formation, and interacts with several cellular proteins, some of which are involved in host defense mechanisms against the virus. This most conserved of all HCV proteins requires oligomerization to function as the organizer of viral particle assembly. Using core dimerization as the basis of transfer-of-energy screening assays, peptides and small molecules were identified which not only inhibit core-core interaction, but also block viral production in cell culture. Initial chemical optimization resulted in compounds active in single digit micromolar concentrations. Core inhibitors could be used in combination with other HCV drugs in order to provide novel treatments of Hepatitis C.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.001

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 head0.086
GPT teacher head0.390
Teacher spread0.304 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations36
Published2010
Admission routes1
Has abstractyes

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