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Record W2322260047 · doi:10.1021/ml500077j

Discovery and Synthesis of C-Nucleosides as Potential New Anti-HCV Agents

2014· article· en· W2322260047 on OpenAlexaff
Alistair G. Draffan, Barbara Frey, Brett Pool, Carlie T. Gannon, Edward M. Tyndall, Michael J. Lilly, Paula Francom, Richard Hufton, Rosliana Halim, Saba Jahangiri, Silas Bond, Van T. Nguyen, Tyrone P. Jeynes, Veronika Wirth, Angela Luttick, Danielle Tilmanis, Jesse Thomas, Melinda J. Pryor, Kate Porter, Craig J. Morton, Bo Lin, Jianmin Duan, George Kukolj, Bruno Simoneau, Ginette McKercher, Lisette Lagacé, Ma’an Amad, Richard C. Bethell, Simon P. Tucker

Bibliographic record

VenueACS Medicinal Chemistry Letters · 2014
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsBoehringer Ingelheim (Canada)
Fundersnot available
KeywordsGuanosineNucleosideHepatitis C virusNS5BNucleotideSofosbuvirChemistryGlycosidic bondUridineStereochemistryAdenosinePurinePharmacologyBiochemistryVirologyVirusHepacivirusBiologyRibavirinEnzymeGeneRNA

Abstract

fetched live from OpenAlex

Nucleoside analogues have long been recognized as prospects for the discovery of direct acting antivirals (DAAs) to treat hepatitis C virus because they have generally exhibited cross-genotype activity and a high barrier to resistance. C-Nucleosides have the potential for improved metabolism and pharmacokinetic properties over their N-nucleoside counterparts due to the presence of a strong carbon-carbon glycosidic bond and a non-natural heterocyclic base. Three 2'CMe-C-adenosine analogues and two 2'CMe-guanosine analogues were synthesized and evaluated for their anti-HCV efficacy. The nucleotide triphosphates of four of these analogues were found to inhibit the NS5B polymerase, and adenosine analogue 1 was discovered to have excellent pharmacokinetic properties demonstrating the potential of this drug class.

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 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 score0.018
Threshold uncertainty score0.655

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)0.0000.000

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 head0.013
GPT teacher head0.276
Teacher spread0.263 · 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

Citations36
Published2014
Admission routes1
Has abstractyes

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