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Record W2022132176 · doi:10.1021/ci400631n

A Refined Model of the HCV NS5A Protein Bound to Daclatasvir Explains Drug-Resistant Mutations and Activity against Divergent Genotypes

2014· article· en· W2022132176 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Chemical Information and Modeling · 2014
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDaclatasvirNS5AHepatitis C virusVirologyGenotypeBiologyComputational biologyHepacivirusGeneVirusGeneticsRibavirin

Abstract

fetched live from OpenAlex

Many direct-acting antiviral agents (DAAs) that selectively block hepatitis C virus (HCV) replication are currently under development. Among these agents is Daclatasvir, a first-in-class inhibitor targeting the NS5A viral protein. Although Daclatasvir is the most potent HCV antiviral molecule yet developed, its binding location and mode of binding remain unknown. The drug exhibits a low barrier to resistance mutations, particularly in genotype 1 viruses, but its efficacy against other genotypes is unclear. Using state-of-the-art modeling techniques combined with the massive computational power of Blue Gene/Q, we identified the atomic interactions of Daclatasvir within NS5A for different HCV genotypes and for several reported resistant mutations. The proposed model is the first to reveal the detailed binding mode of Daclatasvir. It also provides a tool to facilitate design of second generation drugs, which may confer less resistance and/or broader activity against HCV.

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.

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 score0.889
Threshold uncertainty score0.202

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 head0.039
GPT teacher head0.297
Teacher spread0.258 · 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