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Record W4414558797 · doi:10.17615/j68m-aa83

Structural Chemistry of Helicase Inhibition

2025· article· en· W4414558797 on OpenAlexfundno aff
Matthieu Schapira, Timothy M. Willson, Lakshi Selvaratnam

Bibliographic record

VenueUNC Libraries · 2025
Typearticle
Languageen
FieldChemistry
TopicCarbohydrate Chemistry and Synthesis
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchGenentechOntario GenomicsNational Institutes of HealthOntario Genomics InstituteEuropean Federation of Pharmaceutical Industries and AssociationsMerck KGaAMitacsGenome CanadaMcGill UniversityBayerPfizerBristol-Myers Squibb
KeywordsHelicaseRNA Helicase ADNAStructural biologyEnzymeCocrystalTranslation (biology)ATP hydrolysisRNA

Abstract

fetched live from OpenAlex

Helicases are essential motor enzymes that couple nucleoside-triphosphate hydrolysis with DNA or RNA strand unwinding. Helicases are integral to replication, transcription, splicing, and translation of the genome, play crucial roles in the proliferation of cancer cells and propagation of viral pathogens, and are implicated in neurodegenerative diseases. Despite their therapeutic potential, drug discovery efforts targeting helicases face significant challenges due to their dynamic enzymatic cycles, the transient nature of their conformational states, and the conservation of their active sites. Analysis of cocrystal structures of inhibitor-helicase complexes revealed four distinct mechanisms of inhibition: allosteric, ATP-competitive, RNA-competitive, and interfacial inhibitors. While these static X-ray structures reveal potential binding pockets that may support the development of selective drugs, the application of advanced techniques such as cryo-EM, single-molecule analysis, and computational modeling will be essential for understanding helicase dynamics and designing effective inhibitors.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.140
Threshold uncertainty score0.998

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)0.0030.000

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 head0.010
GPT teacher head0.208
Teacher spread0.198 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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