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Record W3025263087 · doi:10.1021/acschembio.0c00253

CRISPR-Based Screen Links an Inhibitor of Nonsense-Mediated Decay to eIF4A3 Target Engagement

2020· article· en· W3025263087 on OpenAlexafffund
Regina Cencic, Sai Kiran Naineni, Lauren Pugsley, Patrick Sénéchal, Ananya Sahni, Jerry Pelletier

Bibliographic record

VenueACS Chemical Biology · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsMcGill University
FundersCanadian Institutes of Health Research
KeywordsNonsense-mediated decayCRISPRBiologyRNA splicingExonGeneticsStop codonIntronRNACell biologyGene

Abstract

fetched live from OpenAlex

Eukaryotic initiation factor (eIF) 4A3 is a DEAD-box RNA helicase and a core component of the exon-junction complex (EJC). The EJC marks the location of exon:exon junctions following the removal of introns by splicing and plays a critical role in an mRNA surveillance program known as nonsense-mediated decay (NMD). NMD is often triggered by the presence of a premature termination codon (PTC) upstream of the EJC, leading to degradation of the variant mRNA which prevents synthesis of a potentially harmful, truncated polypeptide. One approach by which to treat rare diseases where the underlying cause is a PTC is thus to prevent NMD, while stimulating readthrough of the PTC. Hence, there is much interest in inhibiting NMD, and recently a set of small molecules, 1,4-diacylpiperazine derivatives, targeting eIF4A3 has been developed and shown to harbor such activity. Herein, we undertake a CRISPR/Cas9-based variomics screen to identify eIF4A3 alleles resistant to said compounds. Our results provide genetic evidence linking compound bioactivity to eIF4A3 engagement.

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 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 score0.030
Threshold uncertainty score0.745

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 head0.017
GPT teacher head0.317
Teacher spread0.300 · 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

Citations5
Published2020
Admission routes2
Has abstractyes

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