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Record W4307460328 · doi:10.1016/j.xpro.2022.101853

Characterization of multiple interactions between the envelope E protein of SARS-CoV-2 and human BRD4

2022· article· en· W4307460328 on OpenAlexafffund
Mohamad Zandian, Suk Min Jang, Catherine Lachance, Arpan Acharya, Siddappa N. Byrareddy, Jacques Côté, Tatiana G. Kutateladze

Bibliographic record

VenueSTAR Protocols · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Degradation and Inhibitors
Canadian institutionsUniversité Laval
FundersNational Institute of Allergy and Infectious DiseasesNational Institute of General Medical SciencesNational Institute on Drug AbuseNational Heart, Lung, and Blood InstituteCanadian Institutes of Health ResearchNational Institute on AgingNational Cancer InstituteNational Institutes of Health
KeywordsBromodomainBRD4Protein–protein interactionComputational biologyNuclear magnetic resonance spectroscopyAcetylationCell biologyChemistryBiologyVirologyBiophysicsGeneticsStereochemistryGene

Abstract

fetched live from OpenAlex

The SARS-CoV-2 envelope (E) protein hijacks human BRD4 (bromodomain and extra-terminal domain protein 4). Here, we describe a protocol to characterize the interaction of the acetylated E protein with BRD4 in vivo. We detail steps to use NMR spectroscopy to map the binding interface and include steps to monitor the effect of BRD4 inhibitors in SARS-CoV-2-infected human lung bronchial epithelial cells. This approach could be applied to study interactions involving other viral and human proteins. For complete details on the use and execution of this protocol, please refer to Vann et al. (2022).1

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
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 head0.038
GPT teacher head0.322
Teacher spread0.284 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2022
Admission routes2
Has abstractyes

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