MétaCan
Menu
Back to cohort
Record W1993844923 · doi:10.1371/journal.pone.0012791

Comparative Structural Analysis of Human DEAD-Box RNA Helicases

2010· article· en· W1993844923 on OpenAlexafffund
P. Schutz, T. Karlberg, Susanne van den Berg, R. Collins, L. Lehtiö, Martin Högbom, L. Holmberg-Schiavone, W. Tempel, Hee‐Won Park, M. Hammarstrom, M. Moche, A.G. Thorsell, H. Schüler

Bibliographic record

VenuePLoS ONE · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsStructural Genomics ConsortiumUniversity of Toronto
FundersKnut och Alice Wallenbergs StiftelseKarolinska InstitutetStiftelsen för Strategisk ForskningOntario Genomics InstituteCanadian Institutes of Health ResearchOntario GenomicsGenome CanadaOntario Innovation TrustEuropean Synchrotron Radiation FacilityWellcome TrustGlaxoSmithKline
KeywordsDEAD boxHelicaseRNA Helicase ARNABiologyComputational biologyGeneticsRNA-binding proteineIF4ACell biologyNon-coding RNAGene

Abstract

fetched live from OpenAlex

DEAD-box RNA helicases play various, often critical, roles in all processes where RNAs are involved. Members of this family of proteins are linked to human disease, including cancer and viral infections. DEAD-box proteins contain two conserved domains that both contribute to RNA and ATP binding. Despite recent advances the molecular details of how these enzymes convert chemical energy into RNA remodeling is unknown. We present crystal structures of the isolated DEAD-domains of human DDX2A/eIF4A1, DDX2B/eIF4A2, DDX5, DDX10/DBP4, DDX18/myc-regulated DEAD-box protein, DDX20, DDX47, DDX52/ROK1, and DDX53/CAGE, and of the helicase domains of DDX25 and DDX41. Together with prior knowledge this enables a family-wide comparative structural analysis. We propose a general mechanism for opening of the RNA binding site. This analysis also provides insights into the diversity of DExD/H- proteins, with implications for understanding the functions of individual family members.

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 score0.012
Threshold uncertainty score0.259

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 head0.050
GPT teacher head0.327
Teacher spread0.277 · 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

Citations122
Published2010
Admission routes2
Has abstractyes

Explore more

Same venuePLoS ONESame topicRNA Research and SplicingFrench-language works237,207