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Record W2020916721 · doi:10.1074/jbc.m202198200

Role of p50/CDC37 in Hepadnavirus Assembly and Replication

2002· article· en· W2020916721 on OpenAlexaff
Xingtai Wang, Nicholas Grammatikakis, Jianming Hu

Bibliographic record

VenueJournal of Biological Chemistry · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHeat shock proteins research
Canadian institutionsQueen's University
FundersNational Institute of Allergy and Infectious DiseasesAmerican Liver Foundation
KeywordsImmunoprecipitationHsp90P50Reverse transcriptaseBiologyCell biologyIn vitroMolecular biologyViral replicationTranscription factorChaperone (clinical)VirologyChemistryRNACell cultureVirusHeat shock proteinBiochemistryGeneticsGeneMedicine

Abstract

fetched live from OpenAlex

The cellular chaperone Hsp90 has been shown to associate with the reverse transcriptase (RT) of the duck hepatitis B virus and is required for RT functions. However, the molecular basis for the specific interaction between the RT and Hsp90 remains unknown. Comparison of protein compositional properties suggests that the RT is highly related to the protein kinase c-Raf, which interacts with Hsp90 via the cochaperone p50 (CDC37). We tested whether the RT, like c-Raf, is specifically recognized by p50. Immunoprecipitation and pull-down assays showed that p50 or p50deltaC, a p50 mutant defective in Hsp90 binding, could interact specifically with the RT both in vitro and in vivo, indicating that p50 can bind the RT independently of Hsp90. Furthermore, purified p50 and p50deltaC interacted directly with purified RT. The importance of p50-RT interaction for RT functions was underscored by 1) inhibition of protein-primed initiation of reverse transcription by p50deltaC in vitro and 2) stimulation of viral DNA replication and RNA packaging by p50 and their inhibition by p50deltaC in transfected cells. These results suggest that p50 can function as a cellular cofactor for the hepadnavirus RT by mediating the interaction between the RT and Hsp90.

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)0.001
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 score0.009
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.032
GPT teacher head0.302
Teacher spread0.270 · 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

Citations52
Published2002
Admission routes1
Has abstractyes

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