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Record W4309300959 · doi:10.1261/rna.079431.122

The discovery and characterization of two novel structural motifs on the carboxy-terminal domain of kinetoplastid RNA editing ligases

2022· article· en· W4309300959 on OpenAlexafffund
Daniel Moses, Vaibhav Mehta, Reza Salavati

Bibliographic record

VenueRNA · 2022
Typearticle
Languageen
FieldMedicine
TopicTrypanosoma species research and implications
Canadian institutionsMcGill UniversitySte. Anne's Hospital
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyRNA editingCTDDNA ligaseRNARNA ligaseDNACell biologyBiochemistryGeneticsMolecular biologyGene

Abstract

fetched live from OpenAlex

species have a uniquely organized mitochondrial genome, the kinetoplast. Most kinetoplast-transcribed mRNAs are cryptic and encode multiple subunits for the electron transport chain following maturation through a uridine insertion/deletion process called RNA editing. This process is achieved through an enzyme cascade by an RNA editing catalytic complex (RECC), where the final ligation step is catalyzed by the kinetoplastid RNA editing ligases, KREL1 and KREL2. While the amino-terminal domain (NTD) of these proteins is highly conserved with other DNA ligases and mRNA capping enzymes, with five recognizable motifs, the functional role of their diverged carboxy-terminal domain (CTD) has remained elusive. In this manuscript, we assayed recombinant KREL1 in vitro to unveil critical residues from its CTD to be involved in protein-protein interaction and dsRNA ligation activity. Our data show that the α-helix (H)3 of KREL1 CTD interacts with the αH1 of its editosome protein partner KREPA2. Intriguingly, the OB-fold domain and the zinc fingers on KREPA2 do not appear to influence the RNA ligation activity of KREL1. Moreover, a specific KWKE motif on the αH4 of KREL1 CTD is found to be implicated in ligase auto-adenylylation analogous to motif VI in DNA ligases. In summary, we present in the KREL1 CTD a motif VI for auto-adenylylation and a KREPA2 binding motif for RECC integration.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.855
Threshold uncertainty score0.198

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 head0.018
GPT teacher head0.280
Teacher spread0.262 · 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
Published2022
Admission routes2
Has abstractyes

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