MétaCan
Menu
Back to cohort
Record W2091982417 · doi:10.1021/bi0483054

Secondary-Structure Characterization of Two Proficient Kinase Deoxyribozymes

2005· article· en· W2091982417 on OpenAlexaff
John C. Achenbach, Greg A. Jeffries, Simon A. McManus, Lieven P. Billen, Yingfu Li

Bibliographic record

VenueBiochemistry · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDeoxyribozymeComputational biologyPseudoknotSequence (biology)Base pairNucleotideChemistryDNAProtein secondary structureComputer scienceBiochemistryBiologyBase sequenceGene

Abstract

fetched live from OpenAlex

Dk1 and Dk2 are two catalytically proficient, manganese-dependent, guanine-rich deoxyribozymes previously isolated for DNA phosphorylation. In this study, we carried out a series of experiments that aimed to understand the structural properties of Dk1 and Dk2 and compare the structural similarities or differences of these two distinct deoxyribozymes that carry out similar catalytic functions. First, we performed reselections from two partially randomized DNA libraries on the basis of the original Dk1 and Dk2 sequences to isolate catalytically active sequence variants and identify nucleotides that are invariable, well-conserved, or highly mutagenized. Sequence analysis of these variants assisted by secondary-structure predictions led to the identification of possible Watson-Crick base-pairing regions within each deoxyribozyme. Sequence truncation and base-pair partner exchange experiments were conducted to confirm, or rule out, the existence of the predicted secondary-structure elements. Finally, methylation interference experiments were applied to identify nucleotides that are potentially important for the tertiary structure folding of the deoxyribozymes. Our data suggest that Dk1 and Dk2, despite the differences in their primary sequences and NTP requirements, use an analogous stem-loop element to anchor a structural domain of substantial tertiary interactions to execute their catalytic functions.

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 score0.008
Threshold uncertainty score0.587

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 head0.004
GPT teacher head0.249
Teacher spread0.245 · 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

Citations33
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueBiochemistrySame topicAdvanced biosensing and bioanalysis techniquesFrench-language works237,207