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Record W4315782602 · doi:10.1038/s41467-022-35755-8

Structural basis of transcription recognition of a hydrophobic unnatural base pair by T7 RNA polymerase

2023· article· en· W4315782602 on OpenAlexaff
Juntaek Oh, Michiko Kimoto, Haoqing Xu, Jenny Chong, Ichiro Hirao, Dong Wang

Bibliographic record

VenueNature Communications · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Nucleic Acid Chemistry
Canadian institutionsXenon Pharmaceuticals (Canada)
FundersSLAC National Accelerator LaboratoryBasic Energy SciencesNational Institute of General Medical SciencesAgency for Science, Technology and ResearchOffice of ScienceNational Institutes of HealthU.S. Department of Health and Human ServicesU.S. Department of Energy
KeywordsT7 RNA polymeraseRNA polymeraseTranscription (linguistics)PolymeraseRNABase pairChemistryComputational biologyBacteriophageBiologyBiochemistryDNAGeneEscherichia coli

Abstract

fetched live from OpenAlex

Bacteriophage T7 RNA polymerase (T7 RNAP) is widely used for synthesizing RNA molecules with synthetic modifications and unnatural base pairs (UBPs) for a variety of biotechnical and therapeutic applications. However, the molecular basis of transcription recognition of UBPs by T7 RNAP remains poorly understood. Here we focused on a representative UBP, 7-(2-thienyl)-imidazo[4,5-b]pyridine (Ds) and pyrrole 2-carbaldehyde (Pa), and investigated how the hydrophobic Ds-Pa pair is recognized by T7 RNAP. Our kinetic assays revealed that T7 RNAP selectively recognizes the Ds or Pa base in the templates and preferentially incorporates their cognate unnatural base nucleotide substrate (PaTP or DsTP) over natural NTPs. Our structural studies reveal that T7 RNAP recognizes the unnatural substrates at the pre-insertion state in a distinct manner compared to natural substrates. These results provide mechanistic insights into transcription recognition of UBP by T7 RNAP and provide valuable information for designing the next generation of UBPs.

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 score0.004
Threshold uncertainty score0.461

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 head0.015
GPT teacher head0.264
Teacher spread0.248 · 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

Citations21
Published2023
Admission routes1
Has abstractyes

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