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Record W4378228886 · doi:10.1101/2023.05.24.541763

RNA structures and dynamics with Å resolution revealed by x-ray free electron lasers

2023· preprint· en· W4378228886 on OpenAlexfundno aff
Kara A. Zielinski, Shuo Sui, Suzette A. Pabit, Daniel Rivera, Tong Wang, Qingyue Hu, M.M. Kashipathy, Stella Lisova, Chris B. Schaffer, Valerio Mariani, Mark S. Hunter, Christopher Kupitz, Frank R. Moss, Frédéric Poitevin, Thomas D. Grant, Lois Pollack

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldMaterials Science
TopicEnzyme Structure and Function
Canadian institutionsnot available
FundersSLAC National Accelerator LaboratoryBasic Energy SciencesU.S. Department of EnergyOffice of ScienceNational Science FoundationNational Institutes of HealthNatural Sciences and Engineering Research Council of CanadaPfizer
KeywordsRNAStackingMacromoleculeFolding (DSP implementation)Base pairNucleic acid structureDNABiophysicsMillisecondFunction (biology)Helix (gastropod)Resolution (logic)ChemistryComputational biologyPhysicsBiologyComputer scienceCell biologyBiochemistryGeneQuantum mechanics

Abstract

fetched live from OpenAlex

RNA macromolecules, like proteins, fold to assume shapes that are intimately connected to their broadly recognized biological functions; however, because of their high charge and dynamic nature, RNA structures are far more challenging to determine. We introduce an approach that exploits the high brilliance of x-ray free electron laser sources to reveal the formation and ready identification of Å scale features in structured and unstructured RNAs. New structural signatures of RNA secondary and tertiary structures are identified through wide angle solution scattering experiments. With millisecond time resolution, we observe an RNA fold from a dynamically varying single strand through a base paired intermediate to assume a triple helix conformation. While the backbone orchestrates the folding, the final structure is locked in by base stacking. In addition to understanding how RNA triplexes form and thereby function as dynamic signaling elements, this new method can vastly increase the rate of structure determination for these biologically essential, but mostly uncharacterized macromolecules.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.128
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.007
GPT teacher head0.198
Teacher spread0.191 · 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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

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