Evidence map›Paper›PMID 39258540›Full record

ArticleNucleic acids research2024

ARTEMIS: a method for topology-independent superposition of RNA 3D structures and structure-based sequence alignment.

Davyd R Bohdan, Janusz M Bujnicki, Eugene F Baulin

Abstract read
In one paragraph

Article in Nucleic acids research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Davyd R BohdanInternational Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland.ORCID 0000-0002-6456-6658
Janusz M BujnickiInternational Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland.ORCID 0000-0002-6633-165X
Eugene F BaulinInternational Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland.ORCID 0000-0003-4694-9783

Funding

European Molecular Biology Organization ALTF 525-2022IIMCBNational Science Centre 2017/25/B/NZ2/01294
6 · The paper itself

Abstract

Non-coding RNAs play a major role in diverse processes in living cells with their sequence and spatial structure serving as the principal determinants of their function. Superposition of RNA 3D structures is the most accurate method for comparative analysis of RNA molecules and for inferring structure-based sequence alignments. Topology-independent superposition is particularly relevant, as evidenced by structurally similar RNAs with sequence permutations such as tRNA and Y RNA. To date, state-of-the-art methods for RNA 3D structure superposition rely on intricate heuristics, and the potential for topology-independent superposition has not been exhausted. Recently, we introduced the ARTEM method for unrestrained pairwise superposition of RNA 3D modules and now we developed it further to solve the global RNA 3D structure alignment problem. Our new tool ARTEMIS significantly outperforms state-of-the-art tools in both sequentially-ordered and topology-independent RNA 3D structure superposition. Using ARTEMIS we discovered a helical packing motif to be preserved within different backbone topology contexts across various non-coding RNAs, including multiple ribozymes and riboswitches. We anticipate that ARTEMIS will be essential for elucidating the landscape of RNA 3D folds and motifs featuring sequence permutations that thus far remained unexplored due to limitations in previous computational approaches.

Indexed as

Nucleic Acid ConformationSequence AlignmentSoftwareAlgorithmsModels, MolecularRiboswitchRNARNA, CatalyticRNA, TransferRNA, UntranslatedSequence Analysis, RNARiboswitchRNARNA, CatalyticRNA, TransferRNA, Untranslated

Identifiers

PMID39258540
PMCPMC11472068

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.