Evidence map›Paper›PMID 38780739›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2024

The Multiscale Ernwin/SPQR RNA Structure Prediction Pipeline.

Bernhard C Thiel, Simón Poblete, Ivo L Hofacker

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Article in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Bernhard C ThielDepartment of Theoretical Chemistry, Faculty of Chemistry, University of Vienna, Vienna, Austria.
Simón PobleteInstituto de Ciencias Físicas y Matemáticas, Universidad Austral de Chile, Valdivia, Chile.
Ivo L HofackerDepartment of Theoretical Chemistry, Faculty of Chemistry, University of Vienna, Vienna, Austria. ivo@tbi.univie.ac.at.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aside from the well-known role in protein synthesis, RNA can perform catalytic, regulatory, and other essential biological functions which are determined by its three-dimensional structure. In this regard, a great effort has been made during the past decade to develop computational tools for the prediction of the structure of RNAs from the knowledge of their sequence, incorporating experimental data to refine or guide the modeling process. Nevertheless, this task can become exceptionally challenging when dealing with long noncoding RNAs, constituted by more than 200 nucleotides, due to their large size and the specific interactions involved. In this chapter, we describe a multiscale approach to predict such structures, incorporating SAXS experimental data into a hierarchical procedure which couples two coarse-grained representations: Ernwin, a helix-based approach, which deals with the global arrangement of secondary structure elements, and SPQR, a nucleotide-centered coarse-grained model, which corrects and refines the structures predicted at the coarser level.We describe the methodology through its application on the Braveheart long noncoding RNA, starting from the SAXS and secondary structure data to propose a refined, all-atom structure.

Indexed as

Nucleic Acid ConformationRNA, Long NoncodingScattering, Small AngleX-Ray DiffractionAlgorithmsComputational BiologyModels, MolecularRNASoftwareRNARNA, Long NoncodingCoarse-grainMultiscale modelingRNA structureSAXSStructure prediction

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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.