Evidence map›Paper›PMID 32491164›Full record

ArticleNucleic acids research2020

Topological constraints of RNA pseudoknotted and loop-kissing motifs: applications to three-dimensional structure prediction.

Xiaojun Xu, Shi-Jie Chen

Abstract read
In one paragraph

Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. RNA Folding Based on 5 Beads Model and Multiscale Simulation.Interdisciplinary sciences, computational life sciences · 2023
    Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Predicting RNA Scaffolds with a Hybrid Method of Vfold3D and VfoldLA.Methods in molecular biology (Clifton, N.J.) · 2021
    Article
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

2 authors.

Xiaojun XuInstitute of Bioinformatics and Medical Engineering, Jiangsu University of Technology, Changzhou, Jiangsu 213001, China.
Shi-Jie ChenDepartment of Physics, Department of Biochemistry, and Informatics Institute, University of Missouri, Columbia, MO 65211, USA.

Funding

New methods for computational modeling of RNA structuresR35GM134919 · NIGMS · UNIVERSITY OF MISSOURI-COLUMBIA · PI SHI-JIE CHEN · 2020 to 2026
$3.3M
Statistical Mechanics of RNA FoldingR01GM063732 · NIGMS · UNIVERSITY OF MISSOURI-COLUMBIA · PI CHEN, SHI-JIE · 2003 to 2018
$3.2M
New computational tools for predicting ion effects in RNA structuresR01GM117059 · NIGMS · UNIVERSITY OF MISSOURI-COLUMBIA · PI CHEN, SHI-JIE · 2017 to 2020
$1.2M
NIGMS NIH HHS R01 GM063732NIGMS NIH HHS R01 GM117059NIGMS NIH HHS R35 GM134919
6 · The paper itself

Abstract

An RNA global fold can be described at the level of helix orientations and relatively flexible loop conformations that connect the helices. The linkage between the helices plays an essential role in determining the structural topology, which restricts RNA local and global folds, especially for RNA tertiary structures involving cross-linked base pairs. We quantitatively analyze the topological constraints on RNA 3D conformational space, in particular, on the distribution of helix orientations, for pseudoknots and loop-loop kissing structures. The result shows that a viable conformational space is predominantly determined by the motif type, helix size, and loop size, indicating a strong topological coupling between helices and loops in RNA tertiary motifs. Moreover, the analysis indicates that (cross-linked) tertiary contacts can cause much stronger topological constraints on RNA global fold than non-cross-linked base pairs. Furthermore, based on the topological constraints encoded in the 2D structure and the 3D templates, we develop a 3D structure prediction approach. This approach can be further combined with structure probing methods to expand the capability of computational prediction for large RNA folds.

Indexed as

Molecular Dynamics SimulationRNA FoldingNucleotide MotifsRNARNA

Identifiers

PMID32491164
PMCPMC7337929

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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.