Evidence map›Paper›PMID 28301768›Full record

ReviewAnnual review of biophysics2017

Theory and Modeling of RNA Structure and Interactions with Metal Ions and Small Molecules.

Li-Zhen Sun, Dong Zhang, Shi-Jie Chen

Abstract readReview
In one paragraph

Review in Annual review of biophysics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers.

0numbers the graph read from it
0cells of the map it votes in
68citing 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

68 citing papers in PubMed.

  1. Article
  2. Review
  3. Comparative Evaluation of Explicit Solvent Models for RNA-Ligand Docking.Journal of chemical information and modeling · 2026
    Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. RNA 3D Structure Prediction: Progress and Perspective.Molecules (Basel, Switzerland) · 2023
    Review
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article

8 more citing papers are in PubMed but not listed here.

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.

Li-Zhen SunDepartment of Physics, Department of Biochemistry, and MU Informatics Institute, University of Missouri, Columbia, Missouri 65211; email: chenshi@missouri.edu.
Dong ZhangDepartment of Physics, Department of Biochemistry, and MU Informatics Institute, University of Missouri, Columbia, Missouri 65211; email: chenshi@missouri.edu.
Shi-Jie ChenDepartment of Physics, Department of Biochemistry, and MU Informatics Institute, University of Missouri, Columbia, Missouri 65211; email: chenshi@missouri.edu.

Funding

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 GM117059
6 · The paper itself

Abstract

In addition to continuous rapid progress in RNA structure determination, probing, and biophysical studies, the past decade has seen remarkable advances in the development of a new generation of RNA folding theories and models. In this article, we review RNA structure prediction models and models for ion-RNA and ligand-RNA interactions. These new models are becoming increasingly important for a mechanistic understanding of RNA function and quantitative design of RNA nanotechnology. We focus on new methods for physics-based, knowledge-based, and experimental data-directed modeling for RNA structures and explore the new theories for the predictions of metal ion and ligand binding sites and metal ion-dependent RNA stabilities. The integration of these new methods with theories about the cellular environment effects in RNA folding, such as molecular crowding and cotranscriptional kinetic effects, may ultimately lead to an all-encompassing RNA folding model.

Indexed as

CationsDatabases, Nucleic AcidKineticsLigandsMagnesiumMetalsModels, MolecularNucleic Acid ConformationPotassiumRNASodiumThermodynamicsCationsLigandsMagnesiumMetalsPotassiumRNASodiumknowledge-based approachnonspecific ion bindingphysics-based modelingspecific ion bindingthree-dimensional structure prediction

Identifiers

PMID28301768
PMCPMC5508874

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.