Evidence map›Paper›PMID 40753455›Full record

ArticleBiophysical journal2026

Coarse-grained RNA model for the Martini 3 force field.

Danis Yangaliev, S Banu Ozkan

Abstract read
In one paragraph

Article in Biophysical journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Perspective - RNA Dynamics Today and Tomorrow.Journal of molecular biology · 2026
    Review
  4. Article
  5. Review
  6. Article
  7. Review
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.

Danis YangalievDepartment of Physics, Arizona State University, Tempe, Arizona; Center for Biological Physics, Arizona State University, Tempe, Arizona. Electronic address: dyangali@asu.edu.
S Banu OzkanDepartment of Physics, Arizona State University, Tempe, Arizona; Center for Biological Physics, Arizona State University, Tempe, Arizona. Electronic address: banu.ozkan@asu.edu.

Funding

Using dynamic network models to quantitatively predict changes in binding affinity/specificity that arise from long-range amino acid substitutionsR01GM147635 · NIGMS · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI OZKAN, SEFIKA BANU, SWINT-KRUSE, LISKIN · 2022 to 2025
$1.8M
NIGMS NIH HHS R01 GM147635
6 · The paper itself

Abstract

In this work, we developed a coarse-grained model for RNA that is compatible with the Martini 3 force field. The model is parameterized following the Martini philosophy combining the top-down and bottom-up approaches. The nonbonded interactions in the model are derived from the partitioning of nucleobases between polar and nonpolar solvents, along with calculations of the potential of mean force between bases. For bonded interactions, parameters were refined based on atomistic simulations of double-stranded RNA. Additionally, an elastic network was incorporated to maintain the structural integrity of complex RNA molecules, such as transfer RNA, and other specific RNA configurations. We present the implementation of the Martini 3 RNA model and demonstrate its ability to capture the properties of individual bases, single-stranded RNA, double-stranded RNA, and RNA-protein complexes. Compared to the Martini 2 version, the current model offers several key advantages. It is fully compatible with the updated Martini 3 force field, exhibits greater numerical stability-allowing for the successful simulation of larger RNA-protein complexes, such as ribosomes, using the standard Martini time step of 20 fs-and it demonstrates improved agreement with all-atom models and experimental data. This new RNA model enables realistic large-scale explicit-solvent molecular dynamics simulations of complex RNA-containing systems.

Indexed as

Molecular Dynamics SimulationRNANucleic Acid ConformationSolventsRNASolvents

Identifiers

PMID40753455
PMCPMC12456326

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Registered trials

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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.