Evidence map›Paper›PMID 39605385›Full record

ArticlebioRxiv : the preprint server for biology2025

Driving Forces of RNA Condensation Revealed through Coarse-Grained Modeling with Explicit Mg

Shanlong Li, Jianhan Chen

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Shanlong LiDepartment of Chemistry, University of Massachusetts, Amherst, MA 01003, USA.
Jianhan ChenDepartment of Chemistry, University of Massachusetts, Amherst, MA 01003, USA.

Funding

Disordered Proteins and Dynamic Interactions in Biology and Diseases.R35GM144045 · NIGMS · UNIVERSITY OF MASSACHUSETTS AMHERST · PI Jianhan Chen · 2022 to 2026
$2.0M
NIGMS NIH HHS R35 GM144045
6 · The paper itself

Abstract

RNAs are major drivers of phase separation in the formation of biomolecular condensates, and can undergo protein-free phase separation in the presence of divalent ions or crowding agents. Much remains to be understood regarding how the complex interplay of base stacking, base pairing, electrostatics, ion interactions, and particularly structural propensities governs RNA phase behavior. Here we develop an SIGNIFICANCE STATEMENT: Dynamic RNAs and proteins are major drivers of biomolecular phase separation that has been recently discovered to underlie numerous biological processes and be involved in many human diseases. Molecular simulation has an indispensable role to play in dissecting the driving forces and regulation of biomolecular phase separation. The current work describes a high-resolution coarse-grained RNA model that is capable of describing the structure dynamics and complex sequence, concentration, temperature and ion dependent phase transitions of flexible RNAs. The study further reveals a central role of RNA folding in coordinating Mg

Indexed as

biomolecular phase separationlower critical solution temperatureMagnesium-RNA interactionphase diagramtriplet repeat RNA

Identifiers

PMID39605385
PMCPMC11601354

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.