Evidence map›Paper›PMID 42535650›Full record

ArticleNucleic acids research2026

Protein crowders remodel RNA electrostatics, hydration, and dynamics: a challenge to steric crowding models.

Anja Henning-Knechtel, Marko Brnović, Weiwei He, Serdal Kirmizialtin

Abstract read
In one paragraph

Article in Nucleic acids research, 2026. 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

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

4 authors.

Anja Henning-KnechtelChemistry Program, Math and Sciences, New York University Abu Dhabi, Abu Dhabi, 12988, UAE.
Marko BrnovićChemistry Program, Math and Sciences, New York University Abu Dhabi, Abu Dhabi, 12988, UAE.
Weiwei HeChemistry Program, Math and Sciences, New York University Abu Dhabi, Abu Dhabi, 12988, UAE.ORCID 0000-0001-9955-2902
Serdal KirmizialtinChemistry Program, Math and Sciences, New York University Abu Dhabi, Abu Dhabi, 12988, UAE.ORCID 0000-0001-8380-5725

Funding

NYUAD AD181
6 · The paper itself

Abstract

The intracellular environment is densely populated with macromolecules, creating crowded conditions. Whether in vitro environments or synthetic crowders like polyethylene glycol (PEG) accurately capture the complexity of RNA interactions in vivo remains unclear. Using all-atom molecular dynamics simulations, we investigated the HIV-1 TAR RNA hairpin in dilute, PEG-crowded, and realistic protein-crowded solutions. We found that PEG primarily exerts excluded-volume effects, maintaining RNA hydration and Na$^{+}$ ion condensation similar to dilute conditions. In contrast, protein crowders significantly altered RNA electrostatics, reducing Na$^{+}$ condensation by nearly 60%, displacing surface hydration water, and forming chemically specific contacts dominated by positively charged residues, notably arginine, and lysine. These interactions led to local RNA expansion and reshaped its conformational landscape without disrupting the global fold. Moreover, protein crowding dramatically slowed RNA translational and rotational dynamics, as well as local water and ion mobility, whereas these effects were minimal with PEG. Our findings emphasize that crowder identity critically determines RNA behavior and challenge the use of PEG as a universal model for intracellular conditions, providing mechanistic predictions for RNA studies in biologically relevant environments.

Indexed as

RNARNA, ViralHIV-1Molecular Dynamics SimulationNucleic Acid ConformationPolyethylene GlycolsStatic ElectricityWaterPolyethylene GlycolsRNARNA, ViralWater

Identifiers

PMID42535650
PMCPMC13425243

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.