Evidence map›Paper›PMID 42394168›Full record

ArticleBiophysical journal2026

Structure-based simulations of the full Flock House virus capsid reveal pathways and energetics of infection-critical peptide externalization.

Rey G Carten, Eric R May

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. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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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

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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

2 authors.

Rey G CartenDepartment of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06269, USA.
Eric R MayDepartment of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06269, USA; Department of Chemistry, University of Connecticut, Storrs, CT 06269, USA. Electronic address: eric.may@uconn.edu.

Funding

Structural Dynamics of Viral Proteins: Development and Application of Multiscale Computational Methods for Studying Viral Capsids, Proteins and Membrane SystemsR35GM119762 · NIGMS · UNIVERSITY OF CONNECTICUT STORRS · PI Eric Robert May · 2016 to 2026
$4.1M
NIGMS NIH HHS R35 GM119762
6 · The paper itself

Abstract

Viral capsids are metastable assemblies whose large-scale dynamics enable critical steps in infection, including the exposure of internal protein segments that interact with host membranes. Resolving the mechanisms underlying these transitions remains challenging because they involve rare, cooperative motions distributed across entire viral particles. Here, we develop a full-capsid structure-based molecular dynamics framework to investigate infection-relevant dynamics in the T = 3 Flock House virus capsid, a model nonenveloped RNA virus. This native contact-centric coarse-grained representation enables systematic exploration of peptide externalization pathways while preserving the geometric and topological constraints of the intact capsid. To capture infection-relevant environmental changes, we introduce a low-pH capsid model derived from collective structural modes observed in full-capsid atomistic simulations. This approach provides a physically motivated representation of acid-induced capsid deformation while filtering high-frequency fluctuations. Simulations of γ peptide externalization reveal distinct symmetry-dependent escape mechanisms, with exit through the 5-fold axis of symmetry being the most favored. The acidification-associated low-pH structural perturbation modestly reshapes the underlying energy landscape, reducing the energetic cost of peptide release, with the strongest favorability emerging when combined with internal mechanical stress that mimics genome confinement. These findings demonstrate how capsid geometry, symmetry, and environmental conditions couple to regulate peptide release in an RNA virus. More broadly, this work highlights how full-capsid structure-based models can provide an efficient framework for probing functional energy landscapes in large viral assemblies.

Identifiers

PMID42394168
PMCPMC13625885

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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.