ArticleBiophysical journal2026
Structure-based simulations of the full Flock House virus capsid reveal pathways and energetics of infection-critical peptide externalization.
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.
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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.
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