Evidence map›Paper›PMID 42856268›Full record

ArticlebioRxiv : the preprint server for biology2026

Network analysis of correlated conformational dynamics across the evolution of influenza A virus NS1.

Abhishek Bastiray, James E Gonzales, Wonmuk Hwang, Jae-Hyun Cho

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 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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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

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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.

Abhishek BastirayDepartment of Biochemistry and Biophysics, Texas A&M University, College Station, TX 77843, USA.
James E GonzalesDepartment of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA.
Wonmuk HwangDepartment of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA.
Jae-Hyun ChoDepartment of Biochemistry and Biophysics, Texas A&M University, College Station, TX 77843, USA.

Funding

Mechanistic bases of strain-specific virus-host interactionsR35GM152007 · NIGMS · TEXAS A&M AGRILIFE RESEARCH · PI Jae Hyun Cho · 2024 to 2026
$1.1M
NIGMS NIH HHS R35 GM152007
6 · The paper itself

Abstract

Protein evolution requires sequence changes to alter molecular properties without disrupting the dynamic organization necessary for function. How residue-level networks of correlated motions accommodate such mutations remains poorly understood. Here, we investigate the evolution of correlated conformational dynamics in nonstructural protein 1 (NS1) variants of influenza A viruses that emerged between 1918 and 2004. From molecular dynamics (MD) simulations we built residue networks in which edge weights reflect generalized correlations of conformational motion. The network of correlated dynamics is characterized using centrality analysis. Overall network properties are well-conserved across NS1 variants, indicating evolutionary robustness of the dynamical network. Residues ranked highly across multiple centrality measures form a predominantly hydrophobic cluster in the protein core. These residues exhibited low conformational entropy and high sequence conservation, consistent with rigid, coordinated motions. In contrast, residues exhibiting large differences in betweenness and closeness centrality ranks occupied flexible, solvent-exposed regions surrounding the core network. These residues also showed lower evolutionary conservation. These findings reveal a core-periphery structure in which a rigid hydrophobic network enables long-range dynamic connectivity while more adaptable peripheral regions accommodate evolutionary sequence variation. This architecture provides a mechanistic framework for long-range epistatic interactions without compromising the underlying structural framework.

Identifiers

PMID42856268
PMCPMC13648610

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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.