Beyond Pango: The future of virus lineage classification
Keeping pace with ever-changing viruses is a challenge. This study unveils an automated system for classifying viral lineages based on genetics, offering a faster and more objective approach
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RNA-protein complex refinement using AI modeling and docking
This study presents an efficient technique for refining protein-RNA complexes using AI-based modeling and flexible docking. The method, utilizing parallel cascade selection molecular dynamics (PaCS-MD), accelerates conformational sampling of flexible RNA regions and produces high-quality complex models. Experimental validation demonstrates its superiority over template-based modeling, suggesting its potential for constructing complexes with non-canonical RNA-protein interactions
Co-transcriptional riboswitch modleing with ViennaRNA
Riboswitches are RNA molecules that regulate gene expression by sensing metabolites, presenting an interesting target for synthetic biology applications. We present a computational approach based on ViennaRNA tools to dissect and model RNA-ligand interaction dynamics under kinetic control, enabling simulation of riboswitch folding
In silico design of ligand triggered RNA switches
In the world of synthetic biology, the design of RNA switches holds immense promise for various applications, ranging from diagnostics to therapeutics. This paper presents a comprehensive workflow for designing RNA switches that can dynamically alter their structural conformations in response to specific ligands
SHAPE directed RNA folding with the ViennaRNA Package
The ViennaRNA Package supports three published approaches for SHAPE-guided RNA structure prediction. Here we evaluate and compare the methods by Deigan, Zarringhalam, and Washietl
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