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RNA Secondary Structure Prediction Using High-throughput SHAPE
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VfoldLA: A web server for loop assembly-based prediction of putative 3D RNA structures.

Xiaojun Xu1, Chenhan Zhao2, Shi-Jie Chen2

  • 1Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, Jiangsu 213001, China.

Journal of Structural Biology
|June 8, 2019
PubMed
Summary

Predicting large RNA 3D structures is challenging. The new VfoldLA web server automates this process using a loop-classification model, aiding RNA structure-function studies.

Keywords:
Loop templatesRNAStructure predictionVfoldLA

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Area of Science:

  • Structural Biology
  • Computational Biology
  • Bioinformatics

Background:

  • Three-dimensional (3D) RNA structures are essential for cellular functions.
  • Predicting complex RNA structures is a significant challenge, limiting the understanding of RNA structure-function relationships.

Purpose of the Study:

  • To introduce the VfoldLA web server for predicting RNA 3D structures.
  • To provide a user-friendly, automated platform for RNA structure prediction.

Main Methods:

  • The VfoldLA server utilizes a novel VfoldLA model that classifies single-stranded loops into four types.
  • RNA 3D structures are assembled from loop/junction templates based on loop-helix connections.
  • The server accepts nucleotide sequences and base-pair information (2D structure) as input.

Main Results:

  • The VfoldLA web server offers a fully automated prediction of putative 3D RNA structures.
  • Users can input single-RNA or RNA-RNA complex sequences and 2D structures.
  • Outputs include JSmol visualization and downloadable Protein Data Bank (PDB) files.

Conclusions:

  • The VfoldLA server provides a valuable tool for predicting RNA 3D structures.
  • The generated structures can serve as scaffolds for further structure refinement.
  • This facilitates research into RNA structure-function relationships.