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Vfold-Pipeline: a web server for RNA 3D structure prediction from sequences.
Li, Jun; Zhang, Sicheng; Zhang, Dong; Chen, Shi-Jie.
Afiliação
  • Li J; Department of Physics, Department of Biochemistry, and Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA.
  • Zhang S; Department of Physics, Department of Biochemistry, and Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA.
  • Zhang D; College of Life Sciences and Institute of Quantitative Biology, Zhejiang University, Hangzhou 310058, China.
  • Chen SJ; Department of Physics, Department of Biochemistry, and Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA.
Bioinformatics ; 38(16): 4042-4043, 2022 08 10.
Article em En | MEDLINE | ID: mdl-35758624
ABSTRACT

SUMMARY:

RNA 3D structures are critical for understanding their functions and for RNA-targeted drug design. However, experimental determination of RNA 3D structures is laborious and technically challenging, leading to the huge gap between the number of sequences and the availability of RNA structures. Therefore, the computer-aided structure prediction of RNA 3D structures from sequences becomes a highly desirable solution to this problem. Here, we present a pipeline server for RNA 3D structure prediction from sequences that integrates the Vfold2D, Vfold3D and VfoldLA programs. The Vfold2D program can incorporate the SHAPE experimental data in 2D structure prediction. The pipeline can also automatically extract 2D structural constraints from the Rfam database. Furthermore, with a significantly expanded 3D template database for various motifs, this Vfold-Pipeline server can efficiently return accurate 3D structure predictions or reliable initial 3D structures for further refinement. AVAILABILITY AND IMPLEMENTATION http//rna.physics.missouri.edu/vfoldPipeline/index.html. The data underlying this article have been provided in the article and in its online supplementary material. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / RNA Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / RNA Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article