Literature DB >> 28986779

Predicting RNA Structure with Vfold.

Chenhan Zhao1, Xiaojun Xu1, Shi-Jie Chen1.   

Abstract

In order to carry out biological functions, RNA molecules must fold into specific three-dimensional (3D) structures. Current experimental methods to determine RNA 3D structures are expensive and time consuming. With the recent advances in computational biology, RNA structure prediction is becoming increasingly reliable. This chapter describes a recently developed RNA structure prediction software, Vfold, a virtual bond-based RNA folding model. The main features of Vfold are the physics-based loop free energy calculations for various RNA structure motifs and a template-based assembly method for RNA 3D structure prediction. For illustration, we use the yybP-ykoY Orphan riboswitch as an example to show the implementation of the Vfold model in RNA structure prediction from the sequence.

Entities:  

Keywords:  Loop entropy; RNA folding; Template assembly; Vfold model

Mesh:

Substances:

Year:  2017        PMID: 28986779      PMCID: PMC5762135          DOI: 10.1007/978-1-4939-7231-9_1

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  35 in total

Review 1.  NMR spectroscopy of RNA.

Authors:  Boris Fürtig; Christian Richter; Jens Wöhnert; Harald Schwalbe
Journal:  Chembiochem       Date:  2003-10-06       Impact factor: 3.164

Review 2.  Folding and finding RNA secondary structure.

Authors:  David H Mathews; Walter N Moss; Douglas H Turner
Journal:  Cold Spring Harb Perspect Biol       Date:  2010-08-04       Impact factor: 10.005

3.  FR3D: finding local and composite recurrent structural motifs in RNA 3D structures.

Authors:  Michael Sarver; Craig L Zirbel; Jesse Stombaugh; Ali Mokdad; Neocles B Leontis
Journal:  J Math Biol       Date:  2007-08-11       Impact factor: 2.259

4.  Predicting structures and stabilities for H-type pseudoknots with interhelix loops.

Authors:  Song Cao; Shi-Jie Chen
Journal:  RNA       Date:  2009-02-23       Impact factor: 4.942

5.  iFoldRNA: three-dimensional RNA structure prediction and folding.

Authors:  Shantanu Sharma; Feng Ding; Nikolay V Dokholyan
Journal:  Bioinformatics       Date:  2008-06-25       Impact factor: 6.937

Review 6.  RNA folding: conformational statistics, folding kinetics, and ion electrostatics.

Authors:  Shi-Jie Chen
Journal:  Annu Rev Biophys       Date:  2008       Impact factor: 12.981

Review 7.  Computational methods in noncoding RNA research.

Authors:  Ariane Machado-Lima; Hernando A del Portillo; Alan Mitchell Durham
Journal:  J Math Biol       Date:  2007-09-04       Impact factor: 2.259

8.  DAFS: simultaneous aligning and folding of RNA sequences via dual decomposition.

Authors:  Kengo Sato; Yuki Kato; Tatsuya Akutsu; Kiyoshi Asai; Yasubumi Sakakibara
Journal:  Bioinformatics       Date:  2012-10-11       Impact factor: 6.937

9.  Predicting RNA pseudoknot folding thermodynamics.

Authors:  Song Cao; Shi-Jie Chen
Journal:  Nucleic Acids Res       Date:  2006-05-18       Impact factor: 16.971

10.  A comprehensive comparison of comparative RNA structure prediction approaches.

Authors:  Paul P Gardner; Robert Giegerich
Journal:  BMC Bioinformatics       Date:  2004-09-30       Impact factor: 3.169

View more
  13 in total

1.  Predicting Cotranscriptional Folding Kinetics For Riboswitch.

Authors:  Ting-Ting Sun; Chenhan Zhao; Shi-Jie Chen
Journal:  J Phys Chem B       Date:  2018-07-19       Impact factor: 2.991

2.  rsRNASP: A residue-separation-based statistical potential for RNA 3D structure evaluation.

Authors:  Ya-Lan Tan; Xunxun Wang; Ya-Zhou Shi; Wenbing Zhang; Zhi-Jie Tan
Journal:  Biophys J       Date:  2021-11-17       Impact factor: 4.033

Review 3.  Probing RNA structures and functions by solvent accessibility: an overview from experimental and computational perspectives.

Authors:  Md Solayman; Thomas Litfin; Jaswinder Singh; Kuldip Paliwal; Yaoqi Zhou; Jian Zhan
Journal:  Brief Bioinform       Date:  2022-05-13       Impact factor: 13.994

4.  FARFAR2: Improved De Novo Rosetta Prediction of Complex Global RNA Folds.

Authors:  Andrew Martin Watkins; Ramya Rangan; Rhiju Das
Journal:  Structure       Date:  2020-06-11       Impact factor: 5.006

5.  VfoldMCPX: predicting multistrand RNA complexes.

Authors:  Sicheng Zhang; Yi Cheng; Peixuan Guo; Shi-Jie Chen
Journal:  RNA       Date:  2022-01-20       Impact factor: 4.942

6.  Blind prediction of noncanonical RNA structure at atomic accuracy.

Authors:  Andrew M Watkins; Caleb Geniesse; Wipapat Kladwang; Paul Zakrevsky; Luc Jaeger; Rhiju Das
Journal:  Sci Adv       Date:  2018-05-25       Impact factor: 14.136

7.  Evaluating DCA-based method performances for RNA contact prediction by a well-curated data set.

Authors:  Fabrizio Pucci; Mehari B Zerihun; Emanuel K Peter; Alexander Schug
Journal:  RNA       Date:  2020-04-10       Impact factor: 4.942

8.  RNA3DCNN: Local and global quality assessments of RNA 3D structures using 3D deep convolutional neural networks.

Authors:  Jun Li; Wei Zhu; Jun Wang; Wenfei Li; Sheng Gong; Jian Zhang; Wei Wang
Journal:  PLoS Comput Biol       Date:  2018-11-27       Impact factor: 4.475

9.  RNA-Puzzles toolkit: a computational resource of RNA 3D structure benchmark datasets, structure manipulation, and evaluation tools.

Authors:  Marcin Magnus; Maciej Antczak; Tomasz Zok; Jakub Wiedemann; Piotr Lukasiak; Yang Cao; Janusz M Bujnicki; Eric Westhof; Marta Szachniuk; Zhichao Miao
Journal:  Nucleic Acids Res       Date:  2020-01-24       Impact factor: 16.971

Review 10.  RNA 3D Structure Prediction Using Coarse-Grained Models.

Authors:  Jun Li; Shi-Jie Chen
Journal:  Front Mol Biosci       Date:  2021-07-02
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.