RNA 3D Modeling with FARFAR2, Online

Methods Mol Biol. 2023:2586:233-249. doi: 10.1007/978-1-0716-2768-6_14.

Abstract

Understanding the three-dimensional structure of an RNA molecule is often essential to understanding its function. Sampling algorithms and energy functions for RNA structure prediction are improving, due to the increasing diversity of structural data available for training statistical potentials and testing structural data, along with a steady supply of blind challenges through the RNA-Puzzles initiative. The recent FARFAR2 algorithm enables near-native structure predictions on fairly complex RNA structures, including automated selection of final candidate models and estimation of model accuracy. Here, we describe the use of a publicly available webserver for RNA modeling for realistic scenarios using FARFAR2, available at https://rosie.rosettacommons.org/farfar2 . We walk through two cases in some detail: a simple model pseudoknot from the frameshifting element of beet western yellows virus modeled using the "basic interface" to the webserver and a replication of RNA-Puzzle 20, a metagenomic twister sister ribozyme, using the "advanced interface." We also describe example runs of FARFAR2 modeling including two kinds of experimental data: a c-di-GMP riboswitch modeled with low-resolution restraints from MOHCA-seq experiments and a tandem GA motif modeled with 1H NMR chemical shifts.

Keywords: 3D structure modeling; RNA; Rosetta.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Models, Molecular
  • Nucleic Acid Conformation
  • RNA* / chemistry
  • RNA, Catalytic* / chemistry

Substances

  • RNA
  • RNA, Catalytic