F-RAG: Generating Atomic Coordinates from RNA Graphs by Fragment Assembly

Swati Jain, Tamar Schlick

Research output: Contribution to journalArticlepeer-review


Coarse-grained models represent attractive approaches to analyze and simulate ribonucleic acid (RNA) molecules, for example, for structure prediction and design, as they simplify the RNA structure to reduce the conformational search space. Our structure prediction protocol RAGTOP (RNA-As-Graphs Topology Prediction) represents RNA structures as tree graphs and samples graph topologies to produce candidate graphs. However, for a more detailed study and analysis, construction of atomic from coarse-grained models is required. Here we present our graph-based fragment assembly algorithm (F-RAG) to convert candidate three-dimensional (3D) tree graph models, produced by RAGTOP into atomic structures. We use our related RAG-3D utilities to partition graphs into subgraphs and search for structurally similar atomic fragments in a data set of RNA 3D structures. The fragments are edited and superimposed using common residues, full atomic models are scored using RAGTOP's knowledge-based potential, and geometries of top scoring models is optimized. To evaluate our models, we assess all-atom RMSDs and Interaction Network Fidelity (a measure of residue interactions) with respect to experimentally solved structures and compare our results to other fragment assembly programs. For a set of 50 RNA structures, we obtain atomic models with reasonable geometries and interactions, particularly good for RNAs containing junctions. Additional improvements to our protocol and databases are outlined. These results provide a good foundation for further work on RNA structure prediction and design applications.

Original languageEnglish (US)
Pages (from-to)3587-3605
Number of pages19
JournalJournal of Molecular Biology
Issue number23
StatePublished - Nov 24 2017


  • RNA atomic models
  • RNA graph partitioning
  • RNA graphs
  • RNA motif search
  • fragment assembly

ASJC Scopus subject areas

  • Biophysics
  • Structural Biology
  • Molecular Biology


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