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

Area of Science:

• Computational Biology
• Structural Bioinformatics
• Biophysics

Background:

• Coarse-grained models simplify ribonucleic acid (RNA) structures for efficient simulation and analysis, crucial for structure prediction and design.
• Converting these simplified models to all-atom representations is essential for detailed studies but remains challenging.
• Existing methods require robust protocols for accurate atomic model generation from coarse-grained RNA representations.

Purpose of the Study:

• To present the Fragment-based RNA Assembled by Graphs (F-RAG) algorithm for converting coarse-grained RNA graph models into all-atom structures.
• To validate the F-RAG algorithm's performance against experimentally determined RNA structures.
• To establish a foundation for improved RNA structure prediction and design applications.

Main Methods:

• RNA structures are represented as tree graphs using the RNA-As-Graphs Topology Prediction (RAGTOP) protocol.
• The F-RAG algorithm partitions graphs into subgraphs and searches a database for similar atomic fragments.
• Fragments are assembled, scored using RAGTOP's potential, and optimized to generate all-atom models.

Main Results:

• The F-RAG algorithm successfully generated all-atom RNA models with reasonable geometries and residue interactions from coarse-grained inputs.
• Evaluation using all-atom RMSD and Interaction Network Fidelity showed good performance, especially for RNA structures with junctions.
• Comparison with other fragment assembly programs demonstrated competitive results.

Conclusions:

• The F-RAG algorithm provides an effective method for converting coarse-grained RNA models to all-atom structures.
• This approach significantly contributes to advancing RNA structure prediction and design capabilities.
• Further refinements to the protocol and databases are expected to enhance future applications.