Sampling globally and locally correct RNA 3D structures using Ernwin, SPQR and experimental SAXS data.

Area of Science:

• Structural Biology
• Computational Biology
• Biophysics

Background:

• Determining the 3D structure of large RNA in solution is complex, often requiring multiple experimental and computational methods.
• Small-angle X-ray scattering (SAXS) provides geometrical insights but needs careful interpretation for 3D modeling.
• Existing methods may not fully leverage SAXS data for accurate RNA structure prediction.

Purpose of the Study:

• To introduce a novel multiscale computational pipeline for modeling the global shape and atomistic structure of large RNA molecules in solution.
• To integrate small-angle X-ray scattering (SAXS) data effectively into the RNA modeling process.
• To refine RNA structures hierarchically from low resolution to explicit solvent atomistic detail.

Main Methods:

• A multiscale pipeline combining a low-resolution helix model (Ernwin) for conformational exploration using SAXS data.
• A nucleotide-level model (SPQR) for clash removal and structure refinement.
• Hierarchical refinement to achieve atomistic precision in explicit solvent.

Main Results:

• The pipeline successfully modeled four known RNA structures (up to 159 nucleotides) with promising accuracy.
• An all-atom structure of Plasmodium falciparum signal recognition particle ALU RNA was predicted using SAXS data.
• The predicted structure showed an alternate conformation with a better fit to SAXS data than previously published models.

Conclusions:

• The proposed multiscale pipeline effectively integrates SAXS data for accurate 3D RNA structure determination in solution.
• This approach enables the refinement of RNA structures from low-resolution shapes to high-resolution atomistic models.
• The method offers a powerful tool for structural biology, particularly for challenging RNA molecules like the studied ALU RNA.