Ensemble refinement of mismodeled cryo-EM RNA structures using all-atom simulations

Area of Science:

• Structural biology
• Computational biology
• Biochemistry

Background:

• Single-particle cryogenic electron microscopy (cryo-EM) achieves near-atomic resolution for large macromolecules.
• Current cryo-EM refinement methods often produce a single structure, potentially misrepresenting flexible molecules like RNA.
• Accurate structural modeling is crucial for understanding RNA function.

Purpose of the Study:

• To develop and apply a method combining molecular dynamics (MD) simulations with cryo-electron microscopy (cryo-EM) density maps.
• To better model the structural dynamics of complex RNA molecules.
• To reveal limitations of single-structure approaches for flexible RNAs.

Main Methods:

• Utilized metainference, a Bayesian approach, to integrate MD simulations with cryo-EM data.
• Reconstructed an ensemble of structures for the group II intron ribozyme.
• Analyzed RNA-containing cryo-EM structures in the Protein Data Bank (PDB).

Main Results:

• The metainference method generated an ensemble of structures that better matched experimental cryo-EM data.
• Identified inaccuracies in single-structure models for flexible regions of the group II intron ribozyme.
• Found that most cryo-EM structures of RNAs (2.5–4 Å resolution) exhibit similar issues.

Conclusions:

• Cryo-EM structures of RNA require careful interpretation, especially for flexible regions.
• The developed ensemble-based approach offers a more accurate representation of RNA dynamics.
• This method has broad applicability for studying diverse RNA systems using cryo-EM data.