MDTOMO method for continuous conformational variability analysis in cryo electron subtomograms based on molecular...

Area of Science:

• Structural biology
• Biophysics
• Computational biology

Background:

• Cryo-electron tomography (cryo-ET) visualizes macromolecular complexes in native environments.
• Subtomogram averaging (STA) reveals 3D structures but is limited by small complex numbers, hindering comprehensive conformational analysis.
• Current methods struggle to capture the full conformational landscape of molecular complexes.

Purpose of the Study:

• To introduce MDTOMO, a novel method for analyzing continuous conformational variability in cryo-ET data.
• To generate atomic-scale models and free-energy landscapes from cryo-ET subtomograms.
• To overcome limitations of discrete classification in revealing complete conformational heterogeneity.

Main Methods:

• MDTOMO integrates cryo-ET subtomograms with Molecular Dynamics (MD) simulations.
• The method analyzes continuous conformational changes within molecular complexes.
• It models the free-energy landscape associated with observed conformations.

Main Results:

• MDTOMO successfully generated atomic-scale models of conformational variability.
• The method elucidated free-energy landscapes from cryo-ET data.
• Performance was validated on synthetic ABC exporter and in situ SARS-CoV-2 spike datasets.

Conclusions:

• MDTOMO provides a powerful approach to analyze dynamic properties of molecular complexes.
• This method enhances understanding of biological functions through in situ structural data.
• MDTOMO has potential applications in structure-based drug discovery.