Iterative Molecular Dynamics-Rosetta Membrane Protein Structure Refinement Guided by Cryo-EM Densities.

Area of Science:

• Structural Biology
• Computational Biology
• Biophysics

Background:

• Atomistic protein details are crucial for function and drug development.
• Experimental methods like cryo-electron microscopy (cryo-EM) excel at protein structure determination.
• Computational methods struggle with large proteins lacking sequence similarity, necessitating integration of experimental data.

Purpose of the Study:

• To extend cryo-EM density-guided Rosetta-MD protocol for membrane protein structure refinement.
• To improve model selection by combining Rosetta score and fit-to-density.
• To enhance the accuracy of protein structure prediction and refinement.

Main Methods:

• Applied cryo-EM density-guided iterative Rosetta-MD to five membrane-spanning proteins.
• Implemented a refined model selection strategy using both Rosetta score and fit-to-density.
• Tested the protocol's efficacy with varying cryo-EM density map resolutions.

Main Results:

• Successfully refined predicted membrane protein structures to atomic resolution.
• Demonstrated that higher-resolution cryo-EM maps (∼4 Å) yield superior model refinement compared to lower-resolution maps (6.9 Å).
• Reduced average root mean square deviation (RMSD) from 4.66 Å to 1.66 Å using 4 Å density maps.

Conclusions:

• Cryo-EM density-guided Rosetta-MD is effective for refining membrane protein structures.
• The resolution of cryo-EM density maps directly impacts the quality of refined models.
• The improved protocol refines soluble and membrane protein structures with enhanced accuracy.