Q - score as a reliability measure for protein, nucleic acid, and small molecule atomic coordinate models derived...

Area of Science:

• Structural Biology
• Biophysics
• Computational Biology

Background:

• Atomic coordinate models are crucial for interpreting 3D electron microscopy (3DEM) maps from techniques like cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET).
• Quantitative metrics are needed to assess the reliability of atomic coordinates and their support by experimental 3DEM maps, beyond visual inspection.

Purpose of the Study:

• To perform statistical analyses of the $$ metric using a large dataset of 3DEM maps and models.
• To introduce and validate two new metrics ($$ and $$) for comparing map-model fits against databases.
• To demonstrate the utility of these metrics in evaluating atomic coordinate quality and identifying areas of poor resolution in 3DEM data.

Main Methods:

• Statistical analysis of $$ applied to over 10,000 maps and models from EMDB and PDB.
• Development and application of new metrics $$ and $$ for comparative analysis.
• Case studies using proteins, nucleic acids, and small molecules to illustrate metric interpretation.

Main Results:

• The $$ metric shows good correlation with map resolution for well-fitted models.
• New metrics $$ and $$ enable comparison against EMDB entries and resolution-matched datasets.
• $$ effectively identifies well-fitted regions and areas affected by flexibility, damage, or heterogeneity.

Conclusions:

• The $$ metric and its derivatives offer a robust framework for evaluating the quality of atomic coordinate models against 3DEM maps.
• These metrics facilitate effective interpretation and quality control of 3DEM data prior to publication and archiving.
• Conversion of $$ to atomic $$ is demonstrated, enhancing practical application.