Validation (cryo-EM)

Why

Many steps are involved to get from the initial idea about a molecule to the final atomic model and its interpretation. Errors can occur in each of these steps, so validation procedures are necessary to ensure that the atomic models are reasonable and fit the experimental data.

In particular, validation addresses data, model, and model-versus-data quality:

• Data. The quality of experimental data, such as the resolution or amount of noise, defines the quality of the derived models. Therefore, it is vital to understand the data quality so that you use the correct model-building and refinement procedures appropriate for the data at hand. (See the Assessing Map Quality (cryo-EM) overview for more details.)
• Model. The underlying principles behind model validation are the same for any experimental method: a good model should make chemical sense and be consistent with empirical statistics for high-quality prior structures. Thus, atomic models derived from cryo-EM reconstructions should conform to prior knowledge about covalent geometry, non-bonded interactions, and known distributions of side-chain and main-chain conformations in both proteins and nucleic acids. Generally, the goal is to have as few outliers as is feasible, where outliers can be explained by their environment and/or experimental data.
• Model-versus-data fit. Model-verses-data validation criteria require the model to describe its own data well. A perfectly good model from a stereochemistry perspective may not fit the 3D reconstruction sufficiently or at all. In reciprocal space, model-versus-data agreement is assessed by curves of the Fourier shell correlation (FSC) as a function of resolution. In real space, the agreement is measured by correlation coefficients (CCs).

How

Comprehensive validation (cryo-EM) is a one-stop program in Phenix that validates model, data, and model-versus-data fit. The minimal input is a map (in MRC, CCP4, or related format) and an atomic model (in PDB or mmCIF format). However, providing a map, model, and two half-maps is desirable.

For geometric validation, Phenix uses MolProbity, which is fully integrated into the Comprehensive validation (cryo-EM) package. The graphics programs Coot and PyMOL are also fully integrated, enabling communication of the validation results.

How to use the validation tools in the Phenix GUI: Click here

Common issues

• Outliers versus errors: In most structures, there will be Ramachandran and side-chain rotamer outliers. If the data (the map) and surrounding chemistry supports the outlier conformation, then it is most likely an outlier from prior expectations. In the absence of supporting density and/or conflicting local chemistry, it is probably an error that needs correction. For example, an atomic model derived from low-resolution data is expected to have no geometrical outliers because they are unlikely to be supported by the experimental data.

Related programs

• phenix.cablam_validation: The C-Alpha Based Low-Resolution Annotation Method (CaBLAM) validates protein backbone conformations in models determined at low resolution (2.5-4 Å), where it is difficult to determine peptide orientations because carbonyl O atoms cannot be discerned in the density maps. The program uses protein C-alpha geometry to evaluate the main-chain geometry and identify areas of probable secondary structure.
• phenix.mtriage: This program computes various cryo-EM map statistics, including resolution estimates, Fourier shell correlation curves, and more.