Seeing the Invisible: 50 Years of Macromolecular Visualization

Figure 1- a) Key to MolProbity visualization of good and bad all-atom contacts; b) In very high-resolution structures, contacts are typically near-ideal (PDB file 1gci); c) MolProbity includes other model validation criteria to complement the all-atom contacts; d) The combined visual validation-outlier markup guides correction of local modeling errors (PDB file 1j58).

Figure 2 – The appearance of electron density for parts of the T4 phage lysozyme structure at different resolutions: a) At 4Å, backbone connectivity is pretty unambiguous, and the shape of protein α-helices and DNA or RNA double-helices is fairly clear, but very few sidechains can be identified; b) At 3Å, beta-sheets, loops, and most sidechains are seen, but specific backbone and sidechain conformations are unclear; c) At 2Å (or at 2.5Å), the carbonyl oxygens along the backbone are finally visible, defining the orientation of the peptides, and sidechain shapes clearly identify the amino-acid sequence; d) At 1Å (rarely achieved), almost all atoms can be seen separately. Source: 4gbr 3.99Å, 5zbh 3.0Å, 1lyi 2.0Å, 5jdt 1.0Å.

At 2Å resolution, the most common for crystal structures, the electron density is sufficiently detailed for building a good atomic model. If all of MolProbity’s criteria score well and the fit of model to map is good, then that model is (almost surely) essentially correct. That assurance, however, vanishes by 3Å resolution, at which point sidechain shapes, and crucially the carbonyl oxygens, disappear into blobs or tubes and thus the articulation between backbone peptide units is unclear and sidechains are often mispositioned.

Figure 3 - CryoEM structure at 4Å resolution of a membrane receptor that responds both to cold and to menthol (PDB file 6nr2; Yin 2019). (Above) Side and top views of the three-dimensional density map reconstructed from thousands of two-dimensional EM images. (Below) Ribbon diagram of the atomic model. Seok-Yong Lee’s group collected this data at the Duke cryoEM facility.

The challenge is that, as seen in Figure 2, density at 3 to 4Å is very broad and is equally compatible with many rather different atomic models. Discriminating correctly among those model possibilities requires a great deal of additional information. CryoEM (or X-ray) models at these resolutions are often provided with extra information by refinement against traditional validation criteria. The resulting model is somewhat better, on average, but that refinement makes those criteria meaningless for validation. It can even make local conformations worse by hiding outliers without fixing the underlying problems (Richardson 2018). With all outliers refined away, MolProbity has been misleadingly assigning much better scores to these structures than they actually deserve.

This situation is dangerous, because adding up local errors makes larger-scale errors more likely, such as wrong chain connectivity or stretches of sequence out of register from the correct placement. Those errors, in turn, can invalidate biological conclusions and lead to paper retractions, as happened in crystallography around 1990 and motivated the initial development of validation methods.

Figure 4 – (Left) Two successive CaBLAM outliers (magenta) at the end of an α-helix (PDB file 4hel). (Right) Fixing the modeling error by reorienting the central carbonyl oxygen (red ball) is shown correct by a higher-resolution structure (PBD file 3osx).

Several additional independent validation metrics for 3-4Å are needed to make serious errors less likely. The Richardson lab and other groups are thus hard at work on such developments.