Assessment of protein–protein interfaces in cryo-EM derived assemblies

Sony Malhotra (), Agnel Praveen Joseph, Jeyan Thiyagalingam and Maya Topf ()
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Sony Malhotra: University of London
Agnel Praveen Joseph: Scientific Computing Department, Science and Technology Facilities Council
Jeyan Thiyagalingam: Scientific Computing Department, Science and Technology Facilities Council
Maya Topf: University of London

Nature Communications, 2021, vol. 12, issue 1, 1-12

Abstract: Abstract Structures of macromolecular assemblies derived from cryo-EM maps often contain errors that become more abundant with decreasing resolution. Despite efforts in the cryo-EM community to develop metrics for map and atomistic model validation, thus far, no specific scoring metrics have been applied systematically to assess the interface between the assembly subunits. Here, we comprehensively assessed protein–protein interfaces in macromolecular assemblies derived by cryo-EM. To this end, we developed Protein Interface-score (PI-score), a density-independent machine learning-based metric, trained using the features of protein–protein interfaces in crystal structures. We evaluated 5873 interfaces in 1053 PDB-deposited cryo-EM models (including SARS-CoV-2 complexes), as well as the models submitted to CASP13 cryo-EM targets and the EM model challenge. We further inspected the interfaces associated with low-scores and found that some of those, especially in intermediate-to-low resolution (worse than 4 Å) structures, were not captured by density-based assessment scores. A combined score incorporating PI-score and fit-to-density score showed discriminatory power, allowing our method to provide a powerful complementary assessment tool for the ever-increasing number of complexes solved by cryo-EM.

Date: 2021
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DOI: 10.1038/s41467-021-23692-x

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