Using Combined Features to Analyze Atomic Structures Derived from Cryo-EM Density Maps.

Abstract

Cryo-electron microscopy (cryo-EM) has become a major technique for protein structure determination. Many atomic structures have been derived from cryo-EM density maps of about 3Å resolution. Side-chain conformations are well determined in density maps with super-resolutions such as 1-2Å. It is desirable to have a statistical method to detect anomalous side-chains without a super-resolution density map. In this study, we analyzed structures derived from X-ray density maps with higher than 1.5Å resolution and those from cryo-EM density maps with 2-4 Å and 4-6 Å resolutions respectively. We introduce a histogram-based outlier score (HBOS) for anomaly detection in protein models built from cryo-EM density maps. This method uses the statistics derived from X-ray dataset (<1.5Å) as the reference and combines five features involving the distal block distance, side-chain length, phi, psi, and first chi angle of the residue. Higher percentages of anomalies were observed in the cryo-EM models than in the super-resolution X-ray models. Lower percentages of anomalies were observed in cryo-EM models derived after January 2017 than those derived before 2017.