Genetic Algorithm Based Beta-Barrel Detection for Medium Resolution Cryo-EM Density Maps

Abstract

Cryo-electron microscopy (Cryo-EM) is a technique that produces three-dimensional density maps of large protein complexes and enables the study of the interactions and structures of those molecules. Identifying the secondary structures (α-helices and β-sheets) located in proteins using density maps is vital in identifying and matching the backbone of the protein with the cryo-EM density map. The β-barrel is a unique β-sheet structure commonly found in proteins, such as membranes and lipocalins. We present a new approach utilizing a genetic algorithm and ray tracing to automatically identify and extract β-barrels from cryo-EM density maps. This approach was tested using ten simulated density maps at 9 A resolution and six experimental density maps at various resolutions. The results suggest that our approach is capable of performing automatic detection and extraction of the β-barrels from medium resolution cryo-EM density maps.