Beta-Barrel Detection for Medium Resolution Cryo-Electron Microscopy Density Maps Using Genetic Algorithms and Ray Tracing

J Comput Biol. 2018 Mar;25(3):326-336. doi: 10.1089/cmb.2017.0155. Epub 2017 Oct 16.

Abstract

Cryo-electron microscopy (cryo-EM) is a technique that produces three-dimensional density maps of large protein complexes. This allows for the study of the structure of these proteins. Identifying the secondary structures within proteins is vital to understanding the overall structure and function of the protein. The [Formula: see text]-barrel is one such secondary structure, commonly found in lipocalins and membrane proteins. In this article, we present a novel approach that utilizes genetic algorithms, kd-trees, and ray tracing to automatically detect and extract [Formula: see text]-barrels from cryo-EM density maps. This approach was tested on simulated and experimental density maps with zero, one, or multiple barrels in the density map. The results suggest that the proposed approach is capable of performing automatic detection of [Formula: see text]-barrels from medium resolution cryo-EM density maps.

Keywords: beta-barrel; cryo-electron microscopy; feature detection; genetic algorithm; ray tracing.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Amino Acid Motifs*
  • Animals
  • Cryoelectron Microscopy / methods*
  • Humans
  • Lipocalins / chemistry
  • Lipocalins / genetics
  • Sequence Analysis, Protein / methods*

Substances

  • Lipocalins