Full-length de novo protein structure determination from cryo-EM maps using deep learning

Jiahua He, Sheng-You Huang

Abstract: Advances in microscopy instruments and image processing algorithms have led to an increasing number of Cryo-electron microscopy (cryo-EM) maps. However, building accurate models for the EM maps at 3–5 Å resolution remains a challenging and time-consuming process. With the rapid growth of deposited EM maps, there is an increasing gap between the maps and reconstructed/modeled three-dimensional (3D) structures. Therefore, automatic reconstruction of atomic-accuracy full-atom structures from EM maps is pressingly needed.