RT Journal Article
SR Electronic
T1 Progressive and accurate assembly of multi-domain protein structures from cryo-EM density maps
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.10.15.340455
DO 10.1101/2020.10.15.340455
A1 Xiaogen Zhou
A1 Yang Li
A1 Chengxin Zhang
A1 Wei Zheng
A1 Guijun Zhang
A1 Yang Zhang
YR 2020
UL http://biorxiv.org/content/early/2020/10/16/2020.10.15.340455.abstract
AB Progress in cryo-electron microscopy (cryo-EM) has provided the potential for large-size protein structure determination. However, the solution rate for multi-domain proteins remains low due to the difficulty in modeling inter-domain orientations. We developed DEMO-EM, an automatic method to assemble multi-domain structures from cryo-EM maps through a progressive structural refinement procedure combining rigid-body domain fitting and flexible assembly simulations with deep neural network inter-domain distance profiles. The method was tested on a large-scale benchmark set of proteins containing up to twelve continuous and discontinuous domains with medium-to-low-resolution density maps, where DEMO-EM produced models with correct inter-domain orientations (TM-score >0.5) for 98% of cases and significantly outperformed the state-of-the-art methods. DEMO-EM was applied to SARS-Cov-2 coronavirus genome and generated models with average TM-score/RMSD of 0.97/1.4Å to the deposited structures. These results demonstrated an efficient pipeline that enables automated and reliable large-scale multi-domain protein structure modeling with atomic-level accuracy from cryo-EM maps.Competing Interest StatementThe authors have declared no competing interest.