气候变化领域集成服务门户(CCPortal): DeepTracer for fast de novo cryo-EM protein structure modeling and special studies on cov-related complexes

CCPortal

DOI	10.1073/pnas.2017525118
	DeepTracer for fast de novo cryo-EM protein structure modeling and special studies on cov-related complexes
	Pfab J.; Phan N.M.; Si D.
发表日期	2021
ISSN	00278424
卷号	118 期号:2
英文摘要	Information about macromolecular structure of protein complexes and related cellular and molecular mechanisms can assist the search for vaccines and drug development processes. To obtain such structural information, we present DeepTracer, a fully automated deep learning-based method for fast de novo multichain protein complex structure determination from high-resolution cryoelectron microscopy (cryo-EM) maps. We applied DeepTracer on a previously published set of 476 raw experimental cryo-EM maps and compared the results with a current state of the art method. The residue coverage increased by over 30% using DeepTracer, and the rmsd value improved from 1.29 Å to 1.18 Å. Additionally, we applied DeepTracer on a set of 62 coronavirus-related cryo-EM maps, among them 10 with no deposited structure available in EMDataResource. We observed an average residue match of 84% with the deposited structures and an average rmsd of 0.93 Å. Additional tests with related methods further exemplify DeepTracer’s competitive accuracy and efficiency of structure modeling. DeepTracer allows for exceptionally fast computations, making it possible to trace around 60,000 residues in 350 chains within only 2 h. The web service is globally accessible at https://deeptracer.uw.edu. © 2021 National Academy of Sciences. All rights reserved.
英文关键词	Complex; Cryo-EM; De novo; Modeling; Structure
语种	英语
scopus关键词	viral protein; viral protein; amino acid sequence; Article; automation; client server application; computer analysis; controlled study; cryoelectron microscopy; deep learning; EMDataResource; experimental study; intermethod comparison; measurement accuracy; nonhuman; Phenix Benchmark Test; priority journal; protein database; protein structure; sequence homology; Severe acute respiratory syndrome coronavirus 2; chemical structure; chemistry; comparative study; cryoelectron microscopy; structural model; ultrastructure; Cryoelectron Microscopy; Deep Learning; Models, Structural; Molecular Structure; SARS-CoV-2; Viral Proteins
来源期刊	Proceedings of the National Academy of Sciences of the United States of America
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/181087
作者单位	Division of Computing and Software Systems, University of Washington Bothell, Bothell, WA 98011, United States
推荐引用方式 GB/T 7714	Pfab J.,Phan N.M.,Si D.. DeepTracer for fast de novo cryo-EM protein structure modeling and special studies on cov-related complexes[J],2021,118(2).
APA	Pfab J.,Phan N.M.,&Si D..(2021).DeepTracer for fast de novo cryo-EM protein structure modeling and special studies on cov-related complexes.Proceedings of the National Academy of Sciences of the United States of America,118(2).
MLA	Pfab J.,et al."DeepTracer for fast de novo cryo-EM protein structure modeling and special studies on cov-related complexes".Proceedings of the National Academy of Sciences of the United States of America 118.2(2021).