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DeepTracer for fast de novo cryo-EM protein structure modeling and special studies on CoV-related complexes.
Pfab, Jonas; Phan, Nhut Minh; Si, Dong.
  • Pfab J; Division of Computing and Software Systems, University of Washington Bothell, Bothell, WA 98011.
  • Phan NM; Division of Computing and Software Systems, University of Washington Bothell, Bothell, WA 98011.
  • Si D; Division of Computing and Software Systems, University of Washington Bothell, Bothell, WA 98011 dongsi@uw.edu.
Proc Natl Acad Sci U S A ; 118(2)2021 01 12.
Article in English | MEDLINE | ID: covidwho-1066041
ABSTRACT
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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Viral Proteins / Molecular Structure / Deep Learning / SARS-CoV-2 / Models, Structural Topics: Vaccines Language: English Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Viral Proteins / Molecular Structure / Deep Learning / SARS-CoV-2 / Models, Structural Topics: Vaccines Language: English Year: 2021 Document Type: Article