DeepTracer for fast de novo cryo-EM protein structure modeling and special studies on CoV-related complexes

Jonas Pfab; Nhut Minh Phan; Dong Si

doi:10.1073/pnas.2017525118

New Research In

Edited by Eva Nogales, University of California, Berkeley, CA, and approved December 1, 2020 (received for review August 18, 2020)

Significance

Electron cryomicroscopy (cryo-EM), a 2017 Nobel prize-awarded technology, provides direct 3D maps of macromolecules and explains the shape and interactions of protein complexes such as SARS-CoV-2 viral proteins and human cell receptors. This understanding can be combined with detailed structural information gathered using other technologies to form the basis for modeling course of diseases and for designing therapeutic drugs. However, ab initio modeling of protein complex structure remains a challenging problem. Here, we present DeepTracer, a fully automated and robust tool that determines the all-atom structure of a protein complex based solely on its cryo-EM map and amino acid sequence, with improved accuracy and efficiency compared to previous methods. We also provide a web service for global access.

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.

Footnotes

↵¹To whom correspondence may be addressed. Email: dongsi{at}uw.edu.

Author contributions: D.S. designed research; J.P., N.M.P., and D.S. performed research; J.P., N.M.P., and D.S. contributed new reagents/analytic tools; J.P., N.M.P., and D.S. analyzed data; and J.P., N.M.P., and D.S. wrote the paper.
The authors declare no competing interest.
This article is a PNAS Direct Submission.
This article contains supporting information online at https://www.pnas.org/lookup/suppl/doi:10.1073/pnas.2017525118/-/DCSupplemental.

Data Availability.

Application programming interfaces have been deposited on the DeepTracer website (https://deeptracer.uw.edu). All study data are included in the article and SI Appendix.

This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).

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