Information about macromolecular structure of protein complexes such as SARS-CoV-2, 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 automatic deep learning-based method for fast de novo multi-chain protein complex structure determination from high-resolution cryo-electron microscopy (cryo-EM) density maps. We applied DeepTracer on a previously published set of 476 raw experimental density 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 1.29Å to 1.18Å. Additionally, we applied DeepTracer on a set of 62 coronavirus-related density 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 0.93Å. 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 two hours. The web service is globally accessible at https://deeptracer.uw.edu.
1This paper describes outcomes of the 2019 Cryo-EM Map-based Model Metrics Challenge 2 sponsored by EMDataResource (www.emdataresource.org). The goals of this challenge were (1) 3 to assess the quality of models that can be produced using current modeling software, (2) to 4 check the reproducibility of modeling results from different software developers and users, and 5(3) compare the performance of current metrics used for evaluation of models. The focus was on 6 near-atomic resolution maps with an innovative twist: three of four target maps formed a resolution 7 series (1.8 to 3.1 Å) from the same specimen and imaging experiment. Tools developed in 8 previous challenges were expanded for managing, visualizing and analyzing the 63 submitted 9 coordinate models, and several novel metrics were introduced. The results permit specific 10 recommendations to be made about validating near-atomic cryo-EM structures both in the context 11 of individual laboratory experiments and holdings of structure data archives such as the Protein 12 Data Bank. Our findings demonstrate the relatively high accuracy and reproducibility of cryo-EM 13 models derived from these benchmark maps by 13 participating teams, representing both widely 14 used and novel modeling approaches. We also evaluate the pros and cons of the commonly used 15 metrics to assess model quality and recommend the adoption of multiple scoring parameters to 16 provide full and objective annotation and assessment of the model, reflective of the observed 17 density in the cryo-EM map. 18
The N-end rule pathway was one of the first ubiquitin (Ub)-dependent degradation pathways to be identified. Ubr1, a single-chain E3 ligase, targets proteins bearing a destabilizing residue at the N-terminus (N-degron) for rapid K48-linked ubiquitination and proteasome-dependent degradation. How Ubr1 catalyses the initiation of ubiquitination on the substrate and elongation of the Ub chain in a linkage-specific manner through a single E2 ubiquitin-conjugating enzyme (Ubc2) remains unknown. Here, we report the cryo-electron microscopy structures of two complexes representing the initiation and elongation intermediates of Ubr1 captured using chemical approaches. In these two structures, Ubr1 adopts different conformations to facilitate the transfer of Ub from Ubc2 to either an N-degron peptide or a monoubiquitinated degron. These structures not only reveal the architecture of the Ubr1 complex but also provide mechanistic insights into the initiation and elongation steps of ubiquitination catalyzed by Ubr1.
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