DeepTracer for fast de novo cryo-EM protein structure modeling and special studies on CoV-related complexes.
DeepTracer for fast de novo cryo-EM protein structure modeling and special studies on CoV-related complexes.
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DOI：
10.1073/pnas.2017525118
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发表时间：
2021-01-12
影响因子：
11.1
通讯作者：
Si D
中科院分区：
文献类型：
--
作者：
Pfab J;Phan NM;Si D
低温电子显微镜（cryo-EM）是2017年诺贝尔奖获得者，它提供了大分子的直接3D图谱，并解释了蛋白质复合物（如SARS-CoV-2病毒蛋白和人类细胞受体）的形状和相互作用。这种理解可以与使用其他技术收集的详细结构信息相结合，以形成疾病过程建模和治疗药物设计的基础。然而，从头计算蛋白质复合物结构建模仍然是一个具有挑战性的问题。在这里，我们介绍了DeepTracer，这是一种完全自动化和强大的工具，它仅基于其cryo-EM图和氨基酸序列来确定蛋白质复合物的全原子结构，与以前的方法相比，具有更高的准确性和效率。我们还提供全球访问的网络服务。有关蛋白质复合物的大分子结构和相关的细胞和分子机制的信息可以帮助寻找疫苗和药物开发过程。为了获得这些结构信息，我们提出了DeepTracer，这是一种基于深度学习的全自动方法，用于从高分辨率冷冻电子显微镜（cryo-EM）图谱中快速从头确定多链蛋白质复合物结构。我们将DeepTracer应用于先前发表的一组476个原始实验cryo-EM图，并将结果与当前最先进的方法进行了比较。使用DeepTracer的残留物覆盖率增加了30%以上，并且rmsd值从1.29 μ m提高到1.18 μ m。此外，我们将DeepTracer应用于一组62个冠状病毒相关的cryo-EM图，其中10个在EMDataResource中没有沉积结构。我们观察到与沉积结构的平均残留物匹配为84%，平均rmsd为0.93 μ m。使用相关方法进行的其他测试进一步证明了DeepTracer在结构建模方面具有竞争力的准确性和效率。DeepTracer允许异常快速的计算，使其能够在2小时内追踪350条链中的约60，000个残基。该网络服务可在https://deeptracer.uw.edu上全球访问。
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. 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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影响因子：
2.9
作者：
Krivov, Georgii G.;Shapovalov, Maxim V.;Dunbrack, Roland L., Jr.
通讯作者：
Dunbrack, Roland L., Jr.
影响因子：
48
作者：
Frenz B;Walls AC;Egelman EH;Veesler D;DiMaio F
通讯作者：
DiMaio F
影响因子：
2.9
作者：
Keedy, Daniel A.;Williams, Christopher J.;Richardson, Jane S.
通讯作者：
Richardson, Jane S.
DOI：
10.1107/s2059798318006551
发表时间：
2018-06-01
期刊：
Acta crystallographica. Section D, Structural biology
影响因子：
--
作者：
Afonine PV;Poon BK;Read RJ;Sobolev OV;Terwilliger TC;Urzhumtsev A;Adams PD
通讯作者：
Adams PD
影响因子：
16.6
作者：
Terashi G;Kihara D
通讯作者：
Kihara D