Evidence map›Paper›PMID 36682003›Full record

ArticleBriefings in bioinformatics2023

Fast and automated protein-DNA/RNA macromolecular complex modeling from cryo-EM maps.

Andrew Nakamura, Hanze Meng, Minglei Zhao, Fengbin Wang, Jie Hou, Renzhi Cao, Dong Si

Abstract read
In one paragraph

Article in Briefings in bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

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  17. Automated model building and protein identification in cryo-EM maps.bioRxiv : the preprint server for biology · 2023
    Article
  18. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Andrew NakamuraDivision of Computing and Software Systems, University of Washington Bothell, Bothell, WA 98011, USA.ORCID 0000-0002-3253-5312
Hanze MengDepartment of Computer Science, Duke University, Durham, NC 27708, USA.
Minglei ZhaoDepartment of Biochemistry and Molecular Biology, The University of Chicago, Chicago, IL 60637, USA.
Fengbin WangDepartment of Biochemistry and Molecular Genetics, University of Alabama Birmingham, Heersink School of Medicine, Birmingham, AL 35233, USA.
Jie HouDepartment of Computer Science, Saint Louis University, Saint Louis, MO 63103, USA.
Renzhi CaoDepartment of Computer Science, Pacific Lutheran University, Tacoma, WA 98447, USA.ORCID 0000-0002-8345-343X
Dong SiDivision of Computing and Software Systems, University of Washington Bothell, Bothell, WA 98011, USA.ORCID 0000-0001-7039-2589

Funding

Structural and Functional Studies of Molecular Machines Involved in Chemical Modifications of MacromoleculesR35GM143052 · NIGMS · UNIVERSITY OF CHICAGO · PI ZHAO, MINGLEI · 2021 to 2025
$2.1M
NIGMS NIH HHS R35 GM143052
6 · The paper itself

Abstract

Cryo-electron microscopy (cryo-EM) allows a macromolecular structure such as protein-DNA/RNA complexes to be reconstructed in a three-dimensional coulomb potential map. The structural information of these macromolecular complexes forms the foundation for understanding the molecular mechanism including many human diseases. However, the model building of large macromolecular complexes is often difficult and time-consuming. We recently developed DeepTracer-2.0, an artificial-intelligence-based pipeline that can build amino acid and nucleic acid backbones from a single cryo-EM map, and even predict the best-fitting residues according to the density of side chains. The experiments showed improved accuracy and efficiency when benchmarking the performance on independent experimental maps of protein-DNA/RNA complexes and demonstrated the promising future of macromolecular modeling from cryo-EM maps. Our method and pipeline could benefit researchers worldwide who work in molecular biomedicine and drug discovery, and substantially increase the throughput of the cryo-EM model building. The pipeline has been integrated into the web portal https://deeptracer.uw.edu/.

Indexed as

DNARNACryoelectron MicroscopyHumansMacromolecular SubstancesModels, MolecularProtein ConformationDNAMacromolecular SubstancesRNAartificial intelligencecryo-EMmachine learningmacromolecular modelingprotein-DNA/RNA

Identifiers

PMID36682003
PMCPMC10399284

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.