Evidence map›Paper›PMID 36258699›Full record

ArticleIEEE transactions on computational imaging2022

Recovery of Conformational Continuum From Single-Particle Cryo-EM Images: Optimization of ManifoldEM Informed by Ground Truth.

Evan Seitz, Francisco Acosta-Reyes, Suvrajit Maji, Peter Schwander, Joachim Frank

Abstract read
In one paragraph

Article in IEEE transactions on computational imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
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  3. Molecular Insights into Macromolecules Structure, Function, and Regulation.International journal of molecular sciences · 2024
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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

5 authors.

Evan SeitzDepartment of Biochemistry and Molecular Biophysics, Columbia University Medical Center, New York, NY 10032 USA, and also with the Department of Biological Sciences, Columbia University, New York, NY 10027 USA.ORCID 0000-0001-6844-2444
Francisco Acosta-ReyesDepartment of Biochemistry and Molecular Biophysics, Columbia University Medical Center, New York, NY 10032 USA.ORCID 0000-0001-8524-1484
Suvrajit MajiDepartment of Biochemistry and Molecular Biophysics, Columbia University Medical Center, New York, NY 10032 USA.ORCID 0000-0001-5547-1975
Peter SchwanderDepartment of Physics, University of Wisconsin-Milwaukee, Milwaukee, WI 53211 USA.ORCID 0000-0003-2350-8838
Joachim FrankDepartment of Biochemistry and Molecular Biophysics, Columbia University Medical Center, New York, NY 10032 USA, and also with the Department of Biological Sciences, Columbia University, New York, NY 10027 USA.ORCID 0000-0001-5449-6943

Funding

STRUCTURE ANALYSIS OF MACROMOLECULAR ASSEMBLIESR01GM029169 · NIGMS · WADSWORTH CENTER · PI FRANK, JOACHIM · 1985 to 2019
$6.1M
Time-resolved Cryo-EM of Short-lived States in Eukaryotic TranslationR01GM055440 · NIGMS · WADSWORTH CENTER · PI FRANK, JOACHIM · 1997 to 2020
$5.1M
Structural Studies of Macromolecular Assemblies Using Cryo-EMR35GM139453 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI FRANK, JOACHIM · 2021 to 2025
$3.9M
NIGMS NIH HHS R01 GM029169NIGMS NIH HHS R01 GM055440NIGMS NIH HHS R35 GM139453
6 · The paper itself

Abstract

This work is based on the manifold-embedding approach to study biological molecules exhibiting continuous conformational changes. Previous work established a method-now termed ManifoldEM-capable of reconstructing 3D movies and accompanying free-energy landscapes from single-particle cryo-EM images of macromolecules exercising multiple conformational degrees of freedom. While ManifoldEM has proven its viability in several experimental studies, critical limitations and uncertainties have been found throughout its extended development and use. Guided by insights from studies with cryo-EM ground-truth data, simulated from atomic structures undergoing conformational changes, we have built a novel framework, ESPER, able to retrieve the free-energy landscape and respective 3D Coulomb potential maps for all states simulated. As shown by a direct comparison of ground truth vs. recovered maps, and analysis of experimental data from the 80S ribosome and ryanodine receptor, ESPER offers substantial improvements relative to the previous work.

Indexed as

Biomoleculesfree-energy landscapekernel methodsmanifold embeddingquantitative biologysingle particle cryogenic microscopy (cryo-EM)spectral geometryunsupervised machine learning

Identifiers

PMID36258699
PMCPMC9575687

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Registered trials

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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.