Evidence map›Paper›PMID 38513658›Full record

ArticleStructure (London, England : 1993)2024

A suite of designed protein cages using machine learning and protein fragment-based protocols.

Kyle Meador, Roger Castells-Graells, Roman Aguirre, Michael R Sawaya, Mark A Arbing, Trent Sherman, Chethaka Senarathne, Todd O Yeates

Abstract read
In one paragraph

Article in Structure (London, England : 1993), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Review
  2. Article
  3. Unraveling the maturation pathway of a eukaryotic virus through cryo-EM.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  4. Review
  5. Protein engineering: status report.Protein engineering, design & selection : PEDS · 2026
    Review
  6. Article
  7. Review
  8. Review
  9. From sequence to scaffold: Computational design of protein nanoparticle vaccines from AlphaFold2-predicted building blocks.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Kyle MeadorDepartment of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095, USA.
Roger Castells-GraellsUCLA-DOE Institute for Genomics and Proteomics, Los Angeles, CA 90095, USA.
Roman AguirreDepartment of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095, USA.
Michael R SawayaUCLA-DOE Institute for Genomics and Proteomics, Los Angeles, CA 90095, USA.
Mark A ArbingUCLA-DOE Institute for Genomics and Proteomics, Los Angeles, CA 90095, USA.
Trent ShermanDepartment of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095, USA.
Chethaka SenarathneDepartment of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095, USA.
Todd O YeatesDepartment of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095, USA; UCLA-DOE Institute for Genomics and Proteomics, Los Angeles, CA 90095, USA. Electronic address: yeates@mbi.ucla.edu.

Funding

Pacific Northwest Center for Cryo-EM - Screening supplementU24GM129547 · NIGMS · OREGON HEALTH & SCIENCE UNIVERSITY · PI EVANS, JAMES E, GOUAUX, JAMES E · 2018 to 2023
$54.8M
The Stanford-SLAC CryoEM Center supplementU24GM129541 · NIGMS · STANFORD UNIVERSITY · PI CHIU, WAH, HEDMAN, BRITT · 2018 to 2023
$54.8M
A Synchrotron Radiation Structural Biology ResourcesP30GM133894 · NIGMS · STANFORD UNIVERSITY · PI Aina E. Cohen, KEITH O HODGSON · 2020 to 2026
$43.3M
User Training and OutreachP30GM124165 · NIGMS · CORNELL UNIVERSITY · PI STEVEN E EALICK · 2018 to 2026
$34.2M
CHEMISTRY BIOLOGY INTERFACE TRAINING PROGRAMT32GM008496 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI MAYNARD, HEATHER D · 1993 to 2019
$6.3M
Designing Novel Protein Assemblies as Rigid Symmetric Scaffolds for Cryo-EM ImagingR01GM129854 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI YEATES, TODD O · 2019 to 2022
$1.2M
PILATUS3 X 1M X-ray detectorS10OD021512 · OD · STANFORD UNIVERSITY · PI WEIS, WILLIAM I · 2016 to 2016
$550k
NIGMS NIH HHS P30 GM124165NIGMS NIH HHS P30 GM133894NIGMS NIH HHS R01 GM129854NIGMS NIH HHS T32 GM008496NIGMS NIH HHS U24 GM129541NIGMS NIH HHS U24 GM129547NIH HHS S10 OD021512
6 · The paper itself

Abstract

Designed protein cages and related materials provide unique opportunities for applications in biotechnology and medicine, but their creation remains challenging. Here, we apply computational approaches to design a suite of tetrahedrally symmetric, self-assembling protein cages. For the generation of docked conformations, we emphasize a protein fragment-based approach, while for sequence design of the de novo interface, a comparison of knowledge-based and machine learning protocols highlights the power and increased experimental success achieved using ProteinMPNN. An analysis of design outcomes provides insights for improving interface design protocols, including prioritizing fragment-based motifs, balancing interface hydrophobicity and polarity, and identifying preferred polar contact patterns. In all, we report five structures for seven protein cages, along with two structures of intermediate assemblies, with the highest resolution reaching 2.0 Å using cryo-EM. This set of designed cages adds substantially to the body of available protein nanoparticles, and to methodologies for their creation.

Indexed as

Machine LearningProteinsCryoelectron MicroscopyHydrophobic and Hydrophilic InteractionsModels, MolecularMolecular Docking SimulationProtein ConformationProteinscryoEMde novo interface designmachine learningprotein cagesprotein-protein dockingself-assemblysymmetryX-ray crystallography

Identifiers

PMID38513658
PMCPMC11162342

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.