Evidence map›Paper›PMID 33957123›Full record

ReviewThe Journal of biological chemistry

From integrative structural biology to cell biology.

Andrej Sali

Abstract readHistorical ArticleReview
In one paragraph

Review in The Journal of biological chemistry. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.

0numbers the graph read from it
0cells of the map it votes in
55citing 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

55 citing papers in PubMed.

  1. Evaluation of methods for AlphaFold-based integrative modeling.bioRxiv : the preprint server for biology · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Ligand-driven modulation of chaperone-cochaperone networks shapes proteostasis outcomes.Protein science : a publication of the Protein Society · 2026
    Article
  8. Cloneable contrast across all biological length scales.Journal of structural biology · 2026
    Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Integrative mapping reveals molecular features underlying the mechanism of nucleocytoplasmic transport.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  14. Article
  15. Recognizing amino acid sidechains in a medium-resolution cryo-electron density map.Protein science : a publication of the Protein Society · 2025
    Article
  16. Article
  17. Article
  18. Article
  19. Tutorial on integrative spatiotemporal modeling by integrative modeling platform.Protein science : a publication of the Protein Society · 2025
    Article
  20. Integrative spatiotemporal modeling of biomolecular processes: Application to the assembly of the nuclear pore complex.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
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

1 author.

Andrej SaliResearch Collaboratory for Structural Bioinformatics Protein Data Bank, the Department of Bioengineering and Therapeutic Sciences, the Quantitative Biosciences Institute (QBI), and the Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California, USA. Electronic address: sali@salilab.org.

Funding

VIRAL DEGENERATIVE DEMENTING DISEASE IN AGING (SUPP)P01AG002132 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI PRUSINER, STANLEY B · 1985 to 2024
$51.7M
RESEARCH PROJECT 2U19AI135990 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Nevan J Krogan · 2018 to 2026
$21.4M
PDB MANAGEMENT BY THE RESEARCH COLLABORATORY FOR STRUCTURAL BIOINFORMATICSR01GM133198 · NIGMS · RUTGERS, THE STATE UNIV OF N.J. · PI BURLEY, STEPHEN K · 2019 to 2023
$19.3M
TR&D Project 4. The Imaging Stage: Multiscale Spatiotemporal Modeling of Macromolecular Systems in Cellular NeighborhoodsP41GM109824 · NIGMS · ROCKEFELLER UNIVERSITY · PI ROUT, MICHAEL P · 2014 to 2023
$18.8M
X-ray Screening and Rapid Structure DeterminationP50AI150476 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KROGAN, NEVAN J · 2019 to 2021
$14.4M
Protein/Structure CoreP01GM118303 · NIGMS · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI GERLT, JOHN A · 2016 to 2020
$11.4M
IMP: Software for Hybrid Determination of Macromolecular Assembly StructuresR01GM083960 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI SALI, ANDREJ · 2008 to 2024
$5.2M
Mapping the 3D Genome LandscapeU54DK107981 · NIDDK · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ALBER, FRANK, CHEN, LIN · 2015 to 2019
$4.2M
NIAID NIH HHS P50 AI150476NIAID NIH HHS U19 AI135990NIA NIH HHS P01 AG002132NIDDK NIH HHS U54 DK107981NIGMS NIH HHS P01 GM118303NIGMS NIH HHS P41 GM109824NIGMS NIH HHS R01 GM083960NIGMS NIH HHS R01 GM133198
6 · The paper itself

Abstract

Integrative modeling is an increasingly important tool in structural biology, providing structures by combining data from varied experimental methods and prior information. As a result, molecular architectures of large, heterogeneous, and dynamic systems, such as the ∼52-MDa Nuclear Pore Complex, can be mapped with useful accuracy, precision, and completeness. Key challenges in improving integrative modeling include expanding model representations, increasing the variety of input data and prior information, quantifying a match between input information and a model in a Bayesian fashion, inventing more efficient structural sampling, as well as developing better model validation, analysis, and visualization. In addition, two community-level challenges in integrative modeling are being addressed under the auspices of the Worldwide Protein Data Bank (wwPDB). First, the impact of integrative structures is maximized by PDB-Development, a prototype wwPDB repository for archiving, validating, visualizing, and disseminating integrative structures. Second, the scope of structural biology is expanded by linking the wwPDB resource for integrative structures with archives of data that have not been generally used for structure determination but are increasingly important for computing integrative structures, such as data from various types of mass spectrometry, spectroscopy, optical microscopy, proteomics, and genetics. To address the largest of modeling problems, a type of integrative modeling called metamodeling is being developed; metamodeling combines different types of input models as opposed to different types of data to compute an output model. Collectively, these developments will facilitate the structural biology mindset in cell biology and underpin spatiotemporal mapping of the entire cell.

Indexed as

Models, MolecularAnimalsCell BiologyDatabases, ProteinHistory, 20th CenturyHistory, 21st CenturyHumansMolecular Biologycell biologyintegrative modelingintegrative structural biologyintegrative structure modelingstructural biology

Identifiers

PMID33957123
PMCPMC8203844

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.