Evidence map›Paper›PMID 40753333›Full record

ArticleNature communications2025

Modeling protein conformational ensembles by guiding AlphaFold2 with Double Electron Electron Resonance (DEER) distance distributions.

Tianqi Wu, Richard A Stein, Te-Yu Kao, Benjamin Brown, Hassane S Mchaourab

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Multiple quantumScience advances · 2026
    Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. AI-Physics-Experiment Trinity for Integrated Protein Dynamics Modeling.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
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.

Tianqi WuCenter for Applied AI for Protein Dynamics, Vanderbilt University, Nashville, TN, USA.
Richard A SteinCenter for Applied AI for Protein Dynamics, Vanderbilt University, Nashville, TN, USA.ORCID http://orcid.org/0000-0002-0541-7150
Te-Yu KaoDepartment of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, USA.
Benjamin BrownCenter for Applied AI for Protein Dynamics, Vanderbilt University, Nashville, TN, USA.ORCID http://orcid.org/0000-0001-5296-087X
Hassane S MchaourabCenter for Applied AI for Protein Dynamics, Vanderbilt University, Nashville, TN, USA. hassane.mchaourab@vanderbilt.edu.ORCID http://orcid.org/0000-0002-5673-0980

Funding

Developing a computational platform for induced-fit and chemogenetic drug designDP1DA058349 · NIDA · VANDERBILT UNIVERSITY · PI Benjamin Patrick Brown · 2023 to 2026
$1.9M
Structural Dynamics of Active TransportersR35GM152382 · NIGMS · VANDERBILT UNIVERSITY · PI Hassane S Mchaourab · 2024 to 2026
$1.7M
NIDA NIH HHS DP1 DA058349NIGMS NIH HHS R35 GM152382
6 · The paper itself

Abstract

We describe a modified version of AlphaFold2 that incorporates experimental distance distributions into the network architecture for protein structure prediction. Harnessing the OpenFold platform, we fine-tune AlphaFold2 on structurally dissimilar proteins to explicitly model distance distributions between spin labels determined from Double Electron-Electron Resonance (DEER) spectroscopy. We benchmark the performance of the modified AlphaFold2, refer to as DEERFold, in switching the predicted conformations of a set of membrane transporters using experimental DEER distance distributions. Guided by sparse sets of simulated distance distributions, we showcase the generality of DEERFold in predicting conformational ensembles on a large benchmark set of water soluble and membrane proteins. We find that the intrinsic performance of AlphaFold2 substantially reduces the number of required distributions and the accuracy of their widths needed to drive conformational selection thereby increasing the experimental throughput. The blueprint of DEERFold can be generalized to other experimental methods where distance constraints can be represented by distributions.

Indexed as

ProteinsElectron Spin Resonance SpectroscopyMembrane ProteinsModels, MolecularProtein ConformationSpin LabelsMembrane ProteinsProteinsSpin Labels

Identifiers

PMID40753333
PMCPMC12318079

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.