Evidence map›Paper›PMID 40886049›Full record

ArticleBiophysical journal2025

AlphaFold2 captures conformational transitions in the voltage-gated channel superfamily.

Elaine Tao, Ben Corry

Abstract read
In one paragraph

Article in Biophysical journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

2 authors.

Elaine TaoDivision of Biomedical Science and Biochemistry, Research School of Biology, Australian National University, Canberra, ACT, Australia. Electronic address: elaine.tao@anu.edu.au.
Ben CorryDivision of Biomedical Science and Biochemistry, Research School of Biology, Australian National University, Canberra, ACT, Australia. Electronic address: ben.corry@anu.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Voltage-gated cation channels are crucial membrane proteins responsible for the electrical activity in excitable nerve, muscle, and cardiac tissue. These channels respond to changes in the membrane potential via conformational changes in their voltage-sensing domains (VSDs) that lead to the opening and closing of the ion conduction pore. Since alternative states of the VSDs are difficult to capture via experimental methods, we investigated the application of AlphaFold2 and subsampling of its multiple sequence alignment input to computationally predict structures across a range of intermediate and endpoint states. By generating 600 models for 32 members of the voltage-gated cation channel superfamily, we show that AlphaFold2 is capable of predicting diverse structures of the VSDs that could represent activated, deactivated, and intermediate conformations with more diversity seen for some VSD families compared with others. Modeling the full sequence of pseudo-tetrameric channels also produced a range of heterogeneous states in the pore and intracellular regions representative of local conformational changes and key secondary structural transitions. However, we observe that the global conformational coupling is limited across models, as different functional domains adopt physiologically incompatible states. Although short molecular dynamics simulations of a subset of the models suggest they are structurally plausible conformations, there are some incongruities between certain generated models and resolved cryo-EM structures. Further validation is required to confirm their structural and functional relevance.

Indexed as

Models, MolecularAmino Acid SequenceMolecular Dynamics SimulationProtein ConformationProtein Domains

Identifiers

PMID40886049
PMCPMC12709252

What OpenQuestion holds

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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.