Evidence map›Paper›PMID 31653450›Full record

ArticleBiophysical journal2019

Simulation of Gating Currents of the Shaker K Channel Using a Brownian Model of the Voltage Sensor.

Luigi Catacuzzeno, Fabio Franciolini

Abstract read
In one paragraph

Article in Biophysical journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Fifty years of gating currents and channel gating.The Journal of general physiology · 2023
    Review
  2. Article
  3. Setting Boundaries for Statistical Mechanics.Molecules (Basel, Switzerland) · 2022
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. 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

2 authors.

Luigi CatacuzzenoDepartment of Chemistry, Biology, and Biotechnology, University of Perugia, Perugia, Italy. Electronic address: luigi.catacuzzeno@unipg.it.
Fabio FrancioliniDepartment of Chemistry, Biology, and Biotechnology, University of Perugia, Perugia, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The physical mechanism underlying the voltage-dependent gating of K channels is usually addressed theoretically using molecular dynamics simulations. However, besides being computationally very expensive, this approach is presently unable to fully predict the behavior of fundamental variables of channel gating such as the macroscopic gating current, and hence, it is presently unable to validate the model. To fill this gap, here we propose a voltage-gating model that treats the S4 segment as a Brownian particle moving through a gating channel pore and adjacent internal and external vestibules. In our model, charges on the S4 segment are screened by charged residues localized on neighboring segments of the channel protein and by ions present in the vestibules, whose dynamics are assessed using a flux conservation equation. The electrostatic voltage spatial profile is consistently assessed by applying the Poisson equation to all the charges present in the system. The treatment of the S4 segment as a Brownian particle allows description of the dynamics of a single S4 segment using the Langevin stochastic differential equation or the behavior of a population of S4 segments-useful for assessing the macroscopic gating current-using the Fokker-Planck equation. The proposed model confirms the gating charge transfer hypothesis with the movement of the S4 segment among five different stable positions where the gating charges interact in succession with the negatively charged residues on the channel protein. This behavior produces macroscopic gating currents quite similar to those experimentally found.

Indexed as

Computer SimulationIon Channel GatingModels, BiologicalElectrolytesIonsKineticsProtein DomainsShaker Superfamily of Potassium ChannelsStructural Homology, ProteinTime FactorsElectrolytesIonsShaker Superfamily of Potassium Channels

Identifiers

PMID31653450
PMCPMC7018989

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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.