Evidence map›Paper›PMID 31863286›Full record

ReviewPflugers Archiv : European journal of physiology2020

Voltage-dependent gating in K channels: experimental results and quantitative models.

Luigi Catacuzzeno, Luigi Sforna, Fabio Franciolini

Abstract readReview
PubMed Publisher
In one paragraph

Review in Pflugers Archiv : European journal of physiology, 2020. 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
1.2field-weighted citation impact, top 21% of its field
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, 24 citations in OpenAlex.

  1. Hysteretic Conductance in Ion Channel Gating.Entropy (Basel, Switzerland) · 2026
    Review
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  6. Fifty years of gating currents and channel gating.The Journal of general physiology · 2023
    Review
  7. Article
  8. Article
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  10. A Multi-Scale Approach to Model KFrontiers in molecular biosciences · 2022
    Article
  11. Article
  12. Article
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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

3 authors at 1 institution in 1 country.

Luigi CatacuzzenoDepartment of Chemistry, Biology and Biotechnology, University of Perugia, Via Elce di Sotto 8, 06123, Perugia, Italy. luigi.catacuzzeno@unipg.it.ORCID 0000-0002-4723-0650
Luigi SfornaDepartment of Chemistry, Biology and Biotechnology, University of Perugia, Via Elce di Sotto 8, 06123, Perugia, Italy.
Fabio FrancioliniDepartment of Chemistry, Biology and Biotechnology, University of Perugia, Via Elce di Sotto 8, 06123, Perugia, Italy. fabio.franciolini@unipg.it.
University of Perugia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Voltage-dependent K channels open and close in response to voltage changes across the cell membrane. This voltage dependence was postulated to depend on the presence of charged particles moving through the membrane in response to voltage changes. Recording of gating currents originating from the movement of these particles fully confirmed this hypothesis, and gave substantial experimental clues useful for the detailed understanding of the process. In the absence of structural information, the voltage-dependent gating was initially investigated using discrete Markov models, an approach only capable of providing a kinetic and thermodynamic comprehension of the process. The elucidation of the crystal structure of the first voltage-dependent channel brought in a dramatic change of pace in the understanding of channel gating, and in modeling the underlying processes. It was now possible to construct quantitative models using molecular dynamics, where all the interactions of each individual atom with the surroundings were taken into account, and its motion predicted by Newton's laws. Unfortunately, this modeling is computationally very demanding, and in spite of the advances in simulation procedures and computer technology, it is still limited in its predictive ability. To overcome these limitations, several groups have developed more macroscopic voltage gating models. Their approaches understandably require a number of approximations, which must however be physically well justified. One of these models, based on the description of the voltage sensor as a Brownian particle, that we have recently developed, is able to simultaneously describe the behavior of a single voltage sensor and to predict the macroscopic gating current originating from a population of sensors. The basics of this model are here described, and a typical application using the Kv1.2/2.1 chimera channel structure is also presented.

Indexed as

Ion Channel GatingMolecular Dynamics SimulationAnimalsHumansMembrane PotentialsPotassium Channels, Voltage-GatedProtein DomainsPotassium Channels, Voltage-GatedGating currentsMathematical modelsVoltage-dependent gatingVoltage-gated potassium channels

Identifiers

PMID31863286
OpenAlexW2996367044

What OpenQuestion holds

Textmetadata
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.