Evidence map›Paper›PMID 35857767›Full record

ArticlePLoS computational biology2022

To what extent naringenin binding and membrane depolarization shape mitoBK channel gating-A machine learning approach.

Monika Richter-Laskowska, Paulina Trybek, Piotr Bednarczyk, Agata Wawrzkiewicz-Jałowiecka

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 46% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Machine Learning Methods for the Analysis of the Patch-Clamp Signals.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  2. Article
  3. Flavonoids as Modulators of Potassium Channels.International journal of molecular sciences · 2023
    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

4 authors at 4 institutions in 1 country.

Monika Richter-LaskowskaŁukasiewicz Research Network-Institute of Medical Technology and Equipment, Zabrze, Poland.ORCID 0000-0002-6591-5944
Paulina TrybekFaculty of Science and Technology, University of Silesia in Katowice, Chorzów, Poland.ORCID 0000-0003-4756-9993
Piotr BednarczykDepartment of Physics and Biophysics, Institute of Biology, Warsaw University of Life Sciences-SGGW, Warszawa, Poland.ORCID 0000-0002-7125-0715
Agata Wawrzkiewicz-JałowieckaDepartment of Physical Chemistry and Technology of Polymers, Silesian University of Technology, Gliwice, Poland.ORCID 0000-0001-6885-3956
Institute of Medical Technology and Equipment · PLSilesian University of Technology · PLUniversity of Silesia in Katowice · PLWarsaw University of Life Sciences · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The large conductance voltage- and Ca2+-activated K+ channels from the inner mitochondrial membrane (mitoBK) are modulated by a number of factors. Among them flavanones, including naringenin (Nar), arise as a promising group of mitoBK channel regulators from a pharmacological point of view. It is well known that in the presence of Nar the open state probability (pop) of mitoBK channels significantly increases. Nevertheless, the molecular mechanism of the mitoBK-Nar interactions remains still unrevealed. It is also not known whether the effects of naringenin administration on conformational dynamics can resemble those which are exerted by the other channel-activating stimuli. In aim to answer this question, we examine whether the dwell-time series of mitoBK channels which were obtained at different voltages and Nar concentrations (yet allowing to reach comparable pops) are discernible by means of artificial intelligence methods, including k-NN and shapelet learning. The obtained results suggest that the structural complexity of the gating dynamics is shaped both by the interaction of channel gate with the voltage sensor (VSD) and the Nar-binding site. For a majority of data one can observe stimulus-specific patterns of channel gating. Shapelet algorithm allows to obtain better prediction accuracy in most cases. Probably, because it takes into account the complexity of local features of a given signal. About 30% of the analyzed time series do not sufficiently differ to unambiguously distinguish them from each other, which can be interpreted in terms of the existence of the common features of mitoBK channel gating regardless of the type of activating stimulus. There exist long-range mutual interactions between VSD and the Nar-coordination site that are responsible for higher levels of Nar-activation (Δpop) at deeply depolarized membranes. These intra-sensor interactions are anticipated to have an allosteric nature.

Indexed as

FlavanonesPotassium Channels, Calcium-ActivatedArtificial IntelligenceCalciumMachine LearningCalciumFlavanonesnaringeninPotassium Channels, Calcium-Activated

Identifiers

PMID35857767
PMCPMC9342765
OpenAlexW4286007870

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.