4.6 Article

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

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PLOS COMPUTATIONAL BIOLOGY
卷 18, 期 7, 页码 -

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PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pcbi.1010315

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资金

  1. Lukasiewicz Research Network-Institute of Medical Technology and Equipment as part of Ministry of Education and Science
  2. Silesian University of Technology [04/040/BKM22/0216]
  3. National Science Center of Poland [2016/21/B/NZ1/02769]
  4. [2018/29/B/ST3/01892]

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Research demonstrates that flavanones, including naringenin, show promise as regulators of the large conductance voltage- and Ca2+- activated K+ channels on the inner mitochondrial membrane, mitoBK. The molecular mechanism of mitoBK-Nar interactions and their effects on conformational dynamics remain unclear. Artificial intelligence methods, such as k-NN and shapelet learning, were used to analyze dwell-time series of mitoBK channels at different voltages and Nar concentrations, revealing stimulus-specific patterns of channel gating and the complex interactions between the channel gate, voltage sensor, and Nar-binding site. In addition, long-range intra-sensor interactions between VSD and the Nar-coordination site were found to play a role in Nar-activation at deeply depolarized membranes.
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 (p(op)) 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 p(op)s) 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 (Delta p(op)) at deeply depolarized membranes. These intra-sensor interactions are anticipated to have an allosteric nature.

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