Łukasiewicz Research Network-Institute of Medical Technology and Equipment, Zabrze, Poland.
Faculty of Science and Technology, University of Silesia in Katowice, Chorzów, Poland.
PLoS Comput Biol. 2022 Jul 20;18(7):e1010315. doi: 10.1371/journal.pcbi.1010315. eCollection 2022 Jul.
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.
线粒体内膜大电导电压和 Ca2+-激活钾通道(mitoBK)受多种因素调节。其中,从药理学角度来看,黄烷酮类,包括柚皮素(Nar),是一组很有前途的 mitoBK 通道调节剂。众所周知,在 Nar 存在的情况下,mitoBK 通道的开放状态概率(pop)显著增加。然而,mitoBK-Nar 相互作用的分子机制仍然没有被揭示。也不知道柚皮素给药对构象动力学的影响是否类似于其他激活通道刺激所产生的影响。为了回答这个问题,我们检查了在不同电压和 Nar 浓度下(仍允许达到可比的 pop)获得的 mitoBK 通道停留时间序列是否可以通过人工智能方法(包括 k-NN 和形状学习)来区分。获得的结果表明,门控动力学的结构复杂性既受到通道门与电压传感器(VSD)和 Nar 结合位点相互作用的影响。对于大多数数据,可以观察到通道门控的刺激特异性模式。在大多数情况下,形状学习算法可以获得更好的预测准确性。可能是因为它考虑了给定信号的局部特征的复杂性。大约 30%的分析时间序列没有足够的差异,无法将它们彼此明确区分开来,这可以从 mitoBK 通道门控无论激活刺激的类型如何都存在共同特征的角度来解释。VSD 和 Nar 配位位点之间存在长程相互作用,这导致在深度去极化膜中更高水平的 Nar 激活(Δpop)。这些传感器内相互作用预计具有变构性质。