Balbi Pietro, Massobrio Paolo, Hellgren Kotaleski Jeanette
Department of Neurorehabilitation, Scientific Institute of Pavia via Boezio IRCCS, Istituti Clinici Scientifici Maugeri SpA, Pavia, Italy.
Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS), University of Genova, Genova, Italy.
PLoS Comput Biol. 2017 Sep 1;13(9):e1005737. doi: 10.1371/journal.pcbi.1005737. eCollection 2017 Sep.
Modelling ionic channels represents a fundamental step towards developing biologically detailed neuron models. Until recently, the voltage-gated ion channels have been mainly modelled according to the formalism introduced by the seminal works of Hodgkin and Huxley (HH). However, following the continuing achievements in the biophysical and molecular comprehension of these pore-forming transmembrane proteins, the HH formalism turned out to carry limitations and inconsistencies in reproducing the ion-channels electrophysiological behaviour. At the same time, Markov-type kinetic models have been increasingly proven to successfully replicate both the electrophysiological and biophysical features of different ion channels. However, in order to model even the finest non-conducting molecular conformational change, they are often equipped with a considerable number of states and related transitions, which make them computationally heavy and less suitable for implementation in conductance-based neurons and large networks of those. In this purely modelling study we develop a Markov-type kinetic model for all human voltage-gated sodium channels (VGSCs). The model framework is detailed, unifying (i.e., it accounts for all ion-channel isoforms) and computationally efficient (i.e. with a minimal set of states and transitions). The electrophysiological data to be modelled are gathered from previously published studies on whole-cell patch-clamp experiments in mammalian cell lines heterologously expressing the human VGSC subtypes (from NaV1.1 to NaV1.9). By adopting a minimum sequence of states, and using the same state diagram for all the distinct isoforms, the model ensures the lightest computational load when used in neuron models and neural networks of increasing complexity. The transitions between the states are described by original ordinary differential equations, which represent the rate of the state transitions as a function of voltage (i.e., membrane potential). The kinetic model, developed in the NEURON simulation environment, appears to be the simplest and most parsimonious way for a detailed phenomenological description of the human VGSCs electrophysiological behaviour.
对离子通道进行建模是开发具有生物学细节的神经元模型的一个基本步骤。直到最近,电压门控离子通道主要是根据霍奇金和赫胥黎(HH)的开创性工作所引入的形式主义进行建模的。然而,随着在这些形成孔道的跨膜蛋白的生物物理和分子理解方面不断取得的成果,HH形式主义在重现离子通道的电生理行为方面表现出局限性和不一致性。与此同时,马尔可夫型动力学模型已越来越多地被证明能够成功复制不同离子通道的电生理和生物物理特征。然而,为了对即使是最细微的非导电分子构象变化进行建模,它们通常配备了大量的状态和相关转换,这使得它们计算量很大,不太适合在基于电导的神经元和大型网络中实现。在这项纯粹的建模研究中,我们为所有人类电压门控钠通道(VGSCs)开发了一个马尔可夫型动力学模型。该模型框架详细、统一(即它涵盖了所有离子通道亚型)且计算效率高(即具有最少的状态和转换集)。要建模的电生理数据来自先前发表的关于在异源表达人类VGSC亚型(从NaV1.1到NaV1.9)的哺乳动物细胞系中进行的全细胞膜片钳实验的研究。通过采用最少的状态序列,并对所有不同亚型使用相同的状态图,该模型在用于日益复杂的神经元模型和神经网络时确保了最轻的计算负荷。状态之间的转换由原始的常微分方程描述,这些方程将状态转换的速率表示为电压(即膜电位)的函数。在NEURON模拟环境中开发的动力学模型,似乎是对人类VGSCs电生理行为进行详细现象学描述的最简单、最简约的方法。