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| Journal Article | FZJ-2026-00962 |
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2026
[Verlag nicht ermittelbar]
Washington, DC
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Please use a persistent id in citations: doi:10.1021/acs.jctc.5c01793 doi:10.34734/FZJ-2026-00962
Abstract: Understanding how molecular events in ion channelsimpact neuronal excitability, as derived from the calculation of thetime course of the membrane potentials, can help elucidate themechanisms of neurological disease-linked mutations and supportneuroactive drug design. Here, we propose a multiscale simulationapproach which couples molecular simulations with neuronalsimulations to predict the variations in membrane potential andneural spikes. We illustrate this through two examples. First,molecular dynamics simulations predict changes in current andconductance through the AMPAR neuroreceptor when comparingthe wild-type protein with certain disease-associated variants. Theresults of these simulations inform morphologically detailed modelsof cortical pyramidal neurons, which are simulated using the Arborframework to determine neural spike activity. Based on these multiscale simulations, we suggest that disease associated AMPARvariants may significantly impact neuronal excitability. In the second example, the Arbor model is coupled with coarse-grainedMonte Carlo gating simulations of voltage-gated (K+ and Na+) channels. The predicted current from these ion channels altered themembrane potential and, in turn, the excitation state of the neuron was updated in Arbor. The resulting membrane potential wasthen fed back into the Monte Carlo simulations of the voltage-gated ion channels, resulting in a bidirectional coupling of current andmembrane potential. This allowed the transitions of the states of the ion channels to influence the membrane potentials and viceversa. Our Monte Carlo simulations also included the crucial, so far unexplored, effects of the composition of the lipid membraneembedding. We explored the influence of lipidic compositions only using the Monte Carlo simulations. Our combined approaches,which use several simplifying assumptions, predicted membrane potentials consistent with electrophysiological recordings andestablished a multiscale framework linking the atomistic perturbations to neuronal excitability
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