A

From Atoms to Neuronal Spikes: A Multiscale Simulation Framework

Journal of Chemical Theory and Computation, vol. 22, pp. 783–793

Abstract

High Resolution Image Download MS PowerPoint Slide Understanding how molecular events in ion channels impact neuronal excitability, as derived from the calculation of the time course of the membrane potentials, can help elucidate the mechanisms of neurological disease-linked mutations and support neuroactive drug design. Here, we propose a multiscale simulation approach which couples molecular simulations with neuronal simulations to predict the variations in membrane potential and neural spikes. We illustrate this through two examples. First, molecular dynamics simulations predict changes in current and conductance through the AMPAR neuroreceptor when comparing the wild-type protein with certain disease-associated variants. The results of these simulations inform morphologically detailed models of cortical pyramidal neurons, which are simulated using the Arbor framework to determine neural spike activity. Based on these multiscale simulations, we suggest that disease associated AMPAR variants may significantly impact neuronal excitability. In the second example, the Arbor model is coupled with coarse-grained Monte Carlo gating simulations of voltage-gated (K + and Na + ) channels. The predicted current from these ion channels altered the membrane potential and, in turn, the excitation state of the neuron was updated in Arbor. The resulting membrane potential was then fed back into the Monte Carlo simulations of the voltage-gated ion channels, resulting in a bidirectional coupling of current and membrane potential. This allowed the transitions of the states of the ion channels to influence the membrane potentials and vice versa. Our Monte Carlo simulations also included the crucial, so far unexplored, effects of the composition of the lipid membrane embedding. 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 and established a multiscale framework linking the atomistic perturbations to neuronal excitability.

Authors 7

  1. Ana Damjanovic corresponding

    National Institutes of Health · Johns Hopkins University · National Heart, Lung, and Blood Institute

    Affiliation as printed

    Department of Biophysics

    Department of Physics and Astronomy

    Johns Hopkins University

    National Heart, Lung, and Blood Institute

    National Institutes of Health

  2. Vincenzo Carnevale corresponding

    Temple University

    Affiliation as printed

    Institute for Computational Molecular Science

    Institute for Genomics and Evolutionary Medicine

    Temple University

  3. Thorsten Hater corresponding

    Forschungszentrum Jülich · Jülich Supercomputing Centre

    Affiliation as printed

    Jülich Supercomputing Centre (JSC)

    Simulation and Data Lab Neuroscience, Forschungszentrum Jülich GmbH

  4. National Institutes of Health · Johns Hopkins University · National Heart, Lung, and Blood Institute

    Affiliation as printed

    Department of Physics and Astronomy

    Johns Hopkins University

    National Heart, Lung, and Blood Institute

    National Institutes of Health

  5. Forschungszentrum Jülich · Universitätsklinikum Aachen · Jülich Supercomputing Centre

    Affiliation as printed

    Computational Biomedicine, Institute for Neuroscience and Medicine INM-9

    Department of Neurology, University Hospital Aachen, Pauwelsstraße 30, 52074 Aachen, Germany

    Forschungszentrum Jülich GmbH

    Jülich Supercomputing Centre (JSC)

    Simulation and Data Lab Biology

  6. Sandra Diaz-Pier corresponding

    Forschungszentrum Jülich · Jülich Supercomputing Centre

    Affiliation as printed

    Jülich Supercomputing Centre (JSC)

    Simulation and Data Lab Neuroscience, Forschungszentrum Jülich GmbH

  7. Paolo Carloni corresponding

    Forschungszentrum Jülich

    Affiliation as printed

    Computational Biomedicine, Institute for Neuroscience and Medicine INM-9

    Forschungszentrum Jülich GmbH

Cited by 0 stored of 0

No patents citing this paper on Lens.org (checked 2026-10-06).

References 73