Ionic Mechanisms of Endogenous Bursting in CA3 Hippocampal Pyramidal Neurons: A Model Study

A critical property of some neurons is burst firing, which in the hippocampus plays a primary role in reliable transmission of electrical signals. However, bursting may also contribute to synchronization of electrical activity in networks of neurons, a hallmark of epilepsy. Understanding the ionic mechanisms of bursting in a single neuron, and how mutations associated with epilepsy modify these mechanisms, is an important building block for understanding the emergent network behaviors. We present a single-compartment model of a CA3 hippocampal pyramidal neuron based on recent experimental data. We then use the model to determine the roles of primary depolarizing currents in burst generation. The single compartment model incorporates accurate representations of sodium (Na+) channels (NaV1.1) and T-type calcium (Ca2+) channel subtypes (CaV3.1, CaV3.2, and CaV3.3). Our simulations predict the importance of Na+ and T-type Ca2+ channels in hippocampal pyramidal cell bursting and reveal the distinct contribution of each subtype to burst morphology. We also performed fast-slow analysis in a reduced comparable model, which shows that our model burst is generated as a result of the interaction of two slow variables, the T-type Ca2+ channel activation gate and the Ca2+-dependent potassium (K+) channel activation gate. The model reproduces a range of experimentally observed phenomena including afterdepolarizing potentials, spike widening at the end of the burst, and rebound. Finally, we use the model to simulate the effects of two epilepsy-linked mutations: R1648H in NaV1.1 and C456S in CaV3.2, both of which result in increased cellular excitability

Determinants of Heterogeneity, Excitation and Conduction in the Sinoatrial Node: A Model Study

The sinoatrial node (SAN) is a complex structure that exhibits anatomical and functional heterogeneity which may depend on: 1) The existence of distinct cell populations, 2) electrotonic influences of the surrounding atrium, 3) the presence of a high density of fibroblasts, and 4) atrial cells intermingled within the SAN. Our goal was to utilize a computer model to predict critical determinants and modulators of excitation and conduction in the SAN. We built a theoretical “non-uniform” model composed of distinct central and peripheral SAN cells and a “uniform” model containing only central cells connected to the atrium. We tested the effects of coupling strength between SAN cells in the models, as well as the effects of fibroblasts and interspersed atrial cells. Although we could simulate single cell experimental data supporting the “multiple cell type” hypothesis, 2D “non-uniform” models did not simulate expected tissue behavior, such as central pacemaking. When we considered the atrial effects alone in a simple homogeneous “uniform” model, central pacemaking initiation and impulse propagation in simulations were consistent with experiments. Introduction of fibroblasts in our simulated tissue resulted in various effects depending on the density, distribution, and fibroblast-myocyte coupling strength. Incorporation of atrial cells in our simulated SAN tissue had little effect on SAN electrophysiology. Our tissue model simulations suggest atrial electrotonic effects as plausible to account for SAN heterogeneity, sequence, and rate of propagation. Fibroblasts can act as obstacles, current sinks or shunts to conduction in the SAN depending on their orientation, density, and coupling

Digging into Lipid Membrane Permeation for Cardiac Ion Channel Blocker d-Sotalol with All-Atom Simulations.

Interactions of drug molecules with lipid membranes play crucial role in their accessibility of cellular targets and can be an important predictor of their therapeutic and safety profiles. Very little is known about spatial localization of various drugs in the lipid bilayers, their active form (ionization state) or translocation rates and therefore potency to bind to different sites in membrane proteins. All-atom molecular simulations may help to map drug partitioning kinetics and thermodynamics, thus providing in-depth assessment of drug lipophilicity. As a proof of principle, we evaluated extensively lipid membrane partitioning of d-sotalol, well-known blocker of a cardiac potassium channel Kv11.1 encoded by the hERG gene, with reported substantial proclivity for arrhythmogenesis. We developed the positively charged (cationic) and neutral d-sotalol models, compatible with the biomolecular CHARMM force field, and subjected them to all-atom molecular dynamics (MD) simulations of drug partitioning through hydrated lipid membranes, aiming to elucidate thermodynamics and kinetics of their translocation and thus putative propensities for hydrophobic and aqueous hERG access. We found that only a neutral form of d-sotalol accumulates in the membrane interior and can move across the bilayer within millisecond time scale, and can be relevant to a lipophilic channel access. The computed water-membrane partitioning coefficient for this form is in good agreement with experiment. There is a large energetic barrier for a cationic form of the drug, dominant in water, to cross the membrane, resulting in slow membrane translocation kinetics. However, this form of the drug can be important for an aqueous access pathway through the intracellular gate of hERG. This route will likely occur after a neutral form of a drug crosses the membrane and subsequently re-protonates. Our study serves to demonstrate a first step toward a framework for multi-scale in silico safety pharmacology, and identifies some of the challenges that lie therein

Parameterization for in-silico modeling of ion channel interactions with drugs

Since the first Hodgkin and Huxley ion channel model was described in the 1950s, there has been an explosion in mathematical models to describe ion channel function. As experimental data has become richer, models have concomitantly been improved to better represent ion channel kinetic processes, although these improvements have generally resulted in more model complexity and an increase in the number of parameters necessary to populate the models. Models have also been developed to explicitly model drug interactions with ion channels. Recent models of drug-channel interactions account for the discrete kinetics of drug interaction with distinct ion channel state conformations, as it has become clear that such interactions underlie complex emergent kinetics such as use-dependent block. Here, we describe an approach for developing a model for ion channel drug interactions. The method describes the process of extracting rate constants from experimental electrophysiological function data to use as initial conditions for the model parameters. We then describe implementation of a parameter optimization method to refine the model rate constants describing ion channel drug kinetics. The algorithm takes advantage of readily available parallel computing tools to speed up the optimization. Finally, we describe some potential applications of the platform including the potential for gaining fundamental mechanistic insights into ion channel function and applications to in silico drug screening and development

Channel Openings Are Necessary but not Sufficient for Use-dependent Block of Cardiac Na+ Channels by Flecainide: Evidence from the Analysis of Disease-linked Mutations

Na+ channel blockers such as flecainide have found renewed usefulness in the diagnosis and treatment of two clinical syndromes arising from inherited mutations in SCN5A, the gene encoding the α subunit of the cardiac voltage–gated Na+ channel. The Brugada syndrome (BrS) and the LQT-3 variant of the Long QT syndrome are caused by disease-linked SCN5A mutations that act to change functional and pharmacological properties of the channel. Here we have explored a set of SCN5A mutations linked both to BrS and LQT-3 to determine what disease-modified channel properties underlie distinct responses to the Na+ channel blocker flecainide. We focused on flecainide block that develops with repetitive channel activity, so-called use-dependent block (UDB). Our results indicate that mutation-induced changes in the voltage-dependence of channel availability (inactivation) may act as determinants of flecainide block. The data further indicate that UDB by flecainide requires channel opening, but is not likely due to open channel block. Rather, flecainide appears to interact with inactivation states that follow depolarization-induced channel opening, and mutation-induced changes in channel inactivation will alter flecainide block independent of the disease to which the mutation is linked. Analysis of flecainide block of mutant channels linked to these rare disorders has provided novel insight into the molecular determinants of drug action