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Subunit specific modulation of sodium channels by anti-epileptic drugs

Sun, G.

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Citation for published version (APA):Sun, G. (2007). Subunit specific modulation of sodium channels by anti-epileptic drugs Zutphen: WohrmannPrint

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Guangchun Sun

ii

Guangchun Sun, Shanghai, China, 2007 Printed by Wohrmann Print Service, Zutphen, The Netherlands Cover design: Annelies Olijslagers


ACADEMISCH PROEFSCHRIFT

ter verkrijging van de graad van doctor aan de Universiteit van Amsterdam,

op gezag van de Rector Magnificus prof. dr. D.C. van den Boom, ten overstaan van een door het

college voor promoties ingestelde commissie, in het openbaar te verdedigen in de Agnietenkapel

op dinsdag 16 oktober 2007, te 12.00 uur

door

Guangchun Sun

geboren te Guizhou, Volksrepubliek China

iv

Promotiecommissie: Promotor: Prof. dr. W.J. Wadman Co-promotor: Dr. T.R.Werkman Overige leden: Prof. dr. P.A.J.M. Boon

Dr. J.J. Clare Prof. dr. M. Jols Prof. dr. C.G. Kruse Prof. dr. F.H. Lopes da Silva Prof. dr. M.C. Michel Dr. R.A.Voskuyl

Faculteit der Natuurwetenschappen, Wiskunde en Informatica The research described in this thesis was carried out at the Center for Neuroscience of the Swammerdam Institute for Life Sciences, Universiteit van Amsterdam, The Netherlands. The research was financially supported by the Dutch National Epilepsy Foundation The Power of the Small.

v

ABBREVIATIONS 4-AP------------------ 4-aminopyridine AEDs ----------------- anti-epileptic drugs Cm -------------------- membrane capacitance CBZ ------------------ carbamazepine CHO ----------------- Chinese hamster ovary CNS ------------------ central nervous system DMSO --------------- dimethylsulfoxide DPH ------------------ phenytoin DRG ------------------ dorsal root ganglion EC50 ------------------ the concentration that causes half-maximal effect EGTA ---------------- ethylene glycol-bis(2-aminoethyl-ether)N,N,N,N-tetraacetic acid gmax ------------------- maximal conductance GABA -----------------aminobutyric acid GEFS+ --------------- febrile seizures plus GHK ----------------- Goldman-Hodgkin-Katz H & H ---------------- Hodgkin and Huxley HCL ------------------ human chromosomal localization HEK ------------------ human embryonic kidney HEPES --------------- N-(2-hydroxyethyl)piperazine-N-(2-ethanesulfanic acid) KA -------------------- kainate LTG ------------------ lamotrigine P0 ---------------------- maximal permeability P ---------------------- at postnatal day PIPES ---------------- piperazine- N,N-bis(2-ethanesulfanic acid) disodium salt PN -------------------- peripheral neuron S.E.M ---------------- standard error of the mean SKM ------------------ skeletal muscle SMEI ----------------- severe myoclonic epilepsy of infancy TEA ------------------ tetraethylammonium mTLE ---------------- mesial temporal lobe epilepsy TPM ------------------ topiramate TTX ------------------ tetrodotoxin

vi

CONTENTS Chapter 1 1 General introduction Chapter 2 17 Sodium current properties in different models of epilepsy Chapter 3 25 A comparison of Biophysical and Pharmacological Properties of Human Brain Sodium Channel -subunits NaV1.1, NaV1.2, NaV1.3 and NaV1.6 Expressed in HEK293 Cells Chapter 4 47 Sodium channel properties and functional changes by carbamazepine in rat hippocampal CA1 neurons during development Chapter 5 63 Kinetic changes and modulation by carbamazepine on voltage-gated sodium channels in rat CA1 neurons after epilepsy Chapter 6 79 Carbamazepine and topiramate modulation of transient and persistent sodium currents studied in HEK293 cells expressing the NaV1.3 -subunit Chapter 7 93 General discussion References 107 Nederlandse Samenvatting (Summary in Dutch) 123 (Summary in Chinese) 133 Curriculum Vitae 135 Dankwoord/Acknowledgements 137

CHAPTER 1

General Introduction

Chapter 1

2

Functional role of the sodium channel, action potential generation

Action potentials are the rapidly propagated electrical messages that speed along the axons of the nervous system and over the surface membrane of many muscle and glandular cells. In axons they are brief, travel at constant velocity, and maintain constant amplitude in an all or none fashion. The action potential is a membrane potential change causing a change in conductance that results in the flow of ions through ion channels in the membrane (Hille, 2001). Voltage-gated sodium channels are responsible for the rising phase of the action potential in the membranes of neurons, whereas voltage-gated potassium channels mediate the repolarization process (Hodgkin and Huxley, 1952b, Hodgkin and Huxley, 1952a, Hodgkin and Huxley, 1952c, Hodgkin and Huxley, 1952d) (Fig. 1).

Hodgkin and Huxley recorded sodium currents, using the voltage clamp technique and described their features in a new classical formalism, based on: (1) selective ion conductance, (2) voltage-dependent activation, and (3) rapid inactivation (Hodgkin and Huxley, 1952d), see Box 1. Detailed analysis of sodium channel function during the 1960s and 1970s using the voltage clamp method applied to invertebrate giant axons and vertebrate myelinated nerve fibers yielded mechanistic models for sodium channel function (Armstrong, 1981, Hille, 2001). The sodium channel protein was characterized in 1980, by biochemical approaches- e.g. measurement of ion flux through the channel, high affinity binding of neurotoxins, and detergent solubilization and purification of sodium channel proteins labeled by neurotoxins (Ritchie and Rogart, 1977). The sodium channel protein undergoes voltage-dependent conformation changes that regulate pore conductance and the Hodgkin and Huxleys (H&H) model accounts for ion fluxes and voltage dependent permeability changes of the excitable membrane (Hille, 2001) (box-1). Box-1: The Hodgkin and Huxley formalism for voltage dependent ion channels

In their original papers H&H stated three important assumptions that underlie

their analysis 1) Ionic currents for Na+ and K+ are independent of each other; 2) The ion channels that control the currents can be in several distinct conformational states. The kinetics of the currents are mainly determined by the number of states and the transitions between these states; 3) The voltage dependence arises because all rate constants that determine the transitions between different states are voltage dependent. This set of assumptions was sufficient to characterize the essentials that were known at that time and it also correctly predicted the propagation of an action potential along an axon (Hodgkin and Huxley, 1952d, Hodgkin and Huxley, 1952a).

In this box the formalism for the Na+ current is discussed, which can easily be expanded to describe the kinetics of all voltage dependent channels. Even to date the H&H formalism is still sufficient to describe the macroscopic currents through voltage dependent channels. The sodium current can activate and inactivate so that we need at least three different states to describe it: an open state (O), a closed state (C) and an inactivated state (I).

The transition between the closed and the open state models the process of activation. Assume that a fraction m of the channels is in the open state O and therefore


3

the fraction 1-m is in the closed state C:

mmOCVV

1

)(),(

(V) and (V) are the voltage dependent rate constants for respectively opening and closing. If the equilibrium between closed and open state can be described as a simple first order chemical reaction the time course of the opening of the channels should obey the following differential equation:

)()()1( VmVmdtdm =

which for a constant voltage V leads to the equilibrium distribution (m) and time constant ( ):

)()(

1)()()(

)()(VV

VVV

VVm

+

=+

=

which are determined at a certain membrane voltage under voltage clamp experimental conditions, keeping the voltage constant, to get a better estimation.

In a similar manner the occupancy of the inactivated state can be described from the transition of channels between the inactivated state (I) and the closed state (C), with its own specific rate constants (V) and V), where h is the fraction of the channels in the closed state C and therefore 1-h defines the fraction in the inactivated state I:

hhIC

1

)V(),V(

which leads to:

)()(1)(

)()()()(

VVV

VVVVh

+=

+=

Finally H & H empirically determined that the actual sodium conductance was best described by: max

3 ghmg Na = which for a driving force described by the Nernst equation (ENa) leads to a current of: )(max

3NaNa EVghmI =

in which g max is the maximum conductance and ENa is the equilibrium potential of sodium. Or, when using the Goldman-Hodgkin Katz current equation, to:

)exp(1

)exp()][][(

)( max3

V

VNaNa

VghmNaI outin

++

= with RTF

=

With this model the following sequence of events during an action potential (Fig. 1) is described in mathematical terms. At resting membrane potentials, most channels are in the closed state. In response to membrane depolarization, channels activate within a few hundred microseconds, and will quickly move into the open state. Channels cannot open

Chapter 1

4

from the inactivated state, so the maximum current that is generated strongly depends on the voltage at which activation starts. Once open and at a depolarized potential most channels will quickly (within a few milliseconds) convert to the non-conducting inactivated state. The membrane voltage has to repolarize to a relatively low voltage in order for the channel inactivation to be removed; the channels then transit from the inactivated to the closed state and are available for opening again. This takes time, which limits the firing frequency. During the depolarization, m rises rapidly and h falls slowly. Taking the cube of m sets up a small delay in the rise, and multiplying it by the slowly falling h makes m3h eventually fall to a low value again. After depolarization, m recovers rapidly and h slowly to the original values.

Brain sodium channels cycle through these three functional states within the few milliseconds that an action potential lasts. This characteristic is essential for sustaining rapid trains of action potentials necessary for brain function (Ragsdale and Avoli, 1998).

Figure 1. Action potential and underlying changes in Na and K conductions calculated from the H&H model at 18.5oC. After membrane depolarization, sodium currents activate rapidly and the depolarization becomes regenerative, but even before the peak of the action potential, inactivation starts and the sodium permeability falls back to its original value. The strong depolarization (slowly) activates potassium current, which is needed to repolarize the membrane. The time course of repolarization depends on the rate of sodium channel inactivation and the rate of potassium channel activation. For a brief period after the action potential, the membrane is absolute refractory as a fraction of the sodium channels is inactivated, thereafter the large potassium conductance results in a relative refractory period (Hille, 2001). Molecular properties of the sodium channel

Sodium channel proteins in the mammalian brain consist of n -subunit of approximately 260 kDa in association with auxiliary subunits of 33 to 36 kDa - 1, 2, 3 and 4 (Catterall, 1984, Catterall, 1992, Catterall, 2000, Yu et al., 2003) (Table 1). So far nine -subunits have been shown to form functional sodium channels NaV1.1 to NaV1.9 (Goldin et al., 2000) (Table 1). These subunits consist of four homologous domains (IIV), each of which contains six -helical transmembrane segments (S1S6) and a membrane re-entrant loop that dips into the trans-membrane region of the protein between transmembrane segments S5 and S6. The N-terminal and C-terminal domains are intracellular (Noda et al., 1984, Numa and Noda, 1986, Catterall, 2000) (Fig.2). The


5

S4 segments in each domain serve as the voltage sensors, the S5 and S6 segments and the re-entrant loop between them form the lining of the pore, and the short intracellular loop between domains and IV forms the inactivation gate (Figs. 2 and 3). Auxiliary 1 and 2 subunits contain immunoglobulin-like folds. The immunoglobulin-like fold is a sandwich of two sheets held together by hydrophobic interactions and forms the interface with the subunit (Fig. 2).

Even coexpression of the subunit is required for full reconstitution of the properties of native sodium channels, as these auxiliary subunits modify the kinetics and voltage-dependence of the gating (that is, opening and closing) of the channel (Isom et al., 1994, Catterall, 2000, Cantrell and Catterall, 2001, Yu and Catterall, 2003, Yu et al., 2005). The ion-conducting aqueous pore is contained entirely within the subunit, and the essential elements of sodium-channel function channel opening, ion selectivity and rapid inactivation can be demonstrated when subunits are expressed alone in cells (Goldin et al., 1986, Noda et al., 1986b, Scheuer et al., 1990, Catterall, 2000, Cantrell and Catterall, 2001, Yu and Catterall, 2003).

Figure 2. The primary structures of the subunits of the voltage-gated sodium channels are illustrated as transmembrane folding diagrams. The extracellular domains of the 1 and 2 subunits are shown as immunoglobulin-like folds, which interact with the loops in the subunits as shown. Roman numerals indicate the domains of the subunit; segments 1-5 indicate the transmembrane spanning regions of each domain. Segments 5 and 6 are the pore-lining segments and the S4 helices make up the voltage sensors. Circles in the intracellular loops of domains III and IV indicate the inactivation gate IFM (I1488, F1489 and M1490) motif and its receptor (h, inactivation gate); P, phosphorylation sites (in circles, sites for protein kinase A; in diamonds, sites for protein kinase C); , probable N-linked glycosylation site. The circles in the re-entrant loops (segment 5 and 6) in each domain represent the amino acids that form the ion selectivity filter (Catterall, 2000, Yu and Catterall, 2003).

Chapter 1

6

Figure 3. The hinged-lid mechanism of inactivation of sodium channels. The intracellular loop connecting domains III and IV of the sodium channel is depicted as forming a hinged lid with the critical phenylalanine (F1489) within the IFM (I1488, F1489 and M1490) motif shown occluding the mouth of the pore during the inactivation process. The circles represent the transmembrane helices (Catterall, 2000, Yu and Catterall, 2003). So far four different sodium channel subtypes have been identified in rat brain:

NaV1.1, NaV1.2, NaV1.3 and NaV1.6 (Noda et al., 1986a, Kayano et al., 1988, Schaller et al., 1995) (Table 1). The originally identified as cardiac sodium channel NaV1.5 subtype also appears to be present in the brain (mainly in limbic structures but not in hippocampus) (Hartmann et al., 1999, Wu et al., 2002). Moreover, type NaV1.2, NaV1.3 and NaV1.6 genes encode two isoforms, termed A (for adult) and N (for neonatal), as a result of a mutually exclusive splicing (developmentally regulated) of a single exon (Auld et al., 1988, Sarao et al., 1991, Gustafson et al., 1993, Plummer et al., 1998).

The human sodium channel subunit proteins exhibits a distinct subcellular localization patterns. Types NaV1.1, NaV1.3 and NaV1.6 immunoreactivity are predominantly in neuronal cell bodies and proximal processes, whereas type NaV1.2 is concentrated along axons (Whitaker et al., 2001b). This is similar to rat brain and suggests that different sodium channel subtypes have distinct functions that are highly conserved between human and rodents. However, a recent study indicated that NaV1.1 channels may also be predominantly located on axons (Ogiwara et al., 2007). There is a broader expression of type NaV1.3 in adult human brain than in adult rat brain (Whitaker et al., 2001b). Generally, Nav1.1 and Nav1.3 control neuronal excitability through integration of synaptic impulses to set the threshold for action potential initiation and propagation to the dendritic and axonal compartments, whereas NaV1.2 conducts the action potential (Westenbroek et al., 1989, Trimmer and Rhodes, 2004). During development, NaV1.6 has been shown to replace NaV1.2 in maturing nodes of Ranvier, the gaps in the myelin sheaths of myelinated axons where saltatory action potential conduction takes place (Boiko et al., 2001, Kaplan et al., 2001, Yu and Catterall, 2003).


7

Table 1. Voltage-gated sodium channel family (Catterall, 2000, Morgan et al., 2000, Hille, 2001, Isom, 2001, Whitaker et al., 2001b, Yu et al., 2003, Birch et al., 2004, Catterall et al., 2005, Yu et al., 2005).

subunit

other names

Gene name HCL

Auxiliary subunits

Key tissue distribution

Nav1.1 type I SCN1A 2q24 1,2,3,4 Brain,

spinal cord

Nav1.2 type II SCN2A 2q2324 1,2,3,4 Brain,

spinal cord

Nav1.3 type III SCN3A 2q24 1,3 Brain

(embryonic in rat)

Nav1.6 type VI /NaCh6

/PN4 SCN8A 12q13 1,2

Brain, spinal cord, glia, DRG

Nav1.4 SKM1 SCN4A 17q23

25 1 Skeletal muscle

Nav1.5 h1 SCN5A 3p21 1,2,3,4 Heart muscle

(Brain)

Nav1.7 PN1 /hNE /NaS

SCN9A 2q24 1,2

DRG, neuroendocrine

cells

Nav1.8 SNS /PN3 SCN10A 3p22-24 Unknown DRG

Nav1.9 SNS2 /NaN /PN5

SCN11A 3p21-24 Unknown DRG

subunit

Nav1 SCN1B 19q13 Brain, muscle,

DRG

Nav2 SCN2B 11q22 Brain

Nav3 SCN3B 11q24 Brain

Nav4 SCN4B 11q23 Brain,

spinal cord Abbreviations: DRG, dorsal root ganglion; HCL, human chromosomal localization; PN, peripheral neuron; SNS, sensory neuron specific; SKM, Skeletal muscle.

Chapter 1

8

Box-2: The relation between single channels and macroscopic current

In their original papers H&H did not explicitly state what the molecular form of the channels and the gates was. Since the great advances in molecular biology we now know that channels are membrane proteins and what these proteins look like. Many of them have been cloned and can now be investigated in isolation. This also implies that we have a much better concept of how the real channels operate at the molecular level. In this thesis a description at the level of ionic currents suffices, but in this box we will shortly explain how the macroscopic properties of the currents are related to the molecular properties of the channels. The basic mechanisms of the currents explained in Box-1 are a description of phenomena that are based on real molecular assumptions. The large channel proteins are folded in the membrane in such a way that they indeed form a watery channel, just big enough to let single ions pass. The sodium channel was one of the earliest ones to be cloned (Noda et al., 1984) and many of the details of its structure-function relations are known. In recent years a lot of knowledge has been gathered about the selectivity filter that determines the selective permeability of the channel, about the voltage sensors of ion channels (see specific facts on voltage-gated K+ channels (Gulbis and Doyle, 2004, Yu et al., 2005)) and about mechanisms responsible for properties like inactivation. The easiest way to translate the H&H model of the ionic current into channel properties is illustrated in Fig 4. The channel is presented as a conducting pore when the channel is in the open state, depending on voltage depolarization.

Figure 4. The sodium channel state and the sodium channel current under the cell-attached voltage clamp condition. When the membrane voltage is depolarized, the channel opens and sodium influx occurs (Bear et al., 2006).

The relation between the properties at the single channel level and the ones of the


9

macroscopic current are illustrated in Fig. 5, where an ensemble of 10 single channel sodium currents recorded in response to a depolarizing voltage step from 80 mV to 40 mV is shown and averaged (bottom trace). Their response is stochastic. After the depolarizing step, the channel can be open, but the time it takes until the first opening is stochastic; in fact a detailed analysis of the distribution of the intervals to first opening appears to follow a Poisson distribution, characterized by a mean time that is exactly equal to the time constant of activation obtained from the whole cell current shown as the bottom trace. Also the mean opening time of the channel, measured as the duration during which the channel is in the conducting state follows a Poisson distribution and its characteristic time is related to the time constant of inactivation in the current trace.

Generalizing we can conclude that whenever we encounter rate constant in the H&H state model, it represents a transition between distinct stochastic states in the single channel model.

(A) UNITARY SODIUM CURRENTS

Figure 5. Relation between single channels and macroscopic current (A) Ten consecutive trials of sodium currents are recorded during a voltage step from -80 to -40 mV. The open sodium channel has a conductance of about 2.2 pA. Dashed line indicates the current level when sodium channels are closed. (B) The ensemble average of 352 repeats of the same protocol (Hille, 2001).

Chapter 1

10

Many studies have shown that sodium channels in the brain have distinct

expression patterns depending on the distinct brain regions as well as the stages of development. For example, types NaV1.1, NaV1.2 and NaV1.6 are abundant in adult brain whereas type NaV1.3 was supposed to be mainly expressed at late embryonic and early postnatal time points (Felts et al., 1997, Chen et al., 2000), although more recently it has been shown that type NaV1.3 immunoreactivity is present in the adult rat brain (Lindia and Abbadie, 2003). In addition, in the human brain type NaV1.3 is detectable in many different brain structures (Chen et al., 2000, Whitaker et al., 2001b). All subtypes are detectable in the rat hippocampus (Black et al., 1994, Krzemien et al., 2000). For subunits, 1 and 2 subunits only occurred after postnatal day 3 (P3), whereas the 3 subunit is already present in embryonic tissues (Shah et al., 2001).

The somato-dendritic localization of NaV1.1, NaV1.3 and NaV1.6 sodium channels (see above), which activate at sub-threshold membrane potentials, may be important for generating the non-inactivating or persistent sodium currents, and may boost EPSPs originating in distal dendrites as they spread to the cell soma (Whitaker et al., 2001b). Interestingly, when expressed in HEK293 mammalian cells the cloned human type NaV1.1, NaV1.3 and NaV1.6 -subunits give rise to substantially higher levels of spontaneous persistent current than the type NaV1.2 channel (Chen et al., 2000). Modulation of the sodium channel

Modulation of sodium currents is very important in the brain, although specific deficits that directly affect sodium channel regulation are not yet known. Mutations that subtly alter neuronal voltage-gated sodium channel function can lead to human diseases of hyperexcitability, like epilepsy (Armijo et al., 2005, Meisler and Kearney, 2005, Koopmann et al., 2006, Yamakawa, 2006, Avanzini et al., 2007, Waxman, 2007). The SCN1A gene encoding the NaV1.1 neuronal sodium channel subunit is currently the most clinically relevant of all the known epilepsy genes (Mulley et al., 2005) and a number of epilepsy syndromes are associated with SCN1A gene mutations (Escayg et al., 2000, Claes et al., 2001, Fujiwara et al., 2003), e.g. febrile seizures plus (GEFS+) and severe myoclonic epilepsy of infancy (SMEI) (Vanoye et al., 2006).

SCN1A mutations could alter channel inactivation, resulting in persistent inward sodium current which will likely enhance excitability of neuronal membranes by causing prolonged membrane depolarization (Escayg et al., 2000, Lossin et al., 2002). The persistent sodium current and window current

The persistent sodium current is a noninactivating component of the tetrodotoxin-sensitive sodium current. It may arise from a modal change in gating of conventional sodium channels (Crill, 1996, Taddese and Bean, 2002). Direct interactions of sodium channels with subunits of G proteins might be one of the mechanism of inducing persistent sodium currents (Ma et al., 1994, Ma et al., 1997). The persistent sodium current is thought to be important for integration of neuronal responses, so the


11

modulation of sodium channel gating by G subunits is expected to have profound effects on neuronal excitability (Ma et al., 1997).

The persistent sodium current might have a key role in regulating excitability near firing threshold because it is largely unopposed by other voltage-activated currents in this range of membrane potentials. Moreover, there is evidence that the persistent sodium current contributes to the initiation and maintenance of epileptiform activity (Segal and Douglas, 1997). The persistent sodium current is greater in animal models of epileptogenesis, (Ketelaars et al., 2001, Agrawal et al., 2003, Ellerkmann et al., 2003). Moreover, sodium channel mutations that are associated with epilepsy in mice and humans have been found to enhance the persistent sodium current (Lossin et al., 2002).

The window current is also a noninactivating component of the tetrodotoxin-sensitive sodium current, but comes directly from the model of Hodgkin & Huxley (Hodgkin and Huxley, 1952d). In the Hodgkin-Huxley whole-cell current properties, plots of h (the probability that a sodium channel is not inactivated) and m (the probability that a sodium channel is activated), against membrane potential overlap over a small potential range, predicting a steady sodium conductance over this range. The window current should be affected by the shift in voltage dependence of activation and inactivation. Epilepsy

Epilepsy, one of the most common neurologic disorders, is a major public health issue, affecting about 4% of individuals over their lifetime (Browne and Holmes, 2001). The term epilepsy refers to a collection of disorders of the central nervous system (CNS) exhibiting disturbances of brain function characterized by the repeated occurrence of seizure activity. Most epileptic episodes are idiopathic although, occasionally, sympathomatic seizures can be attributed to head trauma, brain tumor, cerebrovascular problems, etc. The classification of seizure disorders has gradually undergone modification over the years, and the latest attempt was published in 1989 by the Commission on Classification and Terminology of the International League Against Epilepsy (Epilepsia, 30(4): 389-399, 1989). Mesial temporal lobe epilepsy (mTLE) is the most common form of adult focal epilepsy (Engel et al., 1989) and is characterized by chronic seizures that often originate in the hippocampal formation (Sloviter, 1994).

Epileptic seizures are induced by abnormal focal or generalized synchronized electrical discharges within the CNS. The equilibrium in communication between neurons is regulated by a network of excitatory and inhibitory circuits. Enhancement of excitatory or impairment of inhibitory mechanisms will disturb this equilibrium, and the intrinsic properties of individual neurons do also contribute. Since ion channels provide the basis for all these processes, any mutation-induced channel malfunction can directly alter brain excitability and can directly or indirectly induce epileptic seizures (Lerche et al., 2001, Armijo et al., 2005).

Epilepsy reflects neuronal hyperexcitability, arising from largely unknown genetic, molecular, cellular and network mechanisms (Avoli et al., 2005, Crino, 2007). Idiopathic epilepsies, which account for up to 40% of all epilepsies, are mainly caused by genetic factors (Steinlein, 2002) and often involve channelopathies, including sodium channel mutations (Armijo et al., 2005, Koopmann et al., 2006, Avanzini et al., 2007, Waxman,

Chapter 1

12

2007). In generalized epilepsy with febrile seizures plus (GEFS+), mutations in three genes coding for voltage-gated sodium channel or 1 subunits (SCN1A, SCN2A, SCN1B) and one GABA receptor subunit gene (GABRG2) have been identified (Wallace et al., 1998, Escayg et al., 2000, Celesia, 2001, Moulard et al., 2001, Sugawara et al., 2001, Lossin et al., 2002, Steinlein, 2002, Lossin et al., 2003, Mulley et al., 2003, Ceulemans et al., 2004, Armijo et al., 2005). In addition, also mutations in the SCN5A gene (encoding the NaV1.5 channel) have been suggested to underlie inherited epilepsy (Hartmann et al., 1999).

Animal models for temporal lobe epilepsy

Due to the ethical and experimental limitations of human studies, appropriate animal models for epilepsy are essential. Animal models have been developed for studying the basic mechanism(s) of epileptogenesis and the characteristics of chronic epilepsy (Hellier et al., 1998).

There are various experimental animal models for epilepsy that reflect the pathophysiology of human epilepsy. Chronic epilepsy models can be divided into acquired (symptomatic) epilepsy models, including the kindling model of epilepsy, post-status epilepticus models of TLE in which epilepsy develops after an induced sustained status epilepticus; and genetic (idiopathic) models that lead to different types of epilepsy. Currently, the kindling model (Bertram, 2007) and post-status models (kainite (Sun et al., 2006, Cross and Cavazos, 2007), pilocarpine (Borges et al., 2006, Pereira et al., 2007, Pitsch et al., 2007) or stimulus (Magalhaes et al., 2004, Borowicz et al., 2007) induced models) are the most widely used models for studies on epileptogenic processes. The seizures in these models can be used for testing of antiepileptic drug effects (Loscher, 2002), although many other realistic seizure models exist, such as transgenic or knockout mice with induced mutations (Noebels, 1999, Prasad et al., 1999). Pharmacological properties of anti-epileptic drugs

Despite progress in understanding the pathogenesis of seizures and epilepsy (McNamara, 1999), the cellular basis of human epilepsy is not completely understood. In the absence of a specific etiological understanding, approaches to drug therapy of epilepsy have necessarily been directed at the control of symptoms avoiding interference with normal brain function, i.e. the suppression of seizures by chronic administration of antiepileptic (anticonvulsant) drugs (AEDs). Most of these drugs were found empirically and afterwards some of their mechanisms of action have been elucidated. Clinically used AEDs decrease membrane excitability by interacting with ion channels or neurotransmitter receptors. Currently available AEDs appear to act on sodium channels, GABAA receptors, or calcium channels (Macdonald and Kelly, 1993, Macdonald and Kelly, 1994, Macdonald and Kelly, 1995, Meldrum, 1996, Rogawski and Loscher, 2004a, Meldrum and Rogawski, 2007). The pharmacotherapy of epilepsy includes over 20 different medications, mostly divided into older (first generation) drugs e.g. phenobarbital, phenytoin (DPH), carbamazepine (CBZ), and valproate, and new (second generation) drugs such as lamotrigine (LTG), topiramate (TPM), vigabatrin, tiagabine, gabapentin, and levetiracetam (Loscher and Schmidt, 2002). In our research we mainly


13

focused on CBZ, LTG, and DPH which are the most frequently prescribed drugs in the clinic and which all interact with voltage-gated sodium channels.

A short clinically connected description of the drugs used in this thesis is given below:

CBZ is an iminostilbene derivative of tricyclic antidepressants (Fig. 6) with a very short amide side chain. It exhibits a spectrum of anticonvulsant activity very similar to that of DPH (Rogawski and Porter, 1990). In humans, it is effective against partial and generalized tonicclonic seizures, but not against absence seizures (Ragsdale and Avoli, 1998).

LTG is a phenyltriazine (Fig. 6) that emerged from the screening of putative antifolates as anticonvulsant agents. It is a simple compound composed of only two aromatic rings. LTG has proven to be a promising new treatment for partial and generalized tonicclonic seizure (Rogawski and Porter, 1990, Yuen, 1994). In addition, it may also have utility in the management of primary generalized epilepsy with absence attacks (Ragsdale and Avoli, 1998).

DPH is a hydantoin containing the ureide structure (Fig. 6), which is traditionally viewed as an important structural motif responsible for antiepileptic activity. It was first described by Merritt and Putman (Merritt and Putnam, 1938) and it has subsequently been shown to be efficacious in treating partial and generalized tonicclonic seizures in humans. The remarkable property of DPH is that it is capable of preventing seizures without producing sedation. Thus, DPH was the first AED to approach the therapeutic ideal of inhibiting abnormal brain activity characteristic of seizures without appreciably interfering with normal brain activity (Ragsdale and Avoli, 1998).

TPM, a sulfamate-substituted monosaccharide (Fig. 6), is a relatively new AED. It has broad-spectrum activity, being efficacious against partial seizures and various generalized seizure types (Perucca, 2005). Its anticonvulsant action relies on interactions with various neurotransmitter and/or ion channel systems, e.g. inhibition of kainate-evoked currents (Gibbs et al., 2000), enhancement of GABA-evoked currents (White et al., 1997), inhibition of voltage-activated calcium currents (Zhang et al., 2000), but also block of (persistent) sodium currents (Zona et al., 1997, Taverna et al., 1999).

Carbamazepine Lamotrigin

Chapter 1

14

Phenytoin Topiramate

Figure 6. Structures of AEDs used in this study.

CBZ, LTG, and DPH have a similar spectrum of activity in animal seizure models

and in human epilepsies. They all show voltage- and frequency- dependent suppression of sodium currents, which has been implicated as the major mechanism underlying their antiepileptic effect (Rogawski and Porter, 1990, Kuo and Lu, 1997, Ragsdale and Avoli, 1998, Rogawski and Loscher, 2004a). The use-dependent block of discharges is of great mechanistic interest as it readily explains why these nonsedative antiepileptics may effectively inhibit seizure discharges, yet spare most normal activity (Kuo and Lu, 1997). These drugs do not reduce the amplitude or duration of single action potentials but reduce the ability of neurons to fire trains of action potentials at high frequency (Macdonald and Kelly, 1993, Macdonald and Kelly, 1994, Macdonald and Kelly, 1995, Meldrum, 1996). The action of the AEDs appears to be due to a shift of sodium channels to an inactive state that is similar to the normally occurring inactive state but from which recovery is delayed (Macdonald and Kelly, 1993). This stabilization of the inactive form of the channel results in frequency- dependent block of sodium channels and in the blockade of sustained high-frequency repetitive firing of action potentials evoked from reduced membrane potentials (Macdonald and Kelly, 1993).

These three anticonvulsants all have much higher affinity to the inactivated state than to the resting or open state of the sodium channel via a simple bimolecular reaction (a one-to-one binding process) (Macdonald and Kelly, 1993, Kuo, 1998), but long (seconds) depolarizations are needed for drug binding to the channels (Matsuki et al., 1984, Lang et al., 1993, Kuo and Bean, 1994b, Kuo and Bean, 1994a, Xie et al., 1995). They are effective inhibitors of sodium currents only when applied externally, not internally, suggesting that they bind to a common site of the sodium channel located extracellularly (Kuo, 1998).

LTG and DPH may potently inhibit sodium currents by slow binding to the fast inactivated state of sodium channels (Kuo et al., 1997). Compared to DPH, CBZ has 3-fold lower affinity for depolarized channels, but binds to these channels with a five time faster rate (Kuo et al., 1997). Thus, CBZ may be more effective than DPH under epileptic conditions with relatively fast depolarizing shifts. This difference may in part explain why some patients respond better to DPH whereas others are more effectively treated with CBZ (Ragsdale and Avoli, 1998).


15

In addition to effects on the fast voltage-gated sodium current that is responsible for the upstroke of the action potential, AEDs might also act by blocking the persistent sodium current. Several authors have reported that phenytoin (Chao and Alzheimer, 1995, Segal and Douglas, 1997, Lampl et al., 1998, Niespodziany et al., 2004) and topiramate (Taverna et al., 1999) inhibit the persistent sodium current at concentrations lower than those that block fast sodium current. The selective reduction of late, persistent sodium channel openings might contribute to the ability of these drugs to protect against seizures. Pharmacoresistance to AEDs

Although currently available AEDs are effective, at least 30% of all epilepsies are refractory to current AEDs, especially those with complex partial seizures (Macdonald and Kelly, 1993, Loscher and Schmidt, 2002). During recent years, a large number of new AEDs have been marketed worldwide, but the proportion of patients failing to respond to drug treatment has not changed to a significant extent (Brodie and Porter, 1990, Brodie, 2001). Thus, new concepts and original ideas for developing AEDs are urgently needed (Loscher and Schmidt, 2002).

In chronic epilepsy, many patients develop resistance to anticonvulsant drug treatment during the course of their disease, with the underlying mechanisms remaining unclear. Two main concepts have been advanced to explain drug resistance. 1) The overexpression of multidrug transporters, especially P-glycoprotein (Pgp), restricts the access of these drugs to their site of action (Abbott et al., 2002, Loscher and Potschka, 2002, Rizzi et al., 2002, Remy et al., 2003a, Weiss et al., 2003, Remy and Beck, 2006). 2) Molecular drug targets may undergo genetic (see the paragraph Modulation of the sodium channel) or functional modification after which they are no longer sensitive to their ligands. It was reported that the composition of sodium channel subunits was changed after epilepsy. For example, the expression of NaV1.3 channels was markedly increased in rat hippocampus following kainic acid-induced seizures (Bartolomei et al., 1997). In human epileptic hippocampus, a markedly up-regulation of NaV1.3 channel was detected, whereas the NaV1.2 channel was significantly down-regulated (Whitaker et al., 2001a). In addition, the increased expression of neonatal isoforms of NaV1.2 and NaV1.3 channels was observed in hippocampal neurons, dentate granule cell layer and microglial cells after electrically-induced status epilepticus (Aronica et al., 2001). Furthermore, the sodium channel 1 subunit was up-regulated in astrocytes of epilepsy model rats (Catania et al., 2003) and in glia of epilepsy patients (Aronica et al., 2003). These results collectively suggest that changes in sodium channel (subunits) might partly underlie the pharmaco-resistence of AEDs. The studies in this thesis were performed based on this hypothesis. Outline of this thesis

The aim of this thesis is to understand the functional role of sodium channels in epilepsy. Since earlier work has shown the changed expression of sodium channel subunits after epilepsy (see above), the question arose whether (subtle) differences of drug sensitivities between sodium channel subunits could be involved in the pharmacoresistance observed in epilepsy. HEK-cell lines stably expressing the human

Chapter 1

16

brain sodium channel subunits NaV1.1, NaV1.2, NaV1.3 and NaV1.6 comprise a useful tool to study the function of subunits in a standardized expression system. Furthermore, we translated our studies to the sodium channels in dissociated CA1 hippocampal neurons with different subunit composition, during development and after epilepsy.

In Chapter 2, a background theory is discussed to illustrate the study of sodium channel function (and the interactions of AEDs with these channels) under voltage clamp conditions. The parameters of sodium channel properties are illustrated with a modeling study based on actual experiments in CA1 hippocampal pyramidal neurons.

In Chapter 3, the electrophysiological properties of the human brain sodium channel subunits NaV1.1, NaV1.2, NaV1.3 and NaV1.6 expressed in HEK293 cells are studied. In addition, the modulation of the four sodium channels -subunits by the commonly used AEDs CBZ, LTG and DPH is investigated.

In Chapter 4, the sodium channel function as well as its modulation by CBZ in rat neonatal and adult hippocampal CA1 neurons is studied. The purpose of the study is to detect whether changes in the composition of sodium channel -subunits during development underlie a different sensitivity to CBZ.

In Chapter 5, the sodium channel function as well as its modulation by CBZ in rat hippocampal CA1 neurons after kainate-induced epilepsy is studied. The purpose of the study is to determine whether sodium channels of epileptic tissues display a different CBZ sensitivity as compared with sodium channels of control tissue.

In Chapter 6, the inhibition of the persistent sodium current in NaV1.3 -subunit expressed in HEK293 cells by CBZ and TMP is compared. Also the effects of these two AEDs on the transient sodium current are compared. The purpose of the study is to determine to what extent the interactions of CBZ and TPM with the two sodium current components contribute to the anti-epileptic profile of these AEDs.

In Chapter 7, we summarize and discuss the conclusions drawn in the preceding chapters and their implications with regard to the efficacy of AEDs on sodium channel (subtypes).

CHAPTER 2

Sodium current properties in different models of epilepsy

Wytse J. WADMAN, Rogier MIN, and Guangchun SUN

In: Corcoran M, Moshe L, eds. Kindling 6. Amsterdam: Springer, 61-70 (2005)

Chapter 2

18

1. INTRODUCTION

The voltage dependent sodium current determines the upstroke of the action potential and it is therefore one of the determinant factor for neuronal excitability. The steep voltage dependence of activation as well as inactivation in combination with it fast kinetics imply that even relatively small changes in sodium current properties will have a significant influence on for example cell firing frequency. It is therefore not surprising that the majority of anti epileptic drugs (AEDs) exert their action by modulating sodium current properties that are relevant for cell firing (for review see Kohling, 2002). The aim of this study is to parameterize the sodium current in CA1 hippocampal pyramidal cells using the classical description originally provided by Hodgkin and Huxley (Hodgkin and Huxley, 1952d, Hodgkin and Huxley, 1952a) employing voltage clamp data obtained from neurons acutely isolated from the rat hippocampus . Such a description does not comprise every possible detail of the present knowledge of the sodium channel. Nevertheless it appears to be sufficient to describe the changes observed in the inactivation function of the sodium current in neurons isolated from the epileptic focus in rats that were either kindled (Vreugdenhil et al., 1998) or in which a status epilepticus model was generated (Ketelaars et al., 2001).

The most effective drugs against epileptic seizures exert their effect by specifically shifting the inactivation function in a hyperpolarizing direction in a concentration dependent manner. This modulation can be incorporated into the kinetic scheme of the sodium current as a binding to the inactivated state based on actual experiments in the cells under study. With the description of the sodium current at hand a model neuron was implemented in the NEURON simulation environment (Hines and Carnevale, 1997) so that its firing properties could be simulated under current clamp conditions. This offers the possibility to predict how carbamazepine binding could affect the firing behavior of these neurons.

2. Na-CURRENT IN CA1 PYRAMIDAL NEURONS

The classical description of the sodium channel (Hodgkin and Huxley, 1952d, Hodgkin and Huxley, 1952a) postulates that the current is controlled by an activation gate (m: the fraction of open gates) and an inactivation gate (h) that together control the voltage and time dependence of the conductance for sodium. The kinetics in the model is determined by the state of the gates, while the voltage dependence is incorporated in the rate constants that define the state transitions: NaNa gthtmtg = )()()(

3 (1) where h defines the fraction of the h gates in the open state hh VV hh 1)()( (2) and the change in h is given by

hVhVdtdh

hh = )()1()( (3)

The rate constants and determine the steady state (h) at a certain membrane

voltage and the voltage dependent time constant of h. A similar set of equations (2-3) can


19

Figure 1. Examples of fits to sodium currents evoked with various protocols in CA1 pyramidal neurons acutely, enzymatically isolated from the rat hippocampus (for methods see Vreugdenhil and Wadman, 1992). A1 Sodium current evoked by 20 ms depolarization to -40 mV preceded by a 40 ms hyperpolarization to -150 mV. Holding potential is set at -65 mV. The current is fitted with a third order rising exponential and single exponential decay. A2 Same as A1 but now for a depolarization to -25 mV. B Recovery from inactivation measured using a double pulse protocol separated by hyperpolarizations of variable duration and membrane voltage of three different values (-70, -80, and -90 mV). Smooth curves are first order exponential fits to the data points. C Inactivation measured by a standard depolarization to -20 mV, preceded by hyperpolarization to levels between -65 and -150 mV. Smooth curve is the fit to a Boltzmann function (4). D Activation function determined as the peak amplitude of the sodium current evoked by a 20 ms depolarization. Smooth curve is the fit to the Goldman-Hodgkin-Katz current equation (Hille, 2001), using a Boltzmann function to describe the voltage dependence of the permeability (5).

be defined for the activation gate m (which stand for the fraction of m gates in the open state). We used a procedure that directly fitted a complete set of currents observed under experimental conditions (examples in figure 1a and b) in order to estimate the best functions for and and found:

41.891.19

1

76.23)( Vme

V +

= and 30.26

57.121

1

36.27)( ++

= Vme

V

and

Chapter 2

20

50.20

66.151

1

856.0)( ++

= Vhe

V and 71.12

08.16

1

917.1)( Vhe

V +

=

Under these conditions the inactivation function is sufficiently fitted by a Boltzmann equation (figure 1c):

c

h

VVV

e

IVI

+

=

1

)( max (4)

The activation function was fitted with the Goldman-Hodgkin-Katz current equation (Hille, 2001) using a permeability with a Boltzmann type voltage dependence (figure 1d):

V

VNaNa

VcVVh e

e

e

gVVI o

i

+=

+

+

11

)( ][][

max (5)

The sodium current defined by these parameters was implemented in a NEURON simulation model (Hines and Carnevale, 1997), with a single compartment morphology, which resembles the electrotonic shape of the isolated neuron used for the fitting. Applying the standard voltage clamp protocols to the artificial neuron confirmed the correct implementation of the properties of the sodium current. 3. Na-CURRENT INACTIVATION IN EPILEPSY MODELS

The change in excitability that is associated with the process of epileptogenesis is partly resulting from changes in ionic currents. Here we focus on the role of the sodium current properties (for a review see Kohling, 2002). A common observation made in several models of epilepsy is a shift of the inactivation curve in depolarizing direction. In the epilepsy model of classical kindling Vh shifted about 3.1 mV in depolarizing direction (Vreugdenhil et al., 1998). A similar shift (2.5 mV) was found in the SSLSE model of epilepsy (Ketelaars et al., 2001), although in those experiments the variance was larger and the difference did not reach significance (figure 2). The inactivation function is so steep that even a shift of this small magnitude results in a ~25% increase of the number of recruitable sodium channels at resting membrane potential.

4. CBZ MODULATION OF Na-CURRENT INACTIVATION Carbamazepine (CBZ) is one of the drugs of first choice for the treatment of

epileptic patients (Macdonald and Kelly, 1994). Its basic mechanism of action has extensively been studied, in particularly under conditions of voltage clamp in isolated neurons. Extrapolating such results to the effects of the drug under current clamp conditions has proven more difficult than expected and most results are formulated in terms of its effectiveness in the prevention of seizures.

The isolated cell preparation allows to determine which parameters of the sodium current (as defined in figure 1) are modulated by CBZ. CBZ does not affect the activation properties of the sodium current (data not shown, but see Vreugdenhil and Wadman, 1999), but it exerts a highly specific effect on the inactivation of the current (figure 3).


21

Figure 2: Inactivation properties of sodium current in rat hippocampal neurons. A. Shift in depolarizing direction in fully kindled animals (adapted from Vreugdenhil et al., 1998). B. A similar shift in neurons isolated from rats in the SSLSE model (adapted from Ketelaars et al., 2001).

The relation between the CBZ concentration and the shift of the inactivation curve

is well described by a Hill relation with a Hill factor of 1 and an EC50 in the range of 40-100 M (figure 3b). In a series of studies Kuo and coworkers (Kuo et al., 1997, Kuo, 1998) have shown that CBZ acts by binding to an extracellular site of the sodium channel. The affinity of binding to the inactivated state is much larger than that to the resting state. This mechanism can be investigated under voltage clamp, and it can be added to the kinetic scheme presented by equations 1-3.

Figure 3: A. Application of carbamazepine shifts the inactivation in hyperpolarizing direction in a dose dependent way. B. The relation between Vh and CBZ can be described by a Hill function, the Hill factor for this cell was 1 and the EC50 for this cell was 94 M.

Chapter 2

22

The assumption that binding of CBZ predominantly takes place to the inactivated

state of the sodium channel implies the existence of an additional h state (hbound). The distribution of the channels between hclosed and hbound is then determined by a CBZ dependent association constant (CBZ) and a fixed dissociation constant : bound

CBZclosed hCBZh hh +

)( (6)

A protocol was designed in which a depolarizing voltage step of variable duration allowed CBZ to bind to an increasing fraction of inactivated gates.

A standard depolarizing voltage step subsequently applied made it possible to quantify the bound fraction (figure 5A, voltage protocol given as an inset). The binding rate constant was then obtained from the relation between CBZ and the binding rate. For CBZ in CA1 hippocampal pyramidal cells we obtained a value for (CBZ) of 32 3 mM-1s-1.

Figure 4. Determining the binding rate constant (CBZ) for CBZ to the inactivated state of the sodium channel. A. Slow binding to the inactivated state decreases the current evoked by a test pulse after an inactivating voltage step of variable duration. CBZ concentration for this experiment was 50 M. The smooth curve is the single exponential fit to the data points with a time constant of 270 ms. The voltage protocol is given as an inset. B. The binding rate constant can be determined from the relation between binding rate and CBZ concentration, using a least square fit.

5. CBZ MODULATION OF NEURONAL FIRING

The addition of a CBZ dependent bound state to the model allows illustrating the equilibrium distribution of the h channels over the three states as a function of CBZ (see figure 5 for examples of a low and a high concentration of CBZ). It also confirms the observed shift in Vh of the inactivation function and it allows investigating the changes in time constant of recovery from inactivation that can be anticipated (data not shown). In order to evaluate the possible consequences of CBZ presence on neuronal firing rate we


23

implemented the sodium current in a single compartment neuron implemented in the simulation environment NEURON (Hines and Carnevale, 1997). To create realistic firing we had to add at least a voltage dependent potassium current and we implemented the one defined by Hofman and coworkers (Hoffman et al., 1997). Although this oversimplified neuronal model will not demonstrate all the fine variations in firing patterns that are possible (e.g. it will lack properties related to calcium current, calcium accumulation and calcium dependent potassium channels), it will nevertheless demonstrate how CBZ affects basic firing rate of an isolated neuron (for overview see Destexhe and Huguenard, 2000, Destexhe and Huguenard, 2000b).

Figure 5. Distribution of the h gates over the three possible states (open, closed and bound) illustrated for 5 M (left panel) and 50 M CBZ (right panel). The Vh of the curve that describes the distribution between hopen and hclosed shifts from -75.2 mV to -83.7 mV when CBZ is increased from 5 to 50 M.

As is demonstrated in figure 6 the presence of a high concentration of CBZ

(100 M), considerably above the usual adopted therapeutic dose of 15 M) blocks all action potentials. At a concentration of 50 M, CBZ effectively reduces firing rate of the neurons and the difference between figure 6A and B indicates that these properties are use-dependent. 6. CONCLUSIONS

Using a fit procedure that minimizes the collective error of a complete set of current traces describing voltage dependent activation, inactivation, and recovery from inactivation, allowed us to use the classical formalism of Hodgkin and Huxley and model the sodium current with sufficient accuracy to simulate such a set of current traces. Adding one more inactivated state (the one bound to CBZ) also permitted to incorporate

Chapter 2

24

the binding of carbamazepine in a form that catches the essential properties responsible for its anti-epileptic activity.

Figure 6. Firing properties of a hippocampal CA1 neuron investigated in a NEURON simulation model. A. Relation between current injection and firing rate measured over 2000 ms for control and in the presence of 50 and 100 M CBZ. The latter concentration completely blocked neuronal firing. B. The same relation as illustrated in A, but now firing rate was determined over the first 200 ms. C. sample trace of membrane potential for control and in the presence of 150 M CBZ.

The changes induced by CBZ are counteracting the changes observed in sodium current inactivation in the classical kindling model of epilepsy (Goddard et al., 1969, Vreugdenhil et al., 1998) and in the SSLSE model (Lothman et al., 1995, Ketelaars et al., 2001, Gorter et al., 2002). Of course the effectiveness of CBZ in preventing seizures cannot be predicted from such a modeling study as many more parameters of currents and neurons might have changed in the epileptic focus. On the other hand it has provided us with a tool that predicts how an AED will affect firing rate under normal conditions. 7. ACKNOWLEDGMENTS

The help of Martin Vreugdenhil, Susan Ketelaars, Kristel Crommentuijn, Jan

Gorter, and Taco Werkman in the experiments is greatly acknowledged. We also thank Hans Kager and Michiel Remme for their help in building and investigating the NEURON model.

CHAPTER 3

A Comparison of Biophysical and Pharmacological Properties of Human Brain Sodium Channel -subunits NaV1.1, NaV1.2, NaV1.3 and

NaV1.6 Expressed in HEK293 Cells

Guangchun SUN, Taco R. WERKMAN, Jeffrey J. CLARE and Wytse J. WADMAN

Submitted to Molecular Pharmacology

Chapter 3

26

ABSTRACT The whole cell voltage-clamp technique was used to investigate the biophysical and pharmacological properties of the human Na+ channel NaV1.1, NaV1.2, NaV1.3 and NaV1.6 -subunits stably expressed in HEK293 cells. Some subtle differences were observed for the properties of voltage-gated Na+ currents carried by the four -subunits. For instance, the recovery from inactivation of Na+ currents carried by the NaV1.1 and NaV1.6 -subunits was relatively fast (tau values at 80 mV ~7 and ~ 5 ms, respectively) whereas this was much slower for the NaV1.2 and NaV1.3 currents (~18 ms and ~28 ms, respectively). Furthermore, the anti-epileptic drugs (AEDs) carbamazepine (CBZ), lamotrigine (LTG), and phenytoin (DPH) concentration dependently blocked the Na+ currents in a use- and frequency-dependent manner. Especially the NaV1.1 and NaV1.6 currents were found to be less sensitive to CBZ (EC50 values for shifting the steady-state inactivation curve: NaV1.1, ~345 M; NaV1.2, ~65 M; NaV1.3, ~85 M; NaV1.6, ~195 M). When comparing the binding kinetics of the three AEDs, we found that CBZ had a much faster binding rate to the -subunits than LTG and DPH (e.g. for the NaV1.2 subunit: CBZ, 75.1 6.2 mM-1s-1; LTG, 21.0 2.7 mM-1s-1; DPH, 12.9 2.1 M-1s-1). We also observed that all three AEDs displayed slower binding and unbinding rates for the NaV1.3 subunit as compared with the other -subunits. These findings are discussed in the light of AED efficacy, especially under (epileptic) conditions when expression patterns of voltage-gated Na+ channels are changed. Introduction

Voltage-gated Na+ channels play an important role in cellular excitability. They open upon depolarization of the membrane and their regenerative properties make them responsible for the generation of action potentials. Ultimately they are the key players in the transmission of fast impulses through cell membranes and cellular networks (Catterall, 1984). The brain Na+ channel proteins consist of a pore-forming -subunit associated with auxiliary -subunits (Catterall, 2000, Catterall et al., 2005). Expression of the -subunit alone is sufficient for the formation of functional Na+ channels, but subunits (so far four types: 1 through 4 have been identified) can modulate the (inactivation) properties of the channel and also have a role in trafficking the channel to the cell membrane (Isom, 2001, Meadows et al., 2002, Goldin, 2003, Ulbricht, 2005). Of the ten different Na+ channel -subunits known, the NaV1.1, NaV1.2, NaV1.3 and NaV1.6 -subunits comprise the most prominent brain Na+ channels (Noda et al., 1986a, Kayano et al., 1988, Schaller et al., 1995, Yu and Catterall, 2003). Moreover, various alternatively spliced isoforms of these are known including adult and neonatal isoforms of NaV1.2, NaV1.3 and NaV1.6 which result from developmentally regulated splicing of a single exon (Auld et al., 1988, Sarao et al., 1991, Gustafson et al., 1993, Plummer et al., 1998).

Certain generalizations can be made with respect to the location and function of these four -subunits (Yu and Catterall, 2003, Trimmer and Rhodes, 2004). NaV1.1 subunits are located on dendrites and cell bodies and are thought to play a role in synaptic signal transfer from dendrite to cell body. NaV1.2 subunits are mainly located in axons and terminals. They contribute to axonal propagation of action potentials. NaV1.3

Pharmacology of -subunits of human sodium channels

27

subunits are abundant in embryonic and neonatal brain, and also occur in adult brain where they have an expression pattern similar to that of NaV1.1 subunits in the adult brain (Whitaker et al., 2001b, Lindia and Abbadie, 2003, Thimmapaya et al., 2005). Finally, NaV1.6 subunits are expressed at high levels in the nodes of Ranvier of myelinated axons, where they have a function in the characteristic high velocity action potential propagation in these axons.

The most common antiepileptic drugs (AEDs) target voltage-gated Na+ channels in a use- and voltage-dependent manner, a mechanism that selectively dampens pathologic activation of Na+ channels in particularly by preventing high frequency synchronous firing, without interacting with normal Na+ channel function (Macdonald and Kelly, 1995, Clare et al., 2000, Rogawski and Loscher, 2004a, Clare, 2006). Through this action AEDs like carbamazepine (CBZ), phenytoin (DPH) and lamotrigine (LTG) are effective in treating partial and generalized tonic-clonic seizures in humans (Rogawski and Porter, 1990, Ragsdale and Avoli, 1998). The interaction with Na+ channels also underlies therapeutic efficacy of such drugs in the treatment of non-epileptic conditions like neuropathic pain and migraine (Rogawski and Loscher, 2004b). Disturbed function of voltage-gated Na+ channels is implicated in neurological disorders like epilepsy, where in several instances it involves channeloptahies of Na+ channel - and/or -subunits (Clare et al., 2000, George, 2005, Meisler and Kearney, 2005, Clare, 2006).

CBZ, LTG, and DPH all have a much higher affinity to the inactivated state than to the resting state of the Na+ channel which implies that they stabilize the inactivated states, effectively blocking the conductance (Ragsdale and Avoli, 1998). The -helical S6 segments of the III and VI repeats of the -subunits comprise the site where most AEDs bind to the voltage-gated Na+ channel (Rogawski and Loscher, 2004a). This site is accessible from the extracellular side of the channel via a simple one-to-one binding reaction (Kuo, 1998). AED-Na+ channel interactions have been described in several studies (Ragsdale et al., 1991, Kuo and Bean, 1994b, Xie et al., 1995, Ragsdale et al., 1996, Kuo et al., 1997, Kuo and Lu, 1997, Xie et al., 2001, Liu et al., 2003, Ilyin et al., 2005) but a systematic and detailed comparison of AED effects on the different brain Na+ channel subtypes NaV1.1, NaV1.2, NaV1.3 and NaV1.6 is lacking. In this study we will compare the interaction of the AEDs CBZ, DPH and LTG with the four brain related -subunits that were stably expressed in HEK293 cell lines. As there is growing evidence that Na+ channel -subunit expression might undergo modification during or after epileptogensis, understanding of the differences in pharmocological profile of these channel components might be of help in combatting the phenomenon of pharmaco resistance, a condition which affects ~30% of epilepsy patients who do not respond to first-line AEDs (Regesta and Tanganelli, 1999, Remy and Beck, 2006). Materials and Methods

Stably transfected HEK293 cell lines. All experiments were performed in HEK293 cell lines stably expressing the human NaV1.1, NaV1.2, NaV1.3 or NaV1.6 -subunits that have previously been described (Chen et al., 2000, Burbidge et al., 2002, Mantegazza et al., 2005). The cell lines were generated using the pCIN5 vector (Chen et al., 2000) using the method described by Burbidge et al. (Burbidge et al., 2002).

Chapter 3

28

Cell culture. The HEK293 cell lines stably expressing the human NaV1.1, NaV1.2, NaV1.3 or NaV1.6 sodium channel -subunits were cultured in minimum essential medium (Gibco), containing 10% fetal calf serum (Gibco), 1% L-glutamine (200 mM, Gibco) and 1% penicillin/streptomycin (Gibco). Cells were grown in a 95/5% O2/CO2 atmosphere at 37oC and with 95% humidity. One to two days prior to electrophysiological recordings, the cells were plated on glass coverslips.

Whole-cell voltage-clamp recordings. Cells grown on glass coverslips were placed into a recording chamber with 0.5 ml extracellular solution which contained (in mM): NaCl 140, KCl 5, CaCl2 2, MgCl2 1, HEPES 10, and glucose 11; pH was adjusted to 7.4. The patch electrodes had resistances of 2-3 M and were filled with pipette solution consisting of (in mM): CsF 140, EGTA 10, HEPES 10, NaCl 5, MgCl2 2; the pH was adjusted to 7.3. Voltage-dependent Na+ currents were measured under whole-cell voltage-clamp conditions at room temperature (20-22oC). After the whole-cell configuration was established, the cell was perfused with extracellular solution for ~13 minutes allowing the current to stabilize, and then moved into either control or drug-containing extracellular solution emitted from the application pipette using the Fast-Step Perfusion system (SF-77B, Warner Instrument Corporation, Hamden, USA). Voltage-step protocols were applied by an Atari (TT030) computer-controlled Axopatch 200A amplifier. The membrane capacitance was read from the amplifier dials and used to indicate membrane surface. Compensation circuitry was used to reduce the series resistance error by at least 75%. The holding membrane potential was set at 70 mV and currents were sampled at a frequency of 5 kHz and analyzed using custom-made software. Each protocol (lasting 2-2.5 min) was performed at least twice in each (control or drug-containing) extracellular solution. The control extracellular solution was applied before and after drug-containing solution to control the stability of the voltage dependence properties in particularly when estimating drug effects. Preferably, more than one concentration per cell was tested (with a maximum of four concentrations per cell). HEK cells are electrotonically compact and rarely escape voltage-clamp. Only cells that showed little current rundown over the recording time, were incorporated in the analysis. The currents were corrected off-line for linear non-specific leak and residual capacitive current.

Drugs and reagents. CBZ, DPH (Sigma) and LTG (Glaxo Wellcome) were dissolved in dimethylsulfoxide (DMSO, Sigma) to make stock solutions of respectively 400 mM, 100 mM and 333 mM. They were then diluted in extracellular solution to reach their final concentrations; DMSO concentrations in CBZ, DPH and LTG containing solutions were respectively 0.05%, 0.2% and 0.3%, for which concentration no effect on Na+ currents could be demonstrated.

Data analysis. Data are given as the mean standard error of the mean (S.E.M). Multiple groups were compared using an (one or two factor) ANOVA followed by a post-hoc Fisher test. Unless otherwise stated, Students t-test was used for the direct comparison of two groups of parameters. P < 0.05 was considered to indicate a significant difference.


29

Results

Biophysical analysis of Na+ currents carried by the NaV1.1, NaV1.2, NaV1.3 and NaV1.6 -subunits expressed in HEK293 cells. Whole-cell voltage clamp recordings were made of voltage-activated Na+ currents in HEK293 cells expressing the NaV1.1, NaV1.2, NaV1.3 or NaV1.6 -subunits. Na+ currents were activated by 25-ms depolarization steps to levels between 70 mV and +10 mV from a pre-pulse potential of 120 mV (inset of Fig. 1Aa). The depolarization activated a fast, transient inward Na+ current that increased in amplitude as the channels open with steps to higher potentials and then decreased at even higher potentials due to the reduced driving force (Fig. 1 Aa). We determined the peak amplitude of the current for each step and constructed current-voltage relationships for the four -subunits which were fitted to the Goldman-Hodgkin-Katz current equation (Hille, 2001) using a Boltzmann function to describe the sodium permeability as a function of membrane voltage (V):

( ) )exp(1)exp(][][

exp1 F P)( 0

VVNaNaVVI outin

VVV

c

h

+

=

++

Eq 1

With = F/RT where P0 is the maximal permeability of the channel, F is the Faraday constant, R the gas constant and T represents the absolute temperature. The voltage dependence of the conductance is described with a Boltzmann term characterized by the potential of half-maximal activation (Vh) and a slope parameter (Vc). For practical measurements we prefer to substitute gmax = P0 F [Na+]out where gmax is the maximal membrane conductance. The I-V curves in Fig. 1Ab are fits to the mean data points, but these fits were also performed on the data points measured in the individual cells and the resulting average Vh, Vc and Gmax values for the different subunits can be found in Table 1. In general the Vh and Vc values of the four subunits are in the same range, although the difference of the Vh values for activation and inactivation (Vh) of NaV1.1 is smaller than that of the other three subunits (Students t-test, p

Chapter 3

30

each cell) were constructed by determining the product of the activation and inactivation functions (Fig. 2), using the Vh and Vc parameters for activation and inactivation. In Fig. 2A as example the activation and inactivation curves of subunit NaV1.1 are shown. The inactivation curve (i.e. the available fraction) is the same as in Fig. 1B and the

0

0.2

0.4

0.6

0.8

1

-120 -100 -80 -60 -40

NaV1.1

NaV1.2

NaV1.3

NaV1.6

Avai

labl

e Fr

actio

n

Voltage (mV)

-7

-6

-5

-4

-3

-2

-1

0

NaV1.1

NaV1.2

NaV1.3

NaV1.6

-80 -60 -40 -20 0 20

Am

plitu

de (n

A)

Voltage (mV)

3 nA

5 ms

3 nA

5 ms

-35 mV

-70 mV

-150 mV500 ms

-10 mV25 ms

A

B

-70 mV

10 mV

500 ms

25 ms

-120 mV

a b

a b

Figure 1. Voltage-dependent activation and steady-state inactivation of Na+ currents carried by human Na+ channel -subtypes (Nav1.1, Nav1.2, Nav1.3 and Nav1.6) expressed in HEK293 cells. A, Voltage-dependence of activation. (a), Example traces of voltage-activated NaV1.3 Na+ currents. Na+ currents were activated by 25-ms depolarizing voltage steps ranging from 70 mV to +10 mV, following a 500-ms hyperpolarizing pre-pulse to 120 mV (protocol given as inset). (b), The mean peak amplitudes of the Na+ currents carried by the four -subunits are plotted as a function of membrane potential and fitted with the Goldman-Hodgkin-Katz current equation (Eq. 1). These fits to the averaged data points resulted in the following values for Vh and Vc, respectively: NaV1.1, 30.5 0.4 mV and 5.3 0.3 mV (n=8); NaV1.2, 28.6 0.3 mV and 5.4 0.3 (n=36); NaV1.3, 27.0 0.5 mV and 5.3 0.3 mV (n=30); NaV1.6, 26.6 0.3 mV and 5.4 0.3 mV (n=10). B, Voltage-dependence of steady-state


31

inactivation. (a), Example traces of voltage-inactivated NaV1.3 Na+ currents. Na+ currents were evoked with a step depolarization to 10 mV for 25-ms following a 500-ms hyperpolarizing pre-pulse between 150 mV and 35 mV (protocol given as inset). The fraction available current was defined as the normalized peak current (relative to the current amplitude evoked with an inactivating pre-pulse at 150 mV), plotted as a function of membrane potential and fitted with a Boltzmann function (Eq. 2) (b). These fits to the averaged data points resulted in the following values for Vh and Vc, respectively: NaV1.1, 63.4 0.5 and 6.7 0.4 (n=8); NaV1.2, 69.5 0.6 mV and 9.0 0.5 mV (n=36); NaV1.3, 68.1 0.5 mV and 8.2 0.4 mV (n=30); NaV1.6, 66.6 0.5 mV and 7.5 0.4 mV (n=10). Error bars indicate S.E.M.

activation curve is the fitted Boltzmann term from equation 1, which reflects the open fraction of Na+ channels immediately after depolarization to the specific voltage. The resulting mean window currents (Fig. 2B) indicate that the -subunit NaV1.1 is capable of generating a window current that is present over a relatively wide voltage range as compared to the other three subunits. This is also reflected by the smaller Vh value found for the NaV1.1 current (Table 1). Table 1. Activation and steady-state inactivation properties of Na+ currents carried by NaV1.1, NaV1.2, NaV1.3 and NaV1.6 -subunits expressed in HEK293 cells Activation Inactivation

Subtype

Vh (mV) Vc (mV) Gmax(nS)

Vh (mV) Vc (mV)

Vh (mV)

NaV1.1 29.91.7 (8)

4.70.3 (8)

181.5 21.4 (8)

63.21.6 (8)

5.90.6 (8)

33.21.5

(8)

NaV1.2 28.90.9

(36) 4.70.1

(36)

185.7 15.2 (36)

68.61.4 (36)

6.60.2 (36)

40.41.1**

(36)

NaV1.3 27.40.9 (30)

4.40.4 (30)

231.520.1 (30)

67.41.0 (30)

6.90.2 (30)

39.70.9**

(30)

NaV1.6 25.51.1 (10)

5.40.2 (10)

101.814.6 (10)

65.91.0 (10)

6.70.2 (10)

40.01.0**

(10)

Cell numbers are given in brackets. **p

Chapter 3

32

0.0

0.2

0.4

0.6

0.8

1.0

0.0

0.2

0.4

0.6

0.8

1.0

-120 -100 -80 -60 -40 -20 0

activationinactivationAv

aila

ble

fract

ion

Voltage (mV)

Open fraction

NaV1.1

-0.02

-0.015

-0.01

-0.005

0

NaV1.1

NaV1.2

NaV1.3

NaV1.6

-100 -80 -60 -40 -20 0 20

Am

plitu

de (n

A)

Voltage (mV)A B

Figure 2. Construction of the window current carried by the NaV1.1, NaV1.2, NaV1.3 and NaV1.6 -subunits. A, Activation and steady-state inactivation curves of the NaV1.1 current. The activation curve is given by the Boltzmann term of equation 1, the inactivation curve is the same as in Fig. 1Bb. B, The absolute window current carried by the four -subunits was constructed as the product of the inactivation and activation function (see A). Compared with the other three -subunits the window current carried by the NaV1.1 -subunits is active over a wider voltage range.

Next the time course of the recovery from inactivation of the Na+ current was

determined using a double-pulse protocol (inset of Fig. 3A). The interval t (during which the current was allowed to recover) between two 25-ms depolarization steps (to10 mV) was varied between 1 and 200 ms. The recovery time constant was determined at membrane voltages of 80, 90 and 100 mV. The amplitude of the Na+ current activated by the second pulse is plotted as a function of t and fitted with a single-exponential function (Fig. 3Ad) of the form:

=

ttR exp1)( Eq. 3

where is the time constant. The average values estimated for the four -subunits are presented in Fig. 3B where it can be seen that the recovery from inactivation is voltage- and subunit-dependent (two-factor ANOVA, p


33

t = 100 ms

30 ms1 nA

t = 20 ms

t = 2 ms

-80 mV

-10 mV25 ms 25 ms

t = 1~200ms

-90 mV-100 mV

0

5

10

15

20

25

30

35

-80 -90 -100

NaV1.1

NaV1.2

NaV1.3

NaV1.6

Tim

ce c

onst

ant (

ms)

Voltage (mV)

****

**

**

******

**

*

*

^^

^^

^^^^

**

-6

-5

-4

-3

-2

-1

00 50 100 150 200

Am

plitu

de (n

A)

Interval (ms)

V = -80 mV

a

b

c

d

A

B

Figure. 3. Voltage dependence of recovery from inactivation of Na+ currents carried by NaV1.1, NaV1.2, NaV1.3 and NaV1.6 -subunits expressed in HEK293 cells. A, The time course of recovery from inactivation was determined by a double-pulse protocol (given as inset). The variable pulse interval (t = 1, 2, 5, 10, 20, 50, 100 or 200 ms, during which the current was allowed to recover) between two 25-ms depolarizing voltage steps to 25 mV was used to determine the recovery from inactivation at the membrane voltages 80 mV, 90 mV, and 100 mV. Example traces of NaV1.3 currents activated by double pulses with different pulse intervals are shown in (a) (t = 100 ms), (b) (t = 20 ms) and (c) (t = 2 ms). With longer inter-pulse duration more channels recover from inactivation. (d), The amplitude of the Na+ current (recorded from a cell expressing the NaV1.3 -subunit) activated by the second pulse was plotted as a function of t and fitted

Chapter 3

34

with a single-exponential function to give the time constant of recovery from inactivation (Tau, at membrane potential 80 mV). B, Tau values of NaV1.1 (n = 5-6), NaV1.2 (n = 23-26), NaV1.3 (n = 30-33) and NaV1.6 (n = 7-9) currents at the three membrane voltages. The recovery form inactivation was voltage- and subunit-dependent (two-factor ANOVA, p


35

Figure 4. Frequency-dependent block by CBZ and LTG of Na+ currents carried by NaV1.1, NaV1.2, NaV1.3 and NaV1.6 -subunits expressed in HEK293 cells. A, Examples of pulse-activated Na+ current traces (evoked with 20 3-ms voltage steps to 10 mV; pulse interval at 80 mV was 20 ms) recorded from a cell expressing the NaV1.1 -subunit before (a), during (b) and after CBZ (50 M) (c) application. Protocol is given as inset (pulse interval at 80 mV was 20 ms (50 Hz) or 100 ms (10 Hz); the protocol was repeated every 5 s). (d) The CBZ-blocked Na+ current amplitudes (i.e. difference of control and CBZ current amplitude) were plotted against the stimulation time and fitted with a mono-exponential equation to yield the time constant describing the rate at which CBZ develops (164 ms in this particular example). B, Time constants describing the development of CBZ (50 and 200 M) block of Na+ currents evoked with the 10 or 50 Hz stimulation protocol for all four -subunits (n=5-10). C, Frequency

Control

100 ms

2 nA

50 M CBZ Wash

-120 mV

-80 mV -80 mV

-10 mV3 ms

x 19

t = 20, 100 ms

t0

0.5

1

1.5

2

0 100 200 300 400 500

Bloc

ked

Cur

rent

(nA)

Time (ms)

= 164 ms

50 M CBZ, 50 Hz

0

100

200

300

400

10 Hz 50 Hz 10 Hz 50 Hz

NaV1.1

NaV1.2

NaV1.3

NaV1.6

Tim

e co

nsta

nt (m

s)

50 M [CBZ] 200 M

ac

ac

ac

ac

ac

bc

bc

bc

****

***

***

ac

ac

ac

bc

0

2

4

6

8

50 M 200 M

NaV1.1

NaV1.2

NaV1.3

NaV1.6

tau 1

0 / ta

u 50

[CBZ]

Aa b c

B C

D

0

200

400

600

800

1000

1200

1400

10 Hz 50 Hz 10 Hz 50 Hz

NaV1.2

NaV1.3

Tim

e co

nsta

nt (m

s)

30M [LTG] 300M

ac

ac

a

ac

b

cb

**

0

2

4

6

8Na

V1.2

NaV1.3

tau 1

0/ta

u 50

[LTG]30M 300M

****

**

E

d

Chapter 3

36

sensitivity of CBZ block (ratio of tau10 and tau50 values from B) for 50 and 200 M CBZ for the four -subunits (n=5-10). D, Time constants describing the development of LTG (30 and 300 M) block of Na+ currents evoked with the 10 or 50 Hz stimulation protocol for the NaV1.2 and NaV1.3 -subunits (n=6-7). E, Frequency sensitivity of LTG block (ratio of tau10 and tau50 values from D) for 30 and 300 M LTG for the NaV1.2 and NaV1.3 -subunits (n=6-7). Both drugs showed a frequency and concentration-dependent block (multi-factor ANOVA, p


37

addition, EC50 values for CBZ and DPH were for the NaV1.2 and NaV1.3 subunits in the same range (50-90 M), whereas that of LTG was for both subunits ~200 M (differences for CBZ and DPH vs. LTG p

Chapter 3

38

fitted with a logistic function (see inset; eq. 3). B, The Vh induced by CBZ (10, 20, 50, 100 and 200 M), LTG (10, 30, 100, 300 and 1000 M) and DPH (10, 20, 50, 100 and 200 M) on NaV1.2 currents (n=5-14). The EC50 and Vh values obtained by fitting the data point to a logistic equation (eq. 3) are given in the table inset. Values with similar letter superscripts designate a statistical significance (EC50: a and b indicate p


39

Binding rates of AEDs to inactivated NaV1.1, NaV1.2, NaV1.3 and NaV1.6

-subunits. Differences in AED efficacy in treating the various forms of epilepsy can possibly be explained by differences in binding rates onto the Na+ channels. Experiments were performed to determine the binding rates at which AEDs bind to the inactivated Na+ channel subtypes by using a voltage protocol described in Fig. 7 (Kuo and Lu, 1997). With such a protocol the channels were exposed to a depolarizing voltage step (to 40 mV) of different durations (30 2500 ms) (inset Fig. 7A). Longer depolarizing voltage steps allow more channels to enter the inactivated state and due to the much higher affinity of AEDs for this state more channels will be blocked (Fig. 7A). A 5-ms repolarization step to 120 mV (following the prepulse) was applied to allow the fraction of channels not blocked by the AED to recover from inactivation. In these experiments the current amplitude in the presence of AED was subtracted from control current amplitude, yielding the amplitude of the blocked current. This procedure also corrected for a reduction in current amplitude due to a slow inactivation process (Fig. 7Aa). The blocked current amplitude was expressed as function of the prepulse duration and fitted with a mono-exponential function (eq. 3) (Fig. 7B). For each tested concentration this yielded a time constant describing the time course during which channel block developed. By taking the reciprocal of this time constant the binding rate at each concentration was determined. The binding rates were plotted as function of AED concentration and the slope of the fitted linear relationship equals the so-called binding rate constant (Fig. 7C). The binding rate constants of CBZ, LTG and DPH were determined for the NaV1.2 and NaV1.3 subunits and it appeared that the CBZ binding rate constant was approximately three times faster than that of LTG and DPH (p

Chapter 3

40

(Fig. 8B). When comparing CBZ and LTG, we observed for the NaV1.2 and NaV1.3 subunits that the CBZ off rate is much faster than that of LTG (p


41

presence of DPH and was plotted against t. The data points were fitted with a mono-exponential function to determine the time constant (Tau) for development of block in the presence of 10, 20, 50, 100 and 200 M DPH. C, The binding rates (1/Tau, s-1) in NaV1.3 cells are plotted against the DPH concentration. The slope of the linear regression gives the binding rate constant of 7300 M-1s-1 to Nav1.3 for DPH (n = 8). D, Comparison of the binding rate constants of CBZ, DPH and LTG for the -subunits NaV1.1, NaV1.2, NaV1.3 and NaV1.6; these values were determined with the procedure described in A-C. The binding of CBZ to NaV1.3 (45.5 5.9 mM-1s-1, n=5) is slower than to the other three -subunits (NaV1.1: 62.3 6.8 mM-1s-1, n=8; NaV1.2: 75.1 6.2 mM-1s-1, n=5; NaV1.6: 62.1 10.1 mM-1s-1, n=5). Also LTG (12.3 0.8 mM-1s-1, n=5) and DPH (7.3 1.4 mM-1s-1, n=8) binding to NaV1.3 are slower than that to NaV1.2 (21.0 2.7 mM-1s-1 (n=6) and 12.9 2.1 M-1s-1 (n=6), respectively). Furthermore, CBZ binding to NaV1.2 and NaV1.3 is faster than that of LTG and LTG binding to NaV1.2 and NaV1.3 is faster than that of DPH. Error bars indicate S.E.M. * indicates p

Chapter 3

42

at 40 mV for 2000 ms to permit drug binding to the inactivated channels, followed by a step to a recovery potential at 120 mV with a variable time duration t to facilitate channels to recover from inactivation and to allow drug dissociation. The whole protocol (shown as inset) was repeated every 5 s. The blocked current was determined by subtracting the control current (measured in the absence of CBZ) from the current recorded in the presence of CBZ and plotted against the time duration of the recovery t (c). The data points were fitted wi

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