TITLE model of GABAB receptors
COMMENT
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Kinetic model for GABA-B receptors
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Model of GABAB currents including nonlinear stimulus
dependency (fundamental to take into account for GABAB receptors).
Features:
- peak at ~200 ms after burst activation (5@50 Hz); time course fit from experimental IPSPs recorded by J. Schulz
- NONLINEAR SUMMATION (psc is much stronger with bursts)
due to cooperativity of G-protein binding on K+ channels
Approximations:
- single binding site on receptor
- model of alpha G-protein activation (direct) of K+ channel
- G-protein dynamics is second-order; simplified as follows:
- saturating receptor
- no desensitization
- Michaelis-Menten of receptor for G-protein production
- "resting" G-protein is in excess
- Quasi-stat of intermediate enzymatic forms
- binding on K+ channel is fast
Kinetic Equations of model:
dT/dt = -T/tauD -k1 * T * (Bm - B) + k_1 * B
dB/dt = k1 * T * (Bm - B) - (k_1 + k2) * B
dR/dt = K1 * T * (1-R) - K2 * R
dG/dt = (K3 * R * (1-G) - K4 * G) *f
R : fraction activated receptor
T : transmitter
B : GABA transporter
G : fraction activated G-protein
K1,K2,K3,K4 = kinetic rate cst; from Thomson & Destexhe, 1999, Fig. 15 for n=2
k1,k_1,k2 = kinetic rate cst; from Thomson & Destexhe, 1999
tauD : decay due to diffusion; from Sanders et al., 2013
f : factor f to G protein control dynamics
f and K2 adjusted to reach max amplitude ~200 ms after burst start (5@50 Hz)
n activated G-protein bind to a K+ channel:
n G + C <-> O (Alpha,Beta)
If the binding is fast, the fraction of open channels is given by:
O = G^n / ( G^n + KD )
where KD = Beta / Alpha is the dissociation constant
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Also see details in:
Destexhe, A. and Sejnowski, T.J. G-protein activation kinetics and
spill-over of GABA may account for differences between inhibitory responses
in the hippocampus and thalamus. Proc. Natl. Acad. Sci. USA 92:
9515-9519, 1995.
Thompson, A.M. and Destexhe, A. DUAL INTRACELLULAR RECORDINGS AND COMPUTATIONAL
MODELS OF SLOW INHIBITORY POSTSYNAPTIC POTENTIALS IN RAT NEOCORTICAL AND HIPPOCAMPAL
SLICES. Neuroscience 92: 1193-1215, 1999.
Sanders, H., Berends, M., Major, G., Goldman, M.S. and Lisman, J.E. NMDA and
GABAB (KIR) conductances: the "perfect couple" for bistability. J Neurosci 33(2): 424-9, 2013.
Taken from Poirazi, Brannon & Mel. Arithmetic of Subthreshold Synaptic
Summation in a Model CA1 Pyramidal Cell. Neuron 2003 (Originally written by Alain Destexhe, Laval University, 1995)
Modified by J. Schulz according to Thompson & Destexhe (1999) and Sanders, Berends et al. (2013)
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ENDCOMMENT
NEURON {
POINT_PROCESS GABABsyn
RANGE C, R, G, B, g, gmax, tauD
NONSPECIFIC_CURRENT i
RANGE vgat,sst,npy,pv,xEff
RANGE isOn
GLOBAL K1, K2, K3, K4, KD, k1, k_1, k2, e, Bm
}
UNITS {
(nA) = (nanoamp)
(mV) = (millivolt)
(molar) = (1/liter)
(mM) = (millimolar)
(uS) = (microsiemens)
}
PARAMETER {
tauD = 10 (ms) : decay of transmitter concentration
K1 = 0.066 (/ms mM) : forward binding rate to receptor
K2 = 0.008 (/ms) : backward (unbinding) rate of receptor
K3 = 0.27 (/ms) : rate of G-protein production
K4 = 0.044 (/ms) : rate of G-protein decay
KD = 0.5 : half maximal coductance at a level of ~0.7 activated G-protein
n = 2 : nb of binding sites of G-protein on K+
e = -95 (mV) : reversal potential (E_K)
gmax (uS) : maximum conductance
f = 0.1 : factor f controlling the G protein dynamics
k1 = 30 (/ms mM) : 30, forward binding rate to transporter
k_1 = 0.1 (/ms) : backward (unbinding) rate of transporter
k2 = 0.02 (/ms) : clearance of GABA
Bm = 1 (mM) : maximum binding capacity of transporter
vgat=0
sst=0
npy=0
pv=0
xEff=-1
isOn=0
}
ASSIGNED {
v (mV) : postsynaptic voltage
i (nA) : current = g*(v - e)
g (uS) : conductance
Gn
}
STATE {
C (mM) : extracellular transmitter concentration
R : fraction of activated receptor
G : normalized concentration of activated G-protein
B (mM) : bound GABA transporter
}
INITIAL {
C = 0
R = 0
G = 0
B = 0
}
BREAKPOINT {
SOLVE state METHOD cnexp
Gn = G^n
g = isOn * gmax * Gn / (Gn+KD)
i = g *(v - e)
}
DERIVATIVE state {
C' = (-C/tauD -k1 * C * (Bm - B) + k_1 * B)
R' = (K1 * C * (1-R) - K2 * R)
G' = (K3 * R * (1-G) - K4 * G) * f
B' = (k1 * C * (Bm - B) - (k_1 + k2) * B)
}
NET_RECEIVE(weight (mM)) {
C = C + weight
}