Department of Physiology and Biophysics, Mount Sinai School of Medicine, One Gustave Levy Place, New York, NY 10029, USA
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Abstract |
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Keywords: coupling efficiency/G protein coupling surface/implicit solvent model/loop conformation/Monte Carlo simulation
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Introduction |
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Materials and methods |
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The conformational space of the loops was explored with a modified version of the biased Monte Carlo method described earlier, the Conformational Memories (CM) method (
Guarnieri and Wilson, 1995
;
Guarnieri and Weinstein, 1996
). The method was modified with the inclusion of a new implicit solvent model described below. Briefly, the application of the CM technique involves a two-stage process consisting of an exploratory phase and a biased sampling phase. In the exploratory phase, several Monte Carlo-simulated annealing (MC/SA) runs are performed to a final temperature of 300 K. For the peptides studied here, the starting temperature was sufficiently high (3000 K) to guarantee randomization of the starting structures. The cooling schedule was
T
n
+ 1
= 0.9
T
n
and the interval of temperatures was divided into 18 steps; 10
4
trial moves per temperature were generated. The trial conformations were obtained by randomly picking two rotatable dihedral bonds and assigning random values between ±180° (peptide bonds were considered fixed at 180° throughout the simulation). Acceptance of a trial conformation followed the standard Metropolis algorithm with a Boltzmann distribution. After several runs have been performed, a probability distribution of each torsional angle in the mean field of all other rotatable bonds can be obtained at the lower temperature. The number of MC runs is determined by a convergence criterion of the probability distributions (
Guarnieri and Weinstein, 1996
). These distributions are used in the second phase of the simulation, in which the Monte Carlo sampling only explores the populated regions of the conformational space weighted by the probability distribution generated in the first stage (
Guarnieri and Weinstein, 1996
). In the second stage, the ensemble of structures at
T
= 300 K is obtained from a second simulated annealing process.
The solvent environment model
The aqueous environment of IL2 in the cytoplasmic compartment was modeled with a recently developed implicit solvent model that is based on a screened Coulomb potential formulation (the SCP-ISM) (Hassan et al.2000a
,
b
). In this model, the Coulomb interaction among particles is screened by a distance-dependent dielectric function of sigmoidal form. The SCP-ISM introduces the self-energy of the atoms as derived from the integral form of the Born equation and makes use of a novel approach to describe the Born radii of atoms in the protein environment. An algorithm for hydrogen bonding interaction is incorporated, which is based on the degree of exposure of the polar hydrogens to the proton acceptor environment. The model was implemented in the CHARMM package (Brooks et al.1983
) and parameterized in the context of the all-atom PAR22 force field of CHARMM. As implemented in the biased sampling Monte Carlo, this SCP-ISM was shown to predict with accuracy the most favorable conformation of peptides in water (Hassan et al.2000a
,
b
).
Loop conformation in the context of the molecular model of the receptor
The simulations were performed with the IL2 loop anchored to the cytoplasmic ends of TM3 and TM4 in a model of the transmembrane bundle of 5HT
2C
. The spatial relative orientation of the helices is taken from a 3D model of the 5HT
2C
receptor constructed as described elsewhere (
Ballesteros and Weinstein, 1995
), using a template described by Baldwin (Baldwin et al.1997
) according to the density map from cryo-electronmicroscopy for rhodopsin (Unger et al.1997
). This model is characterized by a number of structural motifs consisting of spatially adjacent residues that adopt specific interaction patterns. These structural motifs have been shown to constitute functional microdomains (Ballesteros et al.1998
) and the network of interactions that stabilizes the structural pattern of these motifs (Sealfon et al.1995
; Ballesteros et al.1998
; Konvicka et al.1998
) have been confirmed recently by the breakthrough X-ray structure of rhodopsin (Palczewski et al.2000
). These key features of the receptor model that were confirmed by the crystal structure include (1) the hydrogen bonding network between the conserved N1.50 (asparagine 55 in rhodopsin) and the H-bonded region of interaction between TM2 and TM7 (compare Figures 7 and 8 in Konvicka et al.1998 with Figure 5C
in Palczewski et al.2000)a spatial adjacency that has been verified experimentally in many GPCRs (Sealfon et al.1995; Flanagan et al.1999; and references therein); (2) the `arginine cage' motif at the cytoplasmic end of TM3 that involves the highly conserved DRY sequence (Ballesteros et al.1998
) which brings together the ends of TM3 and TM6 in the `inactive' state of the receptor through an H-bonding interaction between D3.49 (corresponding to E134 in rhodopsin), R3.50 (R135 in rhodopsin) and E6.30 (E247 in rhodopsin), as seen from the comparison of
Figure
2
in Ballesteros
et al.
(1998) and
Figure
5D
in Palczewski
et al.
(2000).
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Geometrical description of the conformational space
In order to define quantitatively the conformational space accessible to the loops in the context of the receptor model, we defined a set of geometrical parameters described in
Figure
2A
and
B
. The coordinates of two fixed points corresponding to the C
atoms of R168 and A155 are defined as points P
1
and P
2
, respectively (Figure 2A
). The axis of TM4, characterized by vector
a
, defines an orientation perpendicular to the plane of the membrane. The middle point of the segment P
1
P
2
defines the point M.
Figure
2B
shows a schematic representation of the geometrical parameters, with the plane of the membrane (perpendicular to TM4) represented by an ellipse. For the sake of clarity the vector
a
defining the TM4 axis is translated to point M that is considered the origin of the coordinates system. The cross product
P
1
x
a
yields vector
R
o
that is perpendicular to both and thus contained in the ellipse that represents the plane of the membrane. To describe the conformational variations, a variable vector
P
3
is defined, where point P
3
is chosen to correspond to the position of the C
of residue 164 (see Figure 2
) whose position changes for each conformation. The cross product
P
3
x
a
yields vector
V
i
perpendicular to both and in the same plane as
R
o
. The angle
between the different
V
i
and
R
o
provides a measure of the space swept by the energetically accessible conformations of the loop, termed the `swing' of IL2 (Figure 4
).
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Results |
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The conformational studies were carried out for two 14-residue peptides that represent the loops of the fully edited and the unedited receptors (nine residues), flanked by three residues from TM3 and two from TM4. The peptide representing the unedited sequence (INI) is AIRNPIEHSRFNSR and for the edited sequence (VGV) the peptide is AVRGPVEHSRFNSR (see Figure 1
). Throughout the simulations, the orientation of fragments 155157 and 167168 are constrained with harmonic potentials to fit the orientations of TM3 and TM4 at their cytoplasmic ends that must remain helical. In addition, the inter-residue distances between the two helical fragments were restrained to the corresponding distance in the receptor model.
The MC/SA phase of the biased Monte Carlo simulation (see Materials and methods) comprises 50 runs. Each run of the MC/SA consists of a random walk of 180 000 steps. Each rotatable bond block is divided into 18 temperature blocks and the dihedral space is partitioned into 36 10° intervals with normalized populations. The spreadsheet including these data represents the dihedral distribution of a given torsional angle in the mean field of all other rotatable bonds. The data from these runs are sorted and merged into 78 blocks, one for each rotatable bond. The identification of the populated regions in the torsional angle space, the conformational memory (
Guarnieri and Weinstein, 1996
), is used in the second phase of the simulation in which biased sampling explores only the populated regions of the conformational space. In this second stage, the ensembles of the populated regions of the conformational structures at 300 K are obtained from a second simulated annealing starting from
T
= 834.8 K and cooling to 300 K, with sampling performed only from the populated regions of the conformational memories. Population convergence is considered when there is no significant difference in the populations of structures obtained by new independent MC/BS runs (the rate of convergence for the calculated angle
is illustrated in Tables I and II
).
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![]() | (1) |
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The results presented in
Figures
3
and
4
show that the ensemble of structures obtained for IL2 of the unedited and edited receptors cover different areas of the conformational space, but with considerable overlap. To quantify this comparison, the calculated angles
were binned into four regions comprising 25° each. The probability
P
i
(
) of finding a loop conformation in bin
i defined by
i
i
+ 25° is given by
![]() | (2) |
For the unedited receptor, the average value of the angle <> is 21.2°, with 41.7% of the structures falling in the narrow region between 25° and 0° (Table I
); the population of the same area in the edited receptor is only 31.1% (Table II
). Conversely, the average value of the angle in the edited receptor is <
> = 27.5° and the most populated region is between angles 50° and 25°, which contains 41.6% of the structures; the population of the same area in the unedited receptor drops to 30.5%. Note that the area corresponding to
> 0 is also larger in the unedited (18.5%) than in the edited IL2 loop (10.9%); see
Tables
I
and
II
.
When these results are put in the context of the receptor model (Figure 3
), the IL2 of the unedited (5HT
2C-INI
) receptor is seen to have a slightly larger population of structures oriented towards the TM7 bundle (the population with
> 0, which represents 18.5% of the total) than the 5HT
2C-VGV
edited receptor (10.9% of the population with
> 0). The schematic illustration in
Figure
3
shows that the IL2 conformations that are oriented towards the interior of the bundle, where the interaction surface with G proteins is likely to be located according to Fanelli
et al
. (Fanelli et al.1999a
, b
), also have greater spatial proximity to the region corresponding to the third intracellular loop, IL3.
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Discussion |
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The structures oriented towards the interior of the bundle would also have greater spatial proximity to the third intracellular loop whose role in G protein coupling has been described (Cheung et al.1992
). While the distribution of the edited loops overlaps the unedited version in some regions, there is a clear deviation away from the region of potential interactions with IL3. Given the experimental evidence for the role of both intracellular loops in G protein coupling, this difference may be responsible for the observation that the 5HT
2C-VGV
edited receptor couples less efficiently to G proteins while retaining
V
max
(Niswender et al.1999
). This relation between IL2 and IL3 in determining G protein coupling is suggested by experimental data for various GPCRs. Thus, peptides corresponding in sequence to the IL2 and IL3 of rhodopsin were shown to be involved in interaction with transducin and these peptides had synergistic effects when binding at their respective sites on the G protein transducin (Konig et al.1989
). Analogous conclusions were reached for the glucagon receptor (Cypess et al.1999
). Similarly, receptor chimera experiments on muscarinic and ß-adrenergic receptors have shown that specific IL2IL3 combinations are necessary for G protein selectivity (Wong et al.1988
). Our present results indicate that the likelihood for a direct interaction between IL2 and IL3 can depend on the conformational properties of IL2, which, in turn, have been shown to depend on the sequence of the loop. From the specific comparison performed here, the interaction between the two loops is predicted to be more favorable for the unedited IL2 loop whose population is higher in regions oriented towards IL3. Although neither the experimental data nor our schematic model demonstrate a direct interaction between these loops, our results suggest that the effects on G protein coupling properties of the compared receptors reflect the likelihood of a structural organization in which the two loops are proximal. In this context, our results provide a molecular basis for the observed synergism between the two loops and a mechanistic basis to explain why the edited 5HT
2C-VGV
receptor couples less efficiently to G proteins (Niswender et al.1999
).
It is noteworthy that the distribution of values for the different forms of the IL2 supports the hypothesis that even a small difference in loop orientation is sufficient to account for the observed reduction in G protein coupling. In this model, the reduction is achieved by disrupting the optimal orientation of IL2 relative to IL3 that is involved in their binding at the G protein. This implies a high sensitivity of the system to small changes in the interaction surface presented to the IL3 and/or the G protein. In the context of the whole activation mechanism process, a series of inter- and intramolecular interactions are required for the propagation of the signal from the binding site to the interaction surface with the intracellular components of the signal transduction pathway, such as the G protein (Ballesteros et al.1998
). We have described previously some of the structural motifs that are involved in the propagation of the signal (Almaula et al.1996a
,
b
; Gether et al.1997
; Ballesteros et al.1998
; Konvicka et al.1998
). These structural motifs constitute functional microdomains that connect directly to the structural determinants presented here for the role of intracellular loop 2.
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Notes |
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Acknowledgments |
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References |
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Received September 15, 2000; revised January 5, 2001; accepted March 17, 2001.