Huan-Xiang Zhou1. 1. Department of Physics and Institute of Molecular Biophysics, Florida State University , Tallahassee, Florida 32306, United States.
Abstract
Ionotropic glutamate receptors (iGluRs) are tetrameric ligand-gated ion channels essential to all aspects of brain function, including higher order processes such as learning and memory. For decades, electrophysiology was the primary means for characterizing the function of iGluRs and gaining mechanistic insight. Since the turn of the century, structures of isolated water-soluble domains and transmembrane-domain-containing constructs have provided the basis for formulating mechanistic hypotheses. Because these structures only represent sparse, often incomplete snapshots during iGluR activation, significant gaps in knowledge remain regarding structures, energetics, and dynamics of key substates along the functional processes. Some of these gaps have recently been filled by molecular dynamics simulations and theoretical modeling. In this Account, I describe our work in the latter arena toward characterizing iGluR gating motions and developing a formalism for calculating thermodynamic and kinetic properties of stationary gating. The structures of iGluR subunits have a highly modular architecture, in which the ligand-binding domain and the transmembrane domain are well separated and connected by flexible linkers. The ligand-binding domain in turn is composed of two subdomains. During activation, agonist binding induces the closure of the intersubdomain cleft. The cleft closure leads to the outward pulling of a linker tethered to the extracellular terminus of the major pore-lining helix of the transmembrane domain, thereby opening the channel. This activation model based on molecular dynamics simulations was validated by residue-specific information from electrophysiological data on cysteine mutants. A further critical test was made through introducing glycine insertions in the linker. Molecular dynamics simulations showed that, with lengthening by glycine insertions, the linker became less effective in pulling the pore-lining helix, leading to weaker stabilization of the channel-open state. In full agreement, single-channel recordings showed that the channel open probability decreased progressively as the linker was lengthened by glycine insertions. Crystal structures of ligand-binding domains showing different degrees of cleft closure between full and partial agonists suggested a simple mechanism for one subtype of iGluRs, but mysteries surrounded a second subtype, where the ligand-binding domains open to similar degrees when bound with either full or partial agonists. Our free energy simulations now suggest that broadening of the free energy basin for cleft closure is a plausible solution. A theoretical basis for these mechanistic hypotheses on partial agonisms was provided by a model for the free energy surface of a full receptor, where the stabilization by cleft closure is transmitted via the linker to the channel-open state. This model can be implemented by molecular dynamics simulations to predict thermodynamic and kinetics properties of stationary gating that are amenable to direct test by single-channel recordings. Close integration between computation and electrophysiology holds great promises in revealing the conformations of key substates in functional processes and the mechanisms of disease-associated mutations.
Ionotropic glutamate receptors (iGluRs) are tetrameric ligand-gated ion channels essential to all aspects of brain function, including higher order processes such as learning and memory. For decades, electrophysiology was the primary means for characterizing the function of iGluRs and gaining mechanistic insight. Since the turn of the century, structures of isolated water-soluble domains and transmembrane-domain-containing constructs have provided the basis for formulating mechanistic hypotheses. Because these structures only represent sparse, often incomplete snapshots during iGluR activation, significant gaps in knowledge remain regarding structures, energetics, and dynamics of key substates along the functional processes. Some of these gaps have recently been filled by molecular dynamics simulations and theoretical modeling. In this Account, I describe our work in the latter arena toward characterizing iGluR gating motions and developing a formalism for calculating thermodynamic and kinetic properties of stationary gating. The structures of iGluR subunits have a highly modular architecture, in which the ligand-binding domain and the transmembrane domain are well separated and connected by flexible linkers. The ligand-binding domain in turn is composed of two subdomains. During activation, agonist binding induces the closure of the intersubdomain cleft. The cleft closure leads to the outward pulling of a linker tethered to the extracellular terminus of the major pore-lining helix of the transmembrane domain, thereby opening the channel. This activation model based on molecular dynamics simulations was validated by residue-specific information from electrophysiological data on cysteine mutants. A further critical test was made through introducing glycine insertions in the linker. Molecular dynamics simulations showed that, with lengthening by glycine insertions, the linker became less effective in pulling the pore-lining helix, leading to weaker stabilization of the channel-open state. In full agreement, single-channel recordings showed that the channel open probability decreased progressively as the linker was lengthened by glycine insertions. Crystal structures of ligand-binding domains showing different degrees of cleft closure between full and partial agonists suggested a simple mechanism for one subtype of iGluRs, but mysteries surrounded a second subtype, where the ligand-binding domains open to similar degrees when bound with either full or partial agonists. Our free energy simulations now suggest that broadening of the free energy basin for cleft closure is a plausible solution. A theoretical basis for these mechanistic hypotheses on partial agonisms was provided by a model for the free energy surface of a full receptor, where the stabilization by cleft closure is transmitted via the linker to the channel-open state. This model can be implemented by molecular dynamics simulations to predict thermodynamic and kinetics properties of stationary gating that are amenable to direct test by single-channel recordings. Close integration between computation and electrophysiology holds great promises in revealing the conformations of key substates in functional processes and the mechanisms of disease-associated mutations.
Ionotropic glutamate
receptors (iGluRs) are tetrameric ligand-gated
ion channels. AMPA and NMDA receptors (AMPARs and NMDARs) are two
main subtypes of postsynaptic iGluRs, and mediate the vast majority
of fast excitatory neurotransmission in the vertebrate nervous system.
These receptors convert transient glutamate signals, arising from
presynaptic release, into postsynaptic electrical and biochemical
signals. The duration of glutamate-induced channel opening determines
the strength of synaptic connections between neurons and is critical
to neurodevelopment and higher order processes such as learning and
memory.[1] Recently, numerous missense mutations
of iGluRs, in particular NMDARs, have been associated with an array
of neurological disorders (e.g., autism, epilepsy, intellectual disability,
and schizophrenia).[2,3] Thus, deep understanding of iGluR
structure and function is critical to both basic and clinical neuroscience.Because of their physiological importance and pathophysiological
implications, iGluRs have been under intense investigations. AMPAR
subunits GluA1–4 form both homo- and heterotetramers, whereas
NMDARs form obligatory heteromers consisting typically of two GluN1
and two GluN2A-D subunits. Each subunit harbors an extracellular agonist-binding
site. Glutamate is the agonist for all AMPAR subunits and GluN2 subunits,
whereas glycine is the agonist for the GluN1 subunit. The central
mechanistic question is how agonist binding triggers the opening of
the ion channel in the cell membrane. For several decades before the
turn of the century, electrophysiology was the primary means for characterizing
the function of iGluRs and gaining mechanistic insight, both at synapses
and on reconstituted or expressed receptors.[4,5] Whole-cell
recordings of AMPARs show fast activation and deactivation as well
as rapid and strong desensitization. In contrast, NMDARs show relatively
slow gating kinetics, with weak or no desensitization depending on
the specific subunits (e.g., GluN2A versus GluN2C).Single-channel
recordings of AMPARs showed a channel-closed state
and up to four subconductance levels that were roughly separated by
quantized increments.[6−9] A simple kinetic model was proposed, where transitions occurred
only between adjacent conductance levels and occupancies of these
levels were binomial.[7] According to this
model, the four subunits open and close the channel independently
and contribute additively to the unitary current. However, more complex
behaviors were observed recently, including deviation from the binomial
distribution at subsaturating agonist concentrations,[8] varying subunit open probabilities in different segments
of a given current trace, and two to three substates within each conductance
level.[9] NMDARs again exhibit very different
behaviors in single-channel recordings.[10−13] A single conductance level was
observed, but lifetime distributions revealed multiple components
within both the channel-closed and open states. The prevailing model
for kinetic analysis of single-channel currents assumes five closed
substates and two open substates; three of the closed substates (C3, C2, and C1) and the two open substates
(O1 and O2) are connected sequentially, while
two longer lived substates (C5 and C4) branch
off from C3 and C2, respectively.[12,14−19]It has long been known that iGluR subunits have a modular
architecture
containing four distinct structural domains (Figure ): extracellular amino-terminal (ATD) and
ligand-binding (LBD) domains; a transmembrane domain (TMD) forming
the ion channel upon tetramer assembly, with the M3 helix lining the
channel pore and harboring the activation gate near the helix C-terminus;
and an intracellular, disorderedC-terminal domain (CTD).[20] The first structure of an isolated LBD, that
of GluA2 bound with a partial agonist, was determined in 1998 by X-ray
crystallography, identifying the ligand binding site within the cleft
between two subdomains (referred to as D1 and D2).[21] Since then crystal structures of GluA2 LBDs bound with
an assortment of ligands have been deposited in the Protein Data Bank
(PDB), reaching an astounding total of 153 entries at present. Interestingly,
AMPAR full agonists induce tight closure of the LBD clefts, partial
agonists induce intermediate closure, and competitive antagonists
lead to wide clefts, suggesting a correlation between degree of LBD
closure and agonist efficacy.[7,22] Another interesting
observation is that ligand size apparently dictates the degree of
AMPAR LBD closure (Figure ): small ligands, usually agonists, fit snugly in a tightly
closed cleft, whereas large ligands, usually antagonists, pry open
the cleft.[23] In 2009, the first crystal
structure of a CTD-truncated GluA2 AMPAR bound with a competitive
antagonist was published (PDB 3KG2; Figure ).[24] This structure confirmed
the highly modular architecture of iGluR subunits, with well-separated
ATD, LBD, and TMD connected by flexible linkers. By superimposing
the D1 subdomains of an isolated LBD bound with glutamate, it was
possible to imagine how agonist-induced D2 closure upon D1 could lead
to an outward movement of the M3 helix.
Figure 1
Modular architecture
of iGluRs. (A) Domains within a GluA2 subunit
(CTD missing). Subdomains of the ATD (L1/2) and LBD (D1/2) and transmembrane
helices of the TMD (M1/3/4) are indicated; a bound ligand is shown
in space-filling mode and the M3-D2 linker is in green. Inset: enlarged
view of the region around the linker. (B) Subunit organization within
the homotetramer (PDB 3KG2).[24] The A, B, C, and D
subunits are in marine, magenta, light blue, and light pink, respectively.
In NMDARs, the A/C and B/D subunits are GluN1 and GluN2, respectively.
Figure 2
Ligand size as a determinant for the degree
of GluA2 LBD closure
and agonist efficacy. (A) Superposition of an agonist-bound GluA2
LBD structure (PDB 1M5C; red) and an antagonist-bound structure (PDB 3R7X; blue). The D1 subdomain
is used for superposition. Cα atoms of K410 in D1 (dark red)
and K695 in D2 (light red), used for defining the distance dK410–K695, are shown as yellow spheres.
(B) Histograms of AMPAR agonists, partial agonists, and competitive
antagonists binned according to dK410–K695. (C) Correlation between dK410–K695 and ligand molecular weight, with R2 = 0.58. Reproduced with permission from ref (23). Copyright 2012 Elsevier.
Modular architecture
of iGluRs. (A) Domains within a GluA2 subunit
(CTD missing). Subdomains of the ATD (L1/2) and LBD (D1/2) and transmembrane
helices of the TMD (M1/3/4) are indicated; a bound ligand is shown
in space-filling mode and the M3-D2 linker is in green. Inset: enlarged
view of the region around the linker. (B) Subunit organization within
the homotetramer (PDB 3KG2).[24] The A, B, C, and D
subunits are in marine, magenta, light blue, and light pink, respectively.
In NMDARs, the A/C and B/D subunits are GluN1 and GluN2, respectively.Ligand size as a determinant for the degree
of GluA2 LBD closure
and agonist efficacy. (A) Superposition of an agonist-bound GluA2
LBD structure (PDB 1M5C; red) and an antagonist-bound structure (PDB 3R7X; blue). The D1 subdomain
is used for superposition. Cα atoms of K410 in D1 (dark red)
and K695 in D2 (light red), used for defining the distance dK410–K695, are shown as yellow spheres.
(B) Histograms of AMPAR agonists, partial agonists, and competitive
antagonists binned according to dK410–K695. (C) Correlation between dK410–K695 and ligand molecular weight, with R2 = 0.58. Reproduced with permission from ref (23). Copyright 2012 Elsevier.At present the PDB contains 44
entries for isolated LBDs of NMDARs,
but surprisingly, they have similar degrees of closure whether bound
with full or partial agonists (although competitive antagonists still
induced wide cleft opening).[25−28] That the crystal structures do not offer a clue to
NMDAR partial agonism is a manifestation of their limits in providing
mechanistic insights. There are now also 44 PDB entries of crystal
and single-particle electron cryomicroscopy (cryoEM) structures for
CTD-truncated AMPARs and NMDARs (for a recent review, see ref (29)). These structures putatively
represent different functional states, but while the water-soluble
domains (ATD and LBD) display ligand-induced structural changes, none
of them has captured an open conformation for the ion channel in the
TMD layer. The inability to capture the open channel could be due
to the strong influence of the solubilizing environment on TMD structures
and the fact that solubilizing conditions in sample preparations for
crystal and cryoEM structure determination often do not model well
the key biophysical properties of cell membranes.[30] If it is challenging for structural techniques to capture
stable functional states, then the challenge is much greater for shedding
light on conformations of the kinetic substates that have been identified
by single-channel recordings. This lack of atomic-level structural
information has been a tremendous impediment to progress in iGluR
physiology and pathophysiology.In this Account, I describe
our recent studies to highlight the
contributions of molecular dynamics (MD) simulations and theoretical
modeling in filling some of the gaps in knowledge regarding iGluR
structure and function. In particular, based on MD simulations we
have developed an activation model in which the M3-D2 linkers play
crucial and subunit-specific roles.[18,31,32] Our free energy simulations have supported the hypothesis
that, whereas a reduced degree of LBD closure, corresponding to a
shift in the minimum position of the LBD free energy basin, may underlie
AMPAR partial agonism, a reduced curvature of the LBD free energy
basin may lead to NMDAR partial agonism.[33] To further interrogate this hypothesis, we have formulated a theoretical
model for calculating iGluR thermodynamic and kinetic properties during
stationary gating.[34] This theoretical model
points to the exciting prospect that iGluR functional properties can
be predicted from intra- and interdomain energetics and dynamics in
MD simulations. Guided by this theoretical model, most recently we
have used free energy simulations to explore conformations of NMDAR
kinetic substates.[35]
Simulations of Gating Motions
As already noted, crystal structures of both isolated domains and
CTD-truncated constructs have been invaluable in formulating mechanistic
hypotheses. However, it should also be recognized that these structures
only represent sparse, often incomplete snapshots during iGluR activation.
MD simulations can allow for two conformational snapshots to be connected
through a physically plausible path, thereby molecular motions from
one functional state to another can be explored. One such simulation
technique is called targeted MD, by which one region of a protein
system is constrained to move from one conformation to another.[36] In our study of GluA2 AMPAR activation, we mimicked
agonist binding by forcing the four LBDs to move from the cleft-open
to the cleft-closed conformation (Figure A).[31] As a direct
consequence of the D2 closure upon D1, the M3-D2 linkers moved outward,
more so in the B/D subunits than in the A/C subunits. The different
extents of outward movements were attributed to the near orthogonal
orientations of the M3-D2 linkers, parallel and perpendicular, respectively,
to the membrane plane in the B/D and A/C subunits (Figures and 3A). The unevenly splayed M3-D2 linkers in turn pulled on the C-termini
of the M3 helices, resulting in channel opening and symmetry breaking
of the TMD layer from 4-fold to 2-fold.
Figure 3
Activation model of GluA2
AMPAR and validation. (A) Model from
MD simulation. The A/C and B/D subunits are in two shades of red and
blue, respectively. The D1 and D2 subdomains are represented as ovals,
the M3 helices as rods, and the M3-D2 linkers as lines; the latter
are critial in coupling LBD and TMD motions. (B) Validation by substituted
cysteine modification rates of Sobolevsky et al.[39] The functional data (blue bars) are ln(kM+/kM–), where kM+ and kM– are modification rates in the presence
and absence of glutamate; arrows on top indicate that the bars present
lower bounds. The MD simulation results (red bars) are differences
in solvent accessible area (in Å2) of residues between
the activated and resting states. Adapted with permission from ref (31). Copyright 2011 Nature
Publishing Group.
Activation model of GluA2
AMPAR and validation. (A) Model from
MD simulation. The A/C and B/D subunits are in two shades of red and
blue, respectively. The D1 and D2 subdomains are represented as ovals,
the M3 helices as rods, and the M3-D2 linkers as lines; the latter
are critial in coupling LBD and TMD motions. (B) Validation by substituted
cysteine modification rates of Sobolevsky et al.[39] The functional data (blue bars) are ln(kM+/kM–), where kM+ and kM– are modification rates in the presence
and absence of glutamate; arrows on top indicate that the bars present
lower bounds. The MD simulation results (red bars) are differences
in solvent accessible area (in Å2) of residues between
the activated and resting states. Adapted with permission from ref (31). Copyright 2011 Nature
Publishing Group.We recognized that functional
data from whole-cell recordings of
cysteine-substituted mutants could provide a variety of residue-specific
information for validating mechanistic models. In particular, correlation
between agonist-induced changes in rates of modifying substituted
cysteines by methanethiosulfonate (MTS) reagents and changes in solvent
accessible areas of the corresponding residues in key gating elements
is very useful for testing activation models.[31,32,37,38] Sobolevsky
et al.[39] found that, upon AMPAR activation,
cysteines substituted into the M3 C-terminal residues L610, I613,
S614, T617, N619, A621, and F623 had increased modification rates,
whereas L620 had a decreased rate. As shown in Figure B, these changes are reproduced well by the
variations in accessible area during our simulated activation process,
with a correlation coefficient of 0.84. In particular, A621 is pore-facing
and became more accessible upon channel activation, whereas L620 projects
outward and faces the pre-M1 helix in the same subunit. As M3 expanded
outward, the spacing between L620 and the pre-M1 helix was reduced
and hence L620 became less accessible. Moreover, the 2-fold symmetry
of the open channel suggested by our simulations is consistent with
Cd2+ coordination data on substituted cysteines at A621.[40] One caveat is that different AMPAR isoforms
were studied by MD simulation (GluA2) and electrophysiology (GluA1),
so a more detailed comparison is not warranted.Our follow-up
study found similar gross features in gating motions
for the GluN1/N2A NMDAR.[32] However, by
its heteromeric nature, the unequal contributions of the two subunit
types came into focus. Our MD simulations showed that LBD closure
led to greater outward movement of the GluN2 M3 helices than the GluN1
counterparts. A simple explanation for this difference is that the
GluN1 and GluN2 subunits align to the A/C and B/D subunits, respectively,
of the GluA2 AMPAR,[41] with near orthogonal
orientations of the M3-D2 linkers in the two subunit types. The simulation
results fit with a wealth of electrophysiological data indicating
that the GluN1 and GluN2 subunits play unequal roles during channel
activation.[42−46] In particular, in the open state, substituted cysteines in the GluN1M3
helices overall showed higher modification rates (thus implicating
greater access) by MTS reagents than those in the GluN2M3 helices.
In our activation simulations, the greater outward movement of the
GluN2 M3 helices led to a rhombus shape for the positions of four
homologous M3 residues, with the GluN1 residues at the obtuse-angle
vertices and the GluN2 residues at the acute-angle vertices. The simulations
thus revealed that the electrophysiological observation of greater
GluN1 M3 exposure unexpectedly results from greater GluN2 M3 outward
movement, thereby implicating a stronger contribution of the GluN2
subunits to channel activation. It should be notated that the initial
structure for MD simulations in this study was built by homology modeling
to the GluA2 AMPAR, before the first crystal structures of CTD-truncated
NMDARs were published.[47,48] Recently Dutta et al.[49] performed elastic network modeling on the respective
crystals structures of an AMPAR and NMDAR, and found similar global
modes of motion (with minor subtype-specific differences), in line
with our conclusion that the two subtypes of iGluRs share similar
gross features in gating motions.As a further test of the critical
roles of the M3-D2 linkers, especially
the ones on GluN2A, in transmitting the stabilization provided by
agonist-induced LBD closure to the open channel, we introduced glycine
insertions into the linkers.[18] Our MD simulations
showed that, with lengthening by glycine insertions, the linker became
less effective, more so with GluN2A insertions than with GluN1 insertions,
in pulling the M3 helices, leading to weaker stabilization of the
channel-open state. In full agreement, single-channel recordings showed
that the channel open probability decreased progressively as the linkers
were lengthened by glycine insertions. This collaboration between
computation and electrophysiology enabled us to gain a much deeper
understanding on the mechanical coupling between the LBDs and TMD
tetramer by the linkers than either approach alone would, with significant
implications for further advances (see below).
Free Energy Simulations
The conformational space of proteins can also be explored via free
energy simulations. Previous computational studies have confirmed
that crystal structures of isolated AMPAR LBDs bound with agonists
spanning a range of efficacies and antagonists correlated well with
the minimum positions of the free energy basins for cleft closure,[50] thereby lending support to the hypothesis that
AMPAR partial agonism arises from partial agonists not inducing as
much cleft closure as full agonists.[7,22] However, that
still left the partial agonism at NMDARs as a mystery, since their
LBDs bound with full and partial agonists have similar degrees of
closure.[25−28] We reasoned that partial agonists must perturb the free energy basin
of a full agonist-bound LBD in some way; if not the minimum position,
then the next suspect is the broadness, or curvature, of the basin.[33]To test the latter hypothesis, we computed
the free energy surfaces
of the GluN1 LBD bound with a variety of ligands (Figure A) using umbrella sampling
(Figure B,C). The
free energy minima were similarly positioned for LBDs bound with full
and partial agonists (in line with their crystal structures), but
partial agonists significantly broadened the free energy basin (i.e.,
reduced the curvature), precisely as we hypothesized (Figure D,E). Antagonists both shifted
the minimum position and further reduced the curvature. The broadening
of free energy basin was directly illustrated in the simulations.
In umbrella sampling windows where the LBD cleft was restrained to
semiclosed positions, where the degree of cleft closure is intermediate
between those in crystal structures of LBDs bound with a small full
agonist and a large antagonist, the glycine-bound cleft retracted
to more closed conformations, i.e., toward the free energy minimum,
but the clefts bound with partial agonists exhibited less tendency
of retraction, and those bound with antagonists showed tendency of
further opening. In other words, compared to the full agonist glycine,
partial agonists were more likely to maintain the LBD in semiclosed
conformations, and antagonists pushed the LBD toward open conformations.
Figure 4
Broadness
of LBD free energy basin as a determinant of NMDAR partial
agonism. (A) Plot of the relative efficacies of GluN1 ligands[5] against their volumes. Chemical structures are
displayed for the full agonists, glycine (Gly) and d-serine
(DSN); partial agonists, d-cycloserine (DCS), 1-aminocyclopropane-1-carboxylic
acid (ACPC), and 1-aminocyclobutane-1-carboxylic acid (ACBC); and
competitive antagonists, 1-aminocyclopentane-1-carboxylic acid (CLE)
and 5,7-dichlorokynurenic acid (DCKA). Linear regression (red line)
for six ligands (other than DCKA) has R2 = 0.72. (B) Two distances, ξ1 and ξ2, used to describe intersubdomain motions; D1 and D2 are in green
and cyan, respectively. (C) Free energy surface of the Gly-bound GluN1
LBD, presented as contours. The free energy minimum is highlighted
by a white dot; a white diagonal line passing through the minimum
is shown. Stars in white, gray, and black represent crystal structures
bound with Gly (PDB 1PB7), CLE (PDB 1Y1M), and DCKA (PDB 1PBQ), respectively. (D) Overlay of free energy contours for the Gly-bound
case (black) and the indicated non-Gly counterpart (red). (E) Slices
of the free energy surfaces along the diagonal coordinate, ξ1′ = (ξ1 + ξ2)/2,
for the full and partial agonists (solid curves) and antagonists (dashed
curves). Reproduced with permission from ref (33). Copyright 2015 Elsevier.
Broadness
of LBD free energy basin as a determinant of NMDAR partial
agonism. (A) Plot of the relative efficacies of GluN1 ligands[5] against their volumes. Chemical structures are
displayed for the full agonists, glycine (Gly) and d-serine
(DSN); partial agonists, d-cycloserine (DCS), 1-aminocyclopropane-1-carboxylic
acid (ACPC), and 1-aminocyclobutane-1-carboxylic acid (ACBC); and
competitive antagonists, 1-aminocyclopentane-1-carboxylic acid (CLE)
and 5,7-dichlorokynurenic acid (DCKA). Linear regression (red line)
for six ligands (other than DCKA) has R2 = 0.72. (B) Two distances, ξ1 and ξ2, used to describe intersubdomain motions; D1 and D2 are in green
and cyan, respectively. (C) Free energy surface of the Gly-bound GluN1
LBD, presented as contours. The free energy minimum is highlighted
by a white dot; a white diagonal line passing through the minimum
is shown. Stars in white, gray, and black represent crystal structures
bound with Gly (PDB 1PB7), CLE (PDB 1Y1M), and DCKA (PDB 1PBQ), respectively. (D) Overlay of free energy contours for the Gly-bound
case (black) and the indicated non-Gly counterpart (red). (E) Slices
of the free energy surfaces along the diagonal coordinate, ξ1′ = (ξ1 + ξ2)/2,
for the full and partial agonists (solid curves) and antagonists (dashed
curves). Reproduced with permission from ref (33). Copyright 2015 Elsevier.The simplest explanation for these
differences among the full and
partial agonists and antagonists in the probabilities of propelling
the LBD into semiclosed and open conformations is ligand size. Recall
that for AMPARs, ligand size affects efficacy apparently by selecting
the degree of cleft closure at the LBD free energy minimum (Figure ). For NMDARs, ligand
size is evidently also a determinant of efficacy (Figure A), not through shifting the
minimum position but by changing the broadness of the free energy
basin. We thus conclude that NMDAR partial agonism arises from partial
agonists broadening the free energy basin, making the LBD more readily
transition from cleft-closed to cleft-semiclosed conformations and
thereby provide less stabilization to the channel-open state.Very recently we carried out a follow-up study on both GluN1 and
GluN2A LBDs,[35] partly to test the assumption
of Kussius and Popescu[16] that disulfide
cross-linking would trap the LBDs in cleft-closed conformations. Our
free energy simulations showed that, instead of being locked in the
fully closed conformation, the cross-linked LBDs sampled semiclosed
conformations almost as readily as the agonist-bound LBDs. For the
GluN1 LBDs, the free energy minimum of the cross-linked form shifted
slightly toward a lower degree of closure, whereas the free energy
curvature was similar to that of the agonist-bound form. On the other
hand, for the GuN2A LBDs, not only did the free energy minimum of
the cross-linked form shift toward a higher degree of closure, but
also the free energy curvature increased markedly. These results suggest
that the cross-linking on the GluN1 subunits would mostly preserve
the gating behavior of the agonist-bound receptor, but the cross-linking
on the GluN2A subunits could result in a measurable increase in channel
opening. These expectations were consistent with functional data from
single-channel recordings.[16]One
should always be careful about whether conclusions drawn from
studies of isolated domains apply to the full receptor. Although modular
architecture is a hallmark of iGluR structures, the LBDs form A/D
and B/C dimers via their D1 subdomains (Figure B) and, for NMDARs in particular, the LBDs
and ATDs have extensive interactions.[47,48] The D1/D1
interface is very important for gating kinetics.[19] Likewise, ATD deletion has a strong effect on NMDAR gating
properties including channel open probability, although the receptors
remain functional.[51,52] Future work should therefore
examine the impact of interdomain and intersubunit couplings on the
free energy landscapes of individual domains. A similar issue in elastic
network modeling was addressed by a “subsystem-environment”
approach.[49] Next I turn to a very different
approach.
Theoretical Modeling
The idea that both the minimum
position and curvature of the LBD
free energy basin are determinants of agonist efficacy is physically
sound and provides plausible explanations for AMPAR and NMDAR partial
agonisms. Yet how the energetics of LBD closure is transmitted to
the channel is not entirely clear. What is needed is a model for the
free energy function of the full receptor. Guided by the mechanistic
insight on channel activation gained from our targeted MD simulations,[18,31,32] we formulated such a theoretical
model.[34]The model was highly simplified,
with minimal ingredients to capture
the most essential properties regarding stationary gating. An iGluR
was represented by a pair of agonist-bound LBDs linked to a TMD tetramer
(Figure A). The closure
of the LBD pair was assumed to be synchronous and described by coordinate y; the opening of the ion channel within the TMD tetramer
was described by coordinate x; and the extension
of the linker was then described by y – x. Exploiting its modular architecture, we assumed that
the free energy function, W(x,y), of the iGluR consisted of terms for LBD closure, channel
opening, and linker-mediated interdomain coupling, denoted by Wb(y), Wc(x), and W1(y – x), respectively:For illustration, we assumed a parabolic
form
for Wb(y) and W1(y – x):where kb and kl are the spring constants for LBD closure and
linker stretching, and Δ = L0 – Lm, with L0 denoting
the linker length when both the LBD cleft and the channel are closed
(i.e., y = 0 and x = 0) and Lm is the equilibrium linker length. We assumed
a double-well form for Wc(x):which has
a deep and shallow minima, with
a free energy difference of 4ε/3, at x = −1
and x = 1, i.e., when the channel is closed and open,
respectively. The linker transmitted the stabilization provided by
LBD closure to the channel-open state, such that the overall free
energy function, with appropriate choices for the model parameters
(e.g., Δ = 1), had two nearly evenly matched basins (Figure B). One basin, “o”,
had its minimum at (x,y) = (1, 0),
with the channel open and the LBD cleft closed; and the other basin,
“c”, had its minimum at (−0.83, – 0.91),
with x and y values corresponding
to a closed channel and a semiclosed LBD cleft.
Figure 5
Theoretical model for
iGluR gating thermodynamics and kinetics.
(A) Conformational coordinates for the LBD (y) and
channel (x). The difference y – x defines linker extension. (B) Free energy function of
the iGluR, with two basins representing the channel-closed and channel-open
states, respectively. (C) Left: value of x as a function
of time, from a Brownian dynamics simulation of the model. Right:
single-channel current trace of the GluN1/N2A NMDAR during stationery
gating. Reproduced with permission from ref (34). Copyright 2015 American
Chemical Society.
Theoretical model for
iGluR gating thermodynamics and kinetics.
(A) Conformational coordinates for the LBD (y) and
channel (x). The difference y – x defines linker extension. (B) Free energy function of
the iGluR, with two basins representing the channel-closed and channel-open
states, respectively. (C) Left: value of x as a function
of time, from a Brownian dynamics simulation of the model. Right:
single-channel current trace of the GluN1/N2A NMDAR during stationery
gating. Reproduced with permission from ref (34). Copyright 2015 American
Chemical Society.The stabilization effect
on the channel-open state by the linker-mediated
coupling to the LBD could be seen by comparing the free energy term Wc(x) for the isolated channel
against the potential of mean force, Wpmf(x), in x after averaging out y in the free energy function for the full receptor,The second term on the right-hand side of eq served to stabilize the
open channel (i.e., x = 1) relative to the closed
channel (i.e., x = −1). Agonist efficacy can
be measured by the channel open probability, which in our model is
given by the normalized configurational integral for the channel-open
state,where x‡ denotes the top of the barrier in the potential of mean force. A
reduction in the degree of cleft closure at the LBD free energy minimum
corresponds to a decrease in L0 (and hence
Δ), whereas a reduction in the curvature of the LBD free energy
basin corresponds to a decrease in k1.
Both lead to weakened stabilization of the channel-open state provided
by agonist-induced LBD closure and hence lower P0, thus providing a theoretical basis for the foregoing mechanistic
hypotheses on AMPAR and NMDAR partial agonisms.We noted that
the glycine insertions in the NMDAR M3-D2 linkers[18] increase Lm, and
thereby decrease Δ. In essence, these NMDAR insertions have
a similar effect as APAR partial agonists. In our study of glycine
insertions, we empirically defined a “pulling factor,”
as the slope of a linear correlation between two effects of the insertions:
ΔΔG, the change in free energy difference
between two kinetic substates, and ΔLm, the change in linker length (Figure ). In our theoretical model, we proved that this slope
is related to the tension in the linker. Specifically, for the two
states c and o in our model,where Fc and F0 denote the linker tensions in the channel-closed
and open states, respectively. The theoretical model thus clarified
that the single-channel recordings using linker insertions were directly
probing changes in linker tensions between kinetic substates along
the NMDAR activation pathway.
Figure 6
“Pulling factor” k, empirically
defined as the slope of linear correlation between ΔΔG and insertion length, for each transition along the NMDAR
activation pathway. (A) Plots correlating ΔΔG (kcal mol–1) and insertion length for GluN2A in
the C2 → C1 transition. Also shown is
the slope k, in kcal mol–1 nm–1, for linear fits to the first three (black) or four
(gray) points. (B) Pulling factors, using three-point analysis, for
all the transitions along the activation pathway. C1, C2, C3, O1, and O2 denote kinetic
substates along the activation pathway. Reproduced with permission
from ref (18). Copyright
2014 Nature Publishing Group.
“Pulling factor” k, empirically
defined as the slope of linear correlation between ΔΔG and insertion length, for each transition along the NMDAR
activation pathway. (A) Plots correlating ΔΔG (kcal mol–1) and insertion length for GluN2A in
the C2 → C1 transition. Also shown is
the slope k, in kcal mol–1 nm–1, for linear fits to the first three (black) or four
(gray) points. (B) Pulling factors, using three-point analysis, for
all the transitions along the activation pathway. C1, C2, C3, O1, and O2 denote kinetic
substates along the activation pathway. Reproduced with permission
from ref (18). Copyright
2014 Nature Publishing Group.In addition to thermodynamic properties, our model was extended
to stationary gating kinetics, by modeling the motions along x and y as diffusive. The transition rates
between c and o were calculated by both a multidimensional reaction
rate theory[53] and Brownian dynamics simulations
(Figure C).
Possible
Conformations of Kinetic Substates Along Activation
Pathway
Saturating amounts of agonists can maintain iGluRs
in stationary
gating, during which the channel switches between closed and open
conformations. It is most probable that the LBDs adopt cleft-closed
conformations in channel open periods, but very little has been known
about LBD conformations in channel closed periods. Kussius and Popescu[16] observed only modest differences in stationary
gating properties between agonist-bound and LBD cross-linked NMDARs.
Assuming that cross-linking locked the LBD clefts closed, they concluded
that LBDs mostly stayed in cleft-closed conformations even during
channel closed periods. However, as noted above, our free energy simulations
have now cast doubt on their assumption.[35] Our theoretical model,[34] instead, predicts
that the LBDs clefts are semiclosed in the channel-closed state. Keeping
the LBD clefts closed while the channel is closed would result in
overstretched linkers and hence excessive tensions; the receptor relieves
such tensions by reducing the degree of LBD closure.From the
GluN1 and GluN2A LBD conformations sampled in our free
energy simulations, we looked for those that would be characteristic
of LBDs in the channel-closed state.[35]Figure displays cleft-semiclosed
conformations of the GluN1 and GluN2A LBD as candidates. Whereas the
cleft-closed conformations are stabilized mostly by interactions of
the bound agonist and the D1 subdomain with the D2 subdomain, the
cleft-semiclosed conformations are stabilized by alternative interactions
of the bound agonist and D1 with D2, as well as by interactions of
the agonist and the cleft-lining residues with water.
Figure 7
Cleft-semiclosed conformations,
possibly characetristic of GluN1
and GluN2A LBDs in the channel-closed state. With the D1 subdomains
superimposed, the D2 subdomains exhibit significant dispacements in
putative semiclosed LBD conformations (GluN1 marine and GluN2A magenta)
relative to the cleft-closed conformations (gray). Inset: distinct
intersubdomain hydrogen bonds in cleft-closed and semiclosed LBDs.
Conformations from ref (35).
Cleft-semiclosed conformations,
possibly characetristic of GluN1
and GluN2A LBDs in the channel-closed state. With the D1 subdomains
superimposed, the D2 subdomains exhibit significant dispacements in
putative semiclosed LBD conformations (GluN1 marine and GluN2A magenta)
relative to the cleft-closed conformations (gray). Inset: distinct
intersubdomain hydrogen bonds in cleft-closed and semiclosed LBDs.
Conformations from ref (35).As revealed by single-channel
recordings, the channel-closed state
of NMDARs contains not a single but three kinetic components outside
desensitization.[10−13] It is now time to conjecture the conformations of these kinetic
substates along the activation pathway, and combine computation and
electrophysiology to delineate and test such conjectures.[54] The first inspiration for our current efforts
in modeling the conformations of the substates came from the glycine
insertion data (Figure B).[18] They suggest that the earlier transitions
(C3 → C2 and C2 → C1) along the activation pathway mostly involve motions within
GluN2A whereas the later transitions (C1 → O1 and O1 → O2) involve concerted
motions of both types of subunits. More specifically, as clarified
by our theoretical model (see eq ), the greatest decreases in M3-D2 linker tensions and hence
linker extensions occur in GluN2A during the C3 →
C2 and C2 → C1 transitions.
Consequently our current conjecture is that the LBDs adopt cleft-semiclosed
conformations in all four subunits for C3, but become cleft-closed
in one of the two GluN2A subunits for C2, in both GluN2A
subunits for C1, and in all the four subunits in the channel-open
state. If our current approach proves successful in characterizing
conformations of NMDAR kinetic substates, future efforts may target
AMPARs, where single-channel electrophysiology is starting to generate
hints on (sub)states in channel gating.[8,9]
Toward An Atomic-Level
Formalism For Predicting Stationary Gating
Properties
Our initial theoretical model[34] has
provided a foundation for mechanistic hypotheses on AMPAR and NMDAR
partial agonisms, clarified that glycine insertions can be used to
probe linker tension, and predicted that the channel-closed state
is characterized by semiclosed LBDs. Yet, the most important implication
of this model is the exciting prospect for iGluR functional properties
to be predicted from intra- and interdomain energetics and dynamics
in MD simulations. Our current efforts are directed at developing
a more realistic theoretical model specifically for NMDARs, with a
free energy function that features local minima corresponding to the
kinetic substates. This model can be implemented by all-atom MD simulations
to predict thermodynamic and kinetic properties of stationary gating
that are amenable to direct test by single-channel recordings.[12,14−19] Our free energy simulations for GluN1 and GluN2A LBDs can be considered
as part of this implementation.[33,35]The resulting
atomic-level formalism for modeling stationary gating
has the potential to become a powerful technology for NMDAR physiology
and pathophysiology. Functional data for disease-associated NMDAR
mutations are lagging far behind gene sequencing data.[2] A computational formalism could ultimately complement the
traditional electrophysiological approach in filling this widening
gap and help realize the promise of precision medicine.
Authors: Chia-Hsueh Lee; Wei Lü; Jennifer Carlisle Michel; April Goehring; Juan Du; Xianqiang Song; Eric Gouaux Journal: Nature Date: 2014-06-22 Impact factor: 49.962
Authors: Kasper B Hansen; Lonnie P Wollmuth; Derek Bowie; Hiro Furukawa; Frank S Menniti; Alexander I Sobolevsky; Geoffrey T Swanson; Sharon A Swanger; Ingo H Greger; Terunaga Nakagawa; Chris J McBain; Vasanthi Jayaraman; Chian-Ming Low; Mark L Dell'Acqua; Jeffrey S Diamond; Chad R Camp; Riley E Perszyk; Hongjie Yuan; Stephen F Traynelis Journal: Pharmacol Rev Date: 2021-10 Impact factor: 18.923