Sarah L Rouse1, Mark S P Sansom. 1. Department of Biochemistry, University of Oxford , South Parks Road, Oxford OX1 3QU, United Kingdom.
Abstract
Structural studies of membrane proteins have highlighted the likely influence of membrane mimetic environments (i.e., lipid bilayers versus detergent micelles) on the conformation and dynamics of small α-helical membrane proteins. We have used molecular dynamics simulations to compare the conformational dynamics of BM2 (a small α-helical protein from the membrane of influenza B) in a model phospholipid bilayer environment with its behavior in protein-detergent complexes with either the zwitterionic detergent dihexanoylphosphatidylcholine (DHPC) or the nonionic detergent dodecylmaltoside (DDM). We find that DDM more closely resembles the lipid bilayer in terms of its interaction with the protein, while the short-tailed DHPC molecule forms "nonphysiological" interactions with the protein termini. We find that the intrinsic micelle properties of each detergent are conserved upon formation of the protein-detergent complex. This implies that simulations of detergent micelles may be used to help select optimal conditions for experimental studies of membrane proteins.
Structural studies of membrane proteins have highlighted the likely influence of membrane mimetic environments (i.e., lipid bilayers versus detergent micelles) on the conformation and dynamics of small α-helical membrane proteins. We have used molecular dynamics simulations to compare the conformational dynamics of BM2 (a small α-helical protein from the membrane of influenza B) in a model phospholipid bilayer environment with its behavior in protein-detergent complexes with either the zwitterionic detergent dihexanoylphosphatidylcholine (DHPC) or the nonionic detergent dodecylmaltoside (DDM). We find that DDM more closely resembles the lipid bilayer in terms of its interaction with the protein, while the short-tailed DHPC molecule forms "nonphysiological" interactions with the protein termini. We find that the intrinsic micelle properties of each detergent are conserved upon formation of the protein-detergent complex. This implies that simulations of detergent micelles may be used to help select optimal conditions for experimental studies of membrane proteins.
Membrane proteins reside
in a complex bilayer environment, containing
multiple species of lipids. However, by necessity, most structural
and biophysical studies require protein reconstitution into either
a simple lipid bilayer or a membrane–mimetic detergent environment.
Combined with the difficulties of overexpression of membrane proteins,
this has led to membrane protein structures being under-represented
in the Protein Data Bank (www.rcsb.org) compared to water-soluble
proteins (http://blanco.biomol.uci.edu/mpstruc/). We therefore
need to improve our understanding of how experimental conditions may
influence the properties of a given membrane protein.Recent
successes in membrane protein structural biology and biophysics
provide a wealth of experimental data to enable us to explore the
effect of environment on their structure. A particularly well-characterized
example of a “simple” membrane protein is provided by
the transmembrane (TM) domain of the influenza A/M2 proton channel.
A/M2-TM is a small, tetrameric, α-helical membrane protein,
the structure of which has been determined by X-ray crystallography,[1] by solution NMR,[2,3] and by solid-state
NMR[4] under a range of conditions.[5] A comparison of the various structures proves
that the packing of the helices within the A/M2 tetramer is sensitive
to the environment in which the protein has been studied. We may expect
similar observations to be made for a wider range of membrane proteins
as the number of deposited structures continues to expand.[6]Molecular dynamics (MD) simulations provide
a powerful tool in
the study of membrane proteins as they allow us to “transplant”
the protein into an environment of interest. The majority of efforts
are dedicated toward restoring these proteins in a native-like bilayer,[7] but the same tools may be used to simulate these
proteins under conditions reflecting those used in experiments, thus
replicating the conditions used in vitro. Examples of this include
MD simulations of crystal packing in OmpA[8] and of the behavior of protein–detergent complexes (PDCs)
in mass spectrometry experiments.[9]Simulations of PDCs pose a number of additional challenges as the
time scales required to fully sample the process of micelle formation
are not readily accessible by conventional atomistic (AT) simulation,
while reduced representations (e.g., coarse-grained simulations) may
not capture all of the details of the process.[10] However, these limitations may be overcome by a variety
of methods, including multiscale approaches,[10] and by averaging over multiple simulations.[11]In the current study, we have focused on the proton channel
from
the influenza B virus (BM2) as a model membrane protein. BM2 is a
small, tetrameric, α-helical membrane protein[12,13] homologous in both structure and function to the A/M2 channel protein
(see above), although BM2 is less well-studied.[14] The structure of the TM domain of BM2 (BM2-TM) has been
determined by solution NMR[15] in detergent
micelles.We used simulations to study BM2-TM in three membrane–mimetic
environments, a simple model lipid bilayer (DPPC; dipalmitoylphosphatidylcholine),
a zwitterionic detergent (DHPC; dihexanoylphosphatidylcholine) used
in the NMR studies, and a nonionic detergent (DDM; n-dodecyl-β-d-maltoside) that has been used in many
crystallographic studies of membrane proteins[16] (Figure 1). To the best of our knowledge,
this is the first comparative MD study of an α-helical membrane
protein in two types of detergent micelles and in a model lipid bilayer,
adding to a number of previous simulation studies of membrane proteins
in a bilayer versus a detergent micelle (see, e.g., refs (17−23)). We note that there are several differences between DHPC and DDM
micelles. The geometry (prolate versus oblate), critical micelle concentration,
and aggregation size are all expected to play a role in the properties
of the PDC. Thus, the effect that these properties of the detergents
have on the structure and dynamics of membrane proteins within PDCs
is studied using BM2-TM as a model of α-helical membrane proteins.
Figure 1
(Upper
panel) Simulation systems showing the BM2 tetrameric helix
bundle in yellow in a DPPC bilayer and in DHPC and DDM micelles. Head
groups are shown in red, and tails are in gray. (Lower panel) Lipid
(DPPC) and detergents (DHPC, DDM) used in this study. The aggregation
properties of DHPC and DDM micelles are as reported in ref (24).
(Upper
panel) Simulation systems showing the BM2 tetrameric helix
bundle in yellow in a DPPC bilayer and in DHPC and DDM micelles. Head
groups are shown in red, and tails are in gray. (Lower panel) Lipid
(DPPC) and detergents (DHPC, DDM) used in this study. The aggregation
properties of DHPC and DDM micelles are as reported in ref (24).
Materials and Methods
All simulations were performed using
GROMACS v4.6 (www.gromacs.org).[25] The initial coordinates of the BM2-TM
domain were from pdb entry 2KIX.[15] His19 residues were
singly protonated and His27 residues doubly protonated.[26] This was done on the basis of experimental data
for these residues at the pH (7.5) at which the NMR structure was
solved.[270] Exploratory simulations investigating
the influence of different combinations of the His27 protonation state
showed no significant differences in stability (Figure S12, Supporting Information). CG and AT parameters
for DHPC and DDM were as described those in ref (9) and available from LipidBook
(http://lipidbook.bioch.ox.ac.uk/).[27] Analyses were performed using GROMACS tools, MDAnalysis
(mdanalysis.googlecode.com),[28] and locally
written code. Visualization used VMD.[29]
Multiscale
Simulations
Coarse-grained (CG) simulations
used the MARTINI v2.1 force field[30,31] and were performed
as described elsewhere.[32] Standard simulation
parameters associated with the MARTINI force field were used, unless
stated otherwise. A time step of 20 fs was used. The temperature (323
or 300 K) and pressure (1 bar) were maintained using the Berendsen
coupling schemes. CG simulations were 1 μs in duration, unless
stated otherwise. Long-range interactions were cut off at 1.2 nm.
Conversion to AT resolution was achieved using a fragment-based method,
as described elsewhere.[32] AT simulations
used the OPLS-UA force field with Berger lipids[33] and TIP4P water as described in ref (9). Additional DPPC simulations
used the OPLS-AA[34] and GROMOS 56a3 force
fields,[35] the latter with the SPC water
model. AT simulations were 100 ns in duration, unless otherwise stated.
A time step of 2 fs was used. The particle mesh Ewald method[36] was used for calculation of long-range electrostatics.
AT simulations used the Berendsen thermostat (323 or 300 K) and Parrinello–Rahman
barostat (1 bar).[37]
BM2 in a DPPC Bilayer
As in previous studies,[32] a multiscale
simulation procedure was used in
which CG simulations were used to self-assemble a bilayer around the
protein. Briefly, these were generated by CGMD simulation of the BM2-TM
domain tetramer with elastic network model restraints. DPPC molecules
were randomly distributed within the cubic simulation box (size 9
nm3) and allowed to self-assemble about the protein in a 1 μs
simulation. A representative snapshot was converted to AT resolution.
Generation of DHPC Micelles
An ATMD simulation of 200
DHPC molecules randomly distributed about a simulation box containing
∼75 000 water molecules was performed. The concentration
of DHPC in this system was ∼300 mM, intended to match the concentrations
used in the solution NMR BM2-TM experiment.[15] The detergent/protein ratio was ∼200:1; therefore, 200 DHPC
monomers was chosen as a minimum system size.
Generation of DDM Micelles
The Packmol[38] software was used to build
two sizes of CG DDM micelle, N = 132 and 150 in a
10 nm3 box. CGMD simulations
were performed followed by conversion to AT resolution. The DDM sugar
rings adopted a chair conformation.
Results and Discussion
DHPC Micelle
Generation
AT resolution simulations of
the self-assembly of DHPC micelles at experimentally relevant detergent
concentrations were comparable to small-angle X-ray scattering (SAXS)
data,[24] implying that this approach may
also be used to study BM2–DHPC complex formation (Supporting Information Figure S1). This method
of self-assembling detergent molecules has been used successfully
for previous studies with zwitterionic detergents.[8,40] Properties
of an individual DHPC micelle that formed within 25 ns and remained
stable for the duration of the simulation (Supporting
Information Figure S2) were compared to experimental SAXS data.
The prolate shape of the micelle (c > a = b) may be quantified by calculation
of the semiaxis
lengths (which are in turn calculated from the micelle moments of
inertia, I1 > I2 > I3).[41] The
polar length, corresponding to the thickness of the head group region,
is found by calculating the semiaxis lengths of the acyl tails alone
and subtracting these from the overall lengths. These along with the
micelle size and radius of gyration are shown in Supporting Information Table S1. The prolate shape of the
micelle (a/c ratio = 1.5) is in
reasonable agreement with SAXS measurements (a/c ratio = 2.2). There is good agreement between the thickness
of the head group region calculated from SAXS data (3.0–4.0)
and that from MD simulations (3.7 ± 0.4). The radius of gyration
of the simulated micelle (Rg) is lower
than the experimental value, corresponding to a more compact assembly.
The discrepancy between experimental and MD values may be related
to hydrated components of the head group region of the micelle contributing
to the SAXS data.[42] However, the overall
agreement between the experimental data and the MD data is reasonable.
The analysis of pure DHPC micelle formation suggested that self-assembly
via ATMD simulations may be used to generate models of protein–DHPC
complexes. CG simulations would allow longer simulations to be performed.
However, initial CG simulations of DHPC self-assembly led to no apparent
upper limit in micelle size with standard MARTINI water (as reported
elsewhere[43]), suggesting that this method
may be of limited use in predicting the size of the PDC.
DDM Micelle
Generation
In contrast to the case for
DHPC, AT resolution self-assembly simulations of DDM were not found
to equilibrate within comparable time scales. A more computationally
efficient manner of generating BM2–DDM complexes was therefore
developed using a multiscale approach, in which preformed DDM micelles
were allowed to interact with BM2. The monomer–micelle equilibrium
lies much further to the right for DDM compared to that for DHPC (Figure 1), such that the concentration of DDM monomers in
bulk solution is approximately 2 orders of magnitude lower than that
for DHPC. It seems reasonable, therefore, to simulate the interaction
of a DDM aggregate (i.e., a preformed micelle) with the membrane protein.
This may in principle be generated using self-assembly simulations
of DDM; however, we found equilibration to be rather slow (on the
microsecond time scale) and therefore chose to use preformed micelles
in the interest of computational efficiency. (Examples of self-assembly
simulations are shown in Supporting Information Figure S3 for comparative purposes.) Two sizes of micelles were
built, N = 132 and 150. These are within the experimentally
determined aggregation range and allow comparison to both experimental
results and a recent MD study of DDM micelles.[42] The initial spherical aggregate for the N = 150 system is shown in Supporting Information Figure S4. Upon CGMD simulation, the micelle “flattens out”
to adopt a more oblate shape, consistent with experimental observations.
There is also a tendency for the maltose head groups to cluster together
on the surface, leaving the alkyl tails to some extent exposed to
solvent. The final CG-DDM micelle was then converted to an AT representation,
using either the OPLS-AA or the GROMOS 56a3 force field. Upon ATMD
simulation of the DDM micelle, the dimensions decrease, and the micelle
ellipticity decreases slightly while maintaining an oblate shape (Supporting Information Table S2). Such changes
upon CG2AT conversion are not unexpected. For example, water molecules
are able to penetrate into the head group region of the AT micelle,
whereas the larger water particles used in CGMD limit the degree of
penetration. The clustering of maltose head groups, leading to a “rough”
surface was maintained in the ATMD simulations. The DDM micelle systems
tested are summarized in Supporting Information Table S2 with calculated parameters compared to those from MD and
experiment. As was observed for the DHPC micelle, there is some difference
between the calculated dimensions of the simulated DDM micelles (including
those from ref (42)) and the experimental scattering data. The main disparity between
experiment and simulation appears to be the degree of ellipticity
(measured by the a/c ratio).This study and previous studies have shown that there is a need to
improve agreement between experimentally and computationally calculated
properties. It may be expected that advances in methodology, such
as developments in polarizable force fields,[44] may lead to improvements. However, the choice of experimental method
for determining micelle properties still causes greater deviation
in calculated properties than the difference between experimental
and computational results.[43]Taken
together, the simulations of the detergent-only systems provide
protocols for each detergent (i.e., AT self-assembly for DHPC versus
multiscale simulations from a CG preformed aggregate for DDM) that
could be extended to simulate formation of respective detergent complexes
with the BM2 protein.
BM2–DHPC Complex Formation
A similar approach
to the one described for the DHPC-only simulation was set up to self-assemble
a BM2–DHPC PDC. The NMR structure of BM2 was restrained in
the center of the box, and 200 DHPC lipids were randomly positioned
and oriented around it. This was the starting point for a 50 ns ATMD
simulation during which the condensation of DHPC detergent molecules
onto the protein surface was monitored. Similarly to the DHPC-only
simulation, small DHPC clusters formed within a few nanoseconds (Supporting Information Figure S5). Following
the initial 50 ns of ATMD simulation, 115 DHPC residues were found
to be directly or indirectly in contact with the protein in a “loose”
aggregate. The majority of these were in contact with the hydrophobic
region of the protein. A smaller micelle of N ≈
25 was attached to the N-terminal extracellular region. The majority
of the hydrophobic surface residues were in contact with the DHPC
tails, and water was excluded from this region (Supporting Information Figure S6). The charged residues near
the protein termini remained largely accessible to water. Once the
initial loose PDC complex formed (after 50 ns), the main PDC was removed
and simulated further in a smaller box (while maintaining the same
overall concentration of DHPC), allowing for a reduction in computational
cost of the equilibration process, in a manner similar to that described
in ref (40). During
the 100 ns simulation, the smaller DHPC micelle attached to the N-terminus
was found to dissociate, and the geometry of the remaining PDC stabilized
within a 100 ns time scale, as evidenced by its radius of gyration
(Supporting Information Figure S7).
Formation
of the BM2–DDM Complex
The calculated
values of the aggregation number of DDM micelles range from 98 to
∼140.[45] Previous simulations and
calculations have shown that upon binding to a protein, the number
of detergent molecules can increase above that of the aggregation
number of pure detergent as the hydrophobic core of the protein provides
additional surface area with which the alkyl tails may interact.[46] On the basis of this evidence, a micelle of
DDM at the upper end of the predicted aggregation number, that is,
150 DDM molecules, was used as the starting point for the generation
of a BM2–DDM complex. The BM2 protein and DDM micelle were
initially separated in the simulation box at a distance greater than
the interaction cutoffs. Five simulations of 1 μs based on this
starting configuration were performed (Supporting
Information Figure S8). In each case, the micelle and BM2-TM
interacted. In four of the simulations, the protein became incorporated
into the center of the DDM micelle, following a variable time spent
in a more surface-bound orientation. These stages may be monitored
in terms of the protein solvent-accessible surface area (SASA) and
simulation box volume (Supporting Information Figure S9). The distributions of DDM head groups in each of the
four simulations where BM2 becomes fully incorporated into the complex
reveal a degree of variation in the position of the protein within
the micelle (Supporting Information Figure
S10). This is reminiscent of a previous suggestion that small peptides
in large detergent micelles may adopt multiple conformations, corresponding
to their adopting a range of positions and/or orientations within
such micelles.[47] The PDC generated in the
first simulation was converted to AT resolution and simulated for
20 ns at 323 K, with positional restraints on the protein to enable
the repacking of detergent molecules around the protein. Similarly
to the DDM-only micelle control, the protein–micelle complex
became more compact (measured by an initial rapid decrease in Rg of the complex from 27.5 to 27.0 Å),
and the geometry stabilized (small fluctuations in Rg in the region of ±0.2 Å) during this 20 ns
simulation.
BM2-TM in a DPPC Bilayer
AT simulations
of BM2-TM in
a DPPC bilayer highlighted some regions of relative instability in
the protein. The average Cα RMSD over the course of the 100
ns ATMD simulation was 3.0 Å (±0.1) (Supporting Information Figure S11). In particular, the pore
radius was found to decrease rapidly during the first 1 ns of simulation
(Supporting Information Figure S12). This
is reminiscent of behavior observed by us and others[48] for UCP2, another membrane protein structure determined
by NMR, in simulations in a lipid bilayer. Interestingly, the structure
of the UCP2 protein was also determined by NMR spectroscopy in the
presence of zwitterionic detergents.[49] A
further destabilizing feature of BM2 seemed to be the His27 residues,
which were lipid-facing in the structure solved in detergent micelles
and of which at least one rotated into the pore during all simulations,
independent of the force field used (Supporting
Information Figure S13). DPPC was chosen as a model membrane
widely used in CGMD simulations and as a simple model of the high
membrane order of the influenza viral membrane.[50] However, it would be of interest in future studies to perform
simulations using a range of more physiologically relevant lipid compositions
to explore their effect on BM2.
Stability of BM2-TM in
a DPPC Bilayer Compared with DHPC and
DDM Micelles
Preliminary simulations performed of the solution
NMR structure revealed that the conformational stability of the protein
(measured as the degree of retention/loss of secondary structure over
the course of the simulation) was reduced in DHPC compared to that
in a bilayer. This was the case independent of temperature (300 and
323 K) and protonation state of the His27 residues (Supporting Information Figure S14). It is probable that the
lateral pressure of the bilayer allowed the helices to pack more tightly,
forming intersubunit contacts. The absence of this lateral pressure
in the DHPC micelles allowed the helices to unfold before these contacts
could be made. In order to simulate the NMR structure in a micelle
environment, the structure of the TM domain following 10 ns equilibration
in a DPPC bilayer (referred to as the “equilibrated NMR structure”)
was chosen as the starting point for further simulations (Supporting Information Figure S14). All following
simulations of the equilibrated NMR structure refer to those using
the NMR structure from 10 ns of ATMD simulation time in the DPPC bilayer
at 323 K as the starting structure. The structure and stability of
the equilibrated NMR structure in each micelle environment was assessed
in terms of the Cα root-mean-square deviation (RMSD) and α-helical
content during simulation at two temperatures (Supporting Information Figure S15A). The structural drift
during each simulation was comparable (Supporting
Information Table S3). The smallest deviation from the equilibrated
NMR structure was observed in the DHPC simulation at 300 K, closest
to the experimental conditions in which the solution NMR structure
was determined. A decline in the number of residues in α-helical
conformation is observed in all simulations. The fluctuations of the
protein show slight differences between the three environments.
PDCs Retain Features of Their “Parent” Detergent
Micelles
The PDCs retain some of the features of their “parent”
detergent-only micelles (Supporting Information Table S4). DHPC micelles are prolate both in the presence and in
the absence of BM2. The architecture of the protein–DDM complex
is similar to that of the DDM-only micelle. The maltose head groups
are again seen to cluster slightly on the surface, as was observed
in CGMD and ATMD simulations of the detergent-only micelle. To compare
the DHPC and DDM micelle environments to that of the DPPC bilayer,
density distribution plots of key protein residues and detergent components
were calculated along the principal axis of the TM helix bundle (Figure 2). Several key differences may be seen upon comparison
of the three density plots: (i) the protein sits asymmetrically within
the DDM micelle such that the lysine and arginine residues are exposed
to the water; (ii) a clear additional peak in the glycerol oxygen
density is present in the DHPC micelle in the region of the lysine
and arginine residues; and (iii) there is density attributable to
the alkyl carbons of DHPC at the terminal regions of the protein.
The differences between the distribution of the lipid/detergent head
groups and alkyl tails were investigated further by generation of
spatial distribution plots over the last 50 ns of simulation time
for each system (Supporting Information Figure S16). In the case of DHPC, the presence of detergent molecule
inserted into the pore at the N- and C-termini is evident from the
density profile. This was also observed in the preliminary CG simulations
in which DHPC self-assembled around BM2 and was seen to insert between
the helices. In each case, the hydrophobic core of the protein is
in contact with the hydrophobic lipid tails.
Figure 2
Density distribution
plots of the (A) DPPC, (B) DHPC, and (C) DDM
systems. The density was calculated at 500 intervals along the z-axis (corresponding to the bilayer normal or the protein
principle axis of symmetry). The area shaded in gray corresponds to
the region containing protein. Distributions for lysine and arginine
residues are shown in orange and yellow, respectively. The nearest
100 water molecules to the protein are used in the calculation of
water density. In (A), only the closest 150 lipids to the protein
are included in calculations, and the density of the phosphorus atoms
has been divided by 2 for clarity. In (A) and (B), only the first
alkyl chain was used. The atoms used for calculating the tail’s
density are the terminal and middle carbons for DPPC, the terminal
carbon for DHPC, and the carbons at each end of the acyl tail and
the middle carbon for DDM. In (C), the density Ring 1 corresponds
to a single oxygen on the ring furthest from the acyl tail, and the
Ring 2 density corresponds to the equivalent oxygen of the other glucose
ring.
Density distribution
plots of the (A) DPPC, (B) DHPC, and (C) DDM
systems. The density was calculated at 500 intervals along the z-axis (corresponding to the bilayer normal or the protein
principle axis of symmetry). The area shaded in gray corresponds to
the region containing protein. Distributions for lysine and arginine
residues are shown in orange and yellow, respectively. The nearest
100 water molecules to the protein are used in the calculation of
water density. In (A), only the closest 150 lipids to the protein
are included in calculations, and the density of the phosphorus atoms
has been divided by 2 for clarity. In (A) and (B), only the first
alkyl chain was used. The atoms used for calculating the tail’s
density are the terminal and middle carbons for DPPC, the terminal
carbon for DHPC, and the carbons at each end of the acyl tail and
the middle carbon for DDM. In (C), the density Ring 1 corresponds
to a single oxygen on the ring furthest from the acyl tail, and the
Ring 2 density corresponds to the equivalent oxygen of the other glucose
ring.
Protein–Detergent
Interactions
Analysis of contacts
between the lipid or detergent and protein (Figure 3) demonstrated similar patterns of contacts for the bilayer
and the micelle systems. A comparison of protein–head group
interactions for the three systems shows that most of the contacts
made in the DPPC bilayer system are largely replicated within the
DHPC micelle. In contrast, in the BM2–DDM complex, the C-terminal
lysine and arginine residues were more exposed to water than those
in a DHPC micelle or in the DPPC bilayer. This is presumably due to
the inability of DDM to form salt bridges with charged residues, making
increased solvation of these side chains possible. This contact analysis
demonstrates that most of the contacts formed in a bilayer environment
are fulfilled by the DHPC micelle environment (with some additional
contacts), while for the DDM micelle, the hydrophobic core is shifted
slightly toward the N-terminus, allowing charged residues in the C-terminal
region to interact with water.
Figure 3
Lipid–detergent interactions per
residue of the BM2 protein.
Residues are colored according to time spent in contact with lipid/detergent
head groups or tails during each simulation on a blue–green–red
scale. Blue corresponds to 0% of simulation, green = 50% simulation
time, and red = the residue is in contact with a lipid head group
or tail for 100% of the simulation.
Lipid–detergent interactions per
residue of the BM2 protein.
Residues are colored according to time spent in contact with lipid/detergent
head groups or tails during each simulation on a blue–green–red
scale. Blue corresponds to 0% of simulation, green = 50% simulation
time, and red = the residue is in contact with a lipid head group
or tail for 100% of the simulation.
Binding Mode of DHPC Compared to DPPC and DDM
The most
frequently occupied positions of the lipid/detergent tails over the
final 10 ns of each simulation are shown in Figure 4. In the DPPC bilayer environment, the lipid tails around
the BM2 protein tend to align parallel to the bilayer normal (i.e.,
parallel to the long axis of the protein). In the DHPC micelle, such
a binding mode is not possible due to the shorter acyl chains. Instead,
the majority of the DHPC tails are aligned perpendicular to the micelle
surface, maximizing coverage of the hydrophobic surface of the protein.
In the DDM micelle, those hydrophobic tails close to the protein surface
tend to align in a similar manner to the tails of DPPC. However, the
shorter length of the DDM tail means that two detergent molecules
with extended carbon tails are not sufficient to cover the hydrophobic
surface, and therefore, slightly more distant detergent molecules
align such that the termini of their alkyl chains are directed toward
the protein surface. Plots of SCD for
DDM provide a means to quantify this picture of lipid orientation
(Supporting Information Figure S17). To
determine if any conserved interaction sites between the protein and
the lipid/detergent acyl tails exist, the two most similar protein
conformations of BM2-TM in DPPC and DDM were chosen for comparison.
The average positions of the DPPC and DDM tails over a 10 ns period
of the trajectories were superimposed and are shown in Figure 5. An example of the tail of a DDM molecule occupying
the same region of the protein surface as the DPPC lipid is highlighted.
Figure 4
Lipid/detergent
binding modes to the BM2 protein in the DPPC bilayer
(A,D), DHPC micelle (B,E), and DDM micelle (C,F) simulations. In A–C,
the protein is displayed as a gray surface. Alkyl tails of the lipids/detergents
are shown in stick representation (colored per molecule). The positions
of the tails are the average positions adopted over the final 10 ns
of each simulation performed at 323 K. Corresponding cartoons of the
modes of interaction are shown in D–F.
Figure 5
Interaction of acyl tails of DPPC and DDM with the protein surface.
(A) Superimposition of the most highly occupied positions of the alkyl
tails of DPPC (cyan) and DDM (red) tails during 10 ns of each simulation
(see text for details). (B) An example of the same region on the protein
surface occupied by an alkyl tail in the two different simulations.
The protein is displayed as a gray surface in each case.
Lipid/detergent
binding modes to the BM2 protein in the DPPC bilayer
(A,D), DHPC micelle (B,E), and DDM micelle (C,F) simulations. In A–C,
the protein is displayed as a gray surface. Alkyl tails of the lipids/detergents
are shown in stick representation (colored per molecule). The positions
of the tails are the average positions adopted over the final 10 ns
of each simulation performed at 323 K. Corresponding cartoons of the
modes of interaction are shown in D–F.Interaction of acyl tails of DPPC and DDM with the protein surface.
(A) Superimposition of the most highly occupied positions of the alkyl
tails of DPPC (cyan) and DDM (red) tails during 10 ns of each simulation
(see text for details). (B) An example of the same region on the protein
surface occupied by an alkyl tail in the two different simulations.
The protein is displayed as a gray surface in each case.
Detergent Dynamics
Visual inspection
of the trajectories
suggested that the DHPC molecules are more dynamic than their DDM
and DPPC counterparts. A direct comparison of diffusion coefficients
of lipid molecules in a bilayer compared to detergent molecules in
a micelle would be difficult to interpret because (i) the lipids in
a bilayer are effectively restricted to lateral motion, whereas in
a micellar system, the detergent molecules can potentially sample
a spherical region, and (ii) the bilayer patch in question (∼300
lipids) may not be large enough to avoid conserved motion of lipids
between periodic images.[51] Therefore, rather
than attempt to compare diffusion coefficients of each lipid or detergent
molecule, the space sampled by individual lipid and detergent molecules
within 6 Å of the protein was calculated for each of the trajectories
(Figure 6). The spatial distributions indicate
that the DHPC complex is consistent with the picture of micelles being
highly dynamic species.[3] However, DDM and
DPPC have similar spatial distributions. The DPPC and DHPC head groups
are identical; therefore, the higher mobility of DHPC may be attributed
to the shorter tail lengths of DHPC, leading to differing binding
modes. To allow a quantitative comparison, analysis of detergent MSDs
(mean-square deviations) over the final 10 ns of the trajectory yielded
diffusion coefficients of 7 (±1) × 10 –7 cm2 s–1 (DHPC) and 0.4 (±0.1)
× 10–7 cm2 s–1 (DDM).
Figure 6
Spatial distribution plots of five representative lipid/detergent
molecules within 6 Å of the protein for each environment. The
initial position of each lipid or detergent molecule is shown in stick
representation, and the resultant spatial distributions are shown
as colored dots. The lipid/detergent molecules in the DPPC and DDM
simulations move to a comparable extent during the simulation, while
those in the DHPC simulation sample a far greater volume of space.
Spatial distribution plots of five representative lipid/detergent
molecules within 6 Å of the protein for each environment. The
initial position of each lipid or detergent molecule is shown in stick
representation, and the resultant spatial distributions are shown
as colored dots. The lipid/detergent molecules in the DPPC and DDM
simulations move to a comparable extent during the simulation, while
those in the DHPC simulation sample a far greater volume of space.
N-Terminal Region of the
Pore Remains Hydrated
The
highly mobile nature of the DHPC micelle might be expected to affect
the degree of water penetration into the hydrophobic core. To assess
if this was the case, calculations of the SASA of the protein were
performed for each environment, and the average SASA per residue over
the final 10 ns of simulation time is shown in Supporting Information Figure S18. The low protein SASA is
largely maintained in the hydrophobic TM region. Radial density distribution
plots of the water position relative to the protein over the simulations
are shown in Supporting Information Figure
S19. These highlight the hydrophobic band around the protein, where
no water is present in either of the micelle simulations. It is evident
that there is water density within the protein pore in each case,
with no clear distinction between the N-terminal region of the pore
in the three environments. This is consistent with our previous study
of a self-assembled BM2 tetramer,[52] as
well as a recent simulation study of the BM2 NMR structure.[53]
Conclusions
The results of this
work enable comparisons to be made between
three types of environment for a membrane protein: a simple model
phospholipid (DPPC) lipid bilayer, small zwitterionic detergent (DHPC)
micelles used in solution NMR experiments, and nonionic, larger detergent
(DDM) micelles commonly used in protein purification and X-ray crystallography.We have shown that both detergent types fulfilled the hydrophobic
and polar contacts that are present in a lipid bilayer. However, DHPC
was observed to form additional “non-native” interactions
with the protein, in which the hydrophobic tail inserted into the
pore region of BM2. Thus, DDM appeared to better mimic the interaction
of the protein with bilayer phospholipids than did DHPC, even though
DHPC and DPPC share the same zwitterionic head groups. This reflects
the alignment of DDM tails in grooves on the protein surface in a
similar fashion to those of DPPC. This mode of interaction may help
to explain the successful use of DDM and related detergents in mimicking
the lipid bilayer in a number of crystallographic structure determinations.[45] The binding modes of detergents within the protein–detergent
complexes may be related to the properties of the “parent”
pure detergent micelles, providing further evidence that the nature
of a membrane–protein complex does not necessarily depend on
the head group type of the lipid used but rather on the geometric
properties of the detergent micelle.[46] The
presence of monomeric DHPC in solution (due to the higher critical
micelle concentration of DHPC compared to that of DDM, DPPC, and other
lipids) is potentially a reason for concern as DHPC monomers were
observed to form “nonphysiological” interactions with
regions of the protein that would not be accessible to lipids within
a bilayer.It is informative to reflect on the methods employed
in this study.
Different methods for generating initial PDCs were found to be more
appropriate for each detergent type. Although it would be ideal to
employ a single method for all detergent types, the development of
sugar head group parameters for the MARTINI force field is relatively
new,[31] and further studies are required
to fully investigate the simulation conditions required to fully satisfy
available experimental data. For example, in studies of DHPC, it has
been suggested that the use of a MARTINI polarizable water model is
important in replicating experimental results for zwitterionic detergents.
It will be of interest to develop similar studies on DDM and related
detergents commonly used in membrane protein solubilization.In summary, the BM2-TM channel was shown to exhibit a degree of
sensitivity to its lipid/detergent environment. In particular, helix
packing interactions could be perturbed by the presence of certain
detergent molecules. The results of these simulations indicate that
BM2 (like the related A/M2 protein) may exhibit a range of conformations
due to the relative malleability of the helix–helix packing
interactions and their sensitivity to their environment. It is likely
that the conformational flexibility of these “simple”
viral ion channels (or viroporins[47]) may
be related to their functional dynamics, in particular, channel gating.