Taras V Pogorelov1, Josh V Vermaas, Mark J Arcario, Emad Tajkhorshid. 1. Center for Biophysics and Computational Biology, School of Chemical Sciences, Departments of Chemistry and Biochemistry, College of Medicine, and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States.
Abstract
Energetics of protein side chain partitioning between aqueous solution and cellular membranes is of fundamental importance for correctly capturing the membrane binding and specific protein-lipid interactions of peripheral membrane proteins. We recently reported a highly mobile membrane mimetic (HMMM) model that accelerates lipid dynamics by modeling the membrane interior partially as a fluid organic solvent while retaining a literal description of the lipid head groups and the beginning of the tails. While the HMMM has been successfully applied to study spontaneous insertion of a number of peripheral proteins into membranes, a quantitative characterization of the energetics of membrane-protein interactions in HMMM membranes has not been performed. We report here the free energy profiles for partitioning of 10 protein side chain analogues into a HMMM membrane. In the interfacial and headgroup regions of the membrane, the side chain free energy profiles show excellent agreement with profiles previously reported for conventional membranes with full-tail lipids. In regions where the organic solvent is prevalent, the increased dipole and fluidity of the solvent generally result in a less accurate description, most notably overstabilization of aromatic and polar amino acids. As an additional measure of the ability of the HMMM model to describe membrane-protein interactions, the water-to-membrane interface transfer energies were analyzed and found to be in agreement with the previously reported experimental and computational hydrophobicity scales. We discuss strengths and weaknesses of HMMM in describing protein-membrane interactions as well as further development of model membranes.
Energetics of protein side chain partitioning between aqueous solution and cellular membranes is of fundamental importance for correctly capturing the membrane binding and specific protein-lipid interactions of peripheral membrane proteins. We recently reported a highly mobile membrane mimetic (HMMM) model that accelerates lipid dynamics by modeling the membrane interior partially as a fluid organic solvent while retaining a literal description of the lipid head groups and the beginning of the tails. While the HMMM has been successfully applied to study spontaneous insertion of a number of peripheral proteins into membranes, a quantitative characterization of the energetics of membrane-protein interactions in HMMM membranes has not been performed. We report here the free energy profiles for partitioning of 10 protein side chain analogues into a HMMM membrane. In the interfacial and headgroup regions of the membrane, the side chain free energy profiles show excellent agreement with profiles previously reported for conventional membranes with full-tail lipids. In regions where the organic solvent is prevalent, the increased dipole and fluidity of the solvent generally result in a less accurate description, most notably overstabilization of aromatic and polar amino acids. As an additional measure of the ability of the HMMM model to describe membrane-protein interactions, the water-to-membrane interface transfer energies were analyzed and found to be in agreement with the previously reported experimental and computational hydrophobicity scales. We discuss strengths and weaknesses of HMMM in describing protein-membrane interactions as well as further development of model membranes.
Biological membranes
are indispensable and multifunctional components
of all living cells and serve as a dynamic platform for a wide range
of vital cellular processes, including signaling and transport.[1] Cellular membranes are a complex environment
characterized by high leaflet asymmetry and heterogeneous composition,[2,3] where more than 25% of the surface area is occupied by proteins.[4] Far from the initial perception of serving as
a passive enclosure, cellular membranes regulate numerous membrane-associated
proteins[5,6] via the mechanical and electrical properties
of the lipid bilayer. The importance of the membrane to life cannot
be overstated, as nearly a third of the 34 000 identified human
proteins are thought to function only in their membrane-bound forms
and depend on membranes for proper function.[7]Experimental biophysical and biochemical studies have contributed
significantly to our understanding of membrane–protein interactions.[8] Such interactions are particularly key to peripheral membrane proteins, in which case the binding
and activity of the protein are strongly coupled to the lipid composition
of the bilayer. A number of membrane anchoring domains are now structurally
resolved and display a wide range of diversity in structural motifs
and modes of interaction with the membrane including varying insertion
depth, requirement for a particular ion or lipid for proper membrane
binding, post-translational modifications to enhance membrane binding,
and the need for dimerization.[5,8] Although interactions
of peripheral proteins with the membrane are thought to be mediated
by both lipid-specific interactions[5,6] and response
to bulk electrical and mechanical properties of the lipid bilayer,[9] challenges to and limitations of experimental
approaches have prevented detailed atomic characterization of the
membrane binding process and associated phenomena for most peripheral
membrane proteins.Molecular dynamics (MD) is a valuable tool
for an atomistic description
of protein–membrane interactions, as it offers temporal and
spatial resolutions needed to study molecular events at an unparalleled
level of detail.[10,11] Indeed, combining experimental
approaches and computational methodologies in a number of peripheral
proteins has proven very effective in understanding how atomic-level
phenomena affect cellular-level events.[12,13] However, relatively
slow lateral lipid dynamics and limits to time scales achievable have
made capturing spontaneous binding and insertion of peripheral proteins
into a membrane challenging to computational studies. These challenges
led us to develop a novel membrane model, termed the highly mobile
membrane mimetic (HMMM), which expedites computational studies of
membrane-associated phenomena by enhancing lipid dynamics.[14]The HMMM is based on the conceptually
simple idea of representing
a large part of the membrane hydrophobic core by a more fluid representation,
while using short-tailed lipids to maintain an atomistic description
of the head groups. The HMMM accelerates lipid dynamics without compromising
accurate description of the lipid head groups, which are key to the
interactions of peripheral proteins with membranes. The model has
been successfully applied to capture the spontaneous membrane binding
and insertion of individual phospholipids,[15] various membrane anchoring domains,[14,16] as well as
individual transmembrane helices.[17] A number
of other applications of the model are now in progress in our laboratory.[18−20]Despite its utility in accelerating insertion events, concerns
remain as to the degree to which the in silico changes
to the membrane perturb the energetic cost of partitioning a protein
into the membrane. To characterize the energetics of the HMMM model
and gain a better understanding of protein–membrane interactions
in the model, we report the potentials of mean force (PMF) of side
chain insertion into a HMMM membrane. These PMFs are compared to reported
experimental,[21] computational all-atom
(FULL-AA),[22] and coarse-grained (FULL-CG)[23] free energies. Reconstructed PMFs analyzed on
the basis of four regions within the membrane[22,24] demonstrate that the HMMM model accurately reproduces the free energy
of side chain partitioning at the membrane interface, an essential
feature needed for a proper description of protein–lipid interactions
in peripheral proteins. On the other hand, the HMMM in its present
form has difficulty describing membrane core energetics for all side
chains due to the fluid and slightly polar nature of the core solvent,
currently limiting the model’s use to peripheral proteins and
single-pass transmembrane proteins. We also compare the results to
previously reported hydrophobicity scales based on the free energy
of side chain insertion into lipid membranes. As the HMMM model was
designed to describe the interactions of peripheral proteins with
the membrane, we devote particular attention to the interactions of
the side chains with the interfacial regions of the membrane.
Methods
In order to assess the accuracy of the HMMM model in describing
the partitioning of proteins into membranes and isolate the impact
of individual residues on the overall protein–membrane interaction,
we prepared simple side chain analogues of 10 amino acids and calculated
the PMF for their insertion into a HMMM membrane. The analogues were
constructed by removing both the amino and carboxylate moieties of
each side chain and replacing the α-carbon by a hydrogen. The
new hydrogen was assigned a partial charge of +0.09, typical for an
aliphatic hydrogen in CHARMM,[25,26] and the charge on the
β-carbon was adjusted by −0.09 to maintain the net charge
of the side chain. The partitioning of the constructed side chain
analogues was investigated for 10 residues that span four major classes,
namely, (1) hydrophobic/aliphatic residues Ala (methane) and Ile (n-butane); (2) aromatic residues Trp (3-methylindole), Phe
(toluene), and Tyr (p-cresol); (3) polar residues
Asn (acetamide), Cys (methanethiol), and Ser (methanol); and (4) charged
residues Asp (acetate) and Arg (N-propylguanidinium).
The choices of amino acid analogues are identical to those used in
previous experimental[21] and computational[22,23] studies, which will be our primary basis for comparison. Wherever
possible, our methodology was identical to those of the reference
studies which used a conventional bilayer.[22,23]
System
Preparation with the HMMM Model
Each system
was constructed by placing two copies of a protein side chain analogue,
offset by 32.5 Å in the z-direction, in a pre-equilibrated
HMMM membrane containing phosphatidylcholine (PC) short-tailed lipids
(st-lipids) along with water and ions. The total charge of the system
was neutralized by adding two Na+ ions for the system with
Asp and two Cl– ions to the system with Arg (one
counterion for each copy of the analogue). The HMMM membrane used
in this study was made of 72 st-lipids (36 PClipids per leaflet)
with an area per lipid of 68 Å2, matching the experimentally
determined value for dioleoylphosphatidylcholine (DOPC).[27] 1,1-Dichloroethane (DCLE) was used as the liquid
solvent representation of the hydrophobic core of the bilayer.[28] Each system, slightly varying depending on the
side chain size, contained approximately 21 300 atoms, including
nearly 4300 water molecules.
Simulation Protocol and Analysis
Simulations were performed
using NAMD2.8[10] with the CHARMM36 force
field parameter set for lipids and small molecules,[25,29] the CHARMM27 parameter set for the side chains,[26,30] and the TIP3P model for water[31] in the
NPnAT (constant normal pressure, area, and temperature)
ensemble. Langevin dynamics with a damping coefficient of 0.5 ps–1 and the Langevin piston Nosé–Hoover
method[32,33] were employed to maintain the temperature
at 298 K and pressure at 1.0 atm. The long-range electrostatic forces
were calculated using the particle mesh Ewald (PME) method[34] with a grid density of 1 Å–3. The cutoff for van der Waals interaction was set at 13.5 Å
with a smoothing function applied after 10 Å. An integration
time step of 2 fs was used. In order to prevent artificially large,
out-of-plane fluctuations of the st-lipids and their occasional partitioning
into bulk water, we applied a weak harmonic constraint (0.05 kcal/mol·Å2) to the z-position to the carbonyl carbon
atoms of each st-lipid. The choice of the weak force constant allowed
for fluctuations of ±3.5 Å along the z-axis,
consistent with membrane fluctuations seen in a conventional bilayer.
No restraints were applied in the xy-plane, allowing
for rapid lateral lipid diffusion.
Umbrella Sampling
The umbrella sampling method was
used to calculate the PMFs for inserting the side chain analogues
into a HMMM membrane. Using the membrane normal (z-axis) as the reaction coordinate, the space to be sampled was divided
into 36 windows with neighboring windows separated by 1 Å. Since
each system contains two copies of the side chain analogue and each
copy is offset by 32.5 Å along the normal, the effective window
spacing is 0.5 Å. The force constant for the harmonic umbrella
potential was 7.17 kcal/mol·Å2. Data for each
simulation were collected for 10.5 ns per window. The first 500 ps
was considered equilibration time and not included in the analysis.
In aggregate, these simulations encompass more than 3.7 μs of
simulated trajectories. The free energy profiles were reconstructed
using the weighted histogram analysis method (WHAM).[35,36] The WHAM calculations and error estimates were carried out using
the g_wham program in the GROMACS package.[37,38] All data within 35 Å of the membrane center were used for the
WHAM calculation. Error estimates were calculated using the bootstrap
error analysis.[38−40]
Free-Energy Perturbation Calculations
Solvation free
energies were calculated using alchemical free-energy perturbation
(FEP).[41] In FEP calculations, side chain
analogues were alchemically solvated in a liquid of interest, namely,
DCLE, water, or dodecane. Growth of the side chain into solution was
controlled by the parameter λ, ranging from 0 to 1, which couples
the side chain to the Hamiltonian of the rest of the system.[42] A scaled-shifted soft-core potential[43] was used for van der Waals interactions to reduce
occurrences of singularities for small values of λ. Each simulation
was run in both directions: forward (solvation, λ from 0 to
1) and backward (desolvation, λ from 1 to 0). The calculations
were divided into 25 windows, where λ increased linearly by
0.04 between windows. Each window consisted of 10 ps of equilibration
and 250 ps of data collection, for a total of 13 ns for each side
chain analogue/solvent combination. Analysis of FEP results was performed
using the Bennett acceptance ratio[44] as
implemented in the ParseFEP plugin[45] of
VMD.[46]
Results and Discussion
The PMFs resulting from the umbrella sampling calculations were
analyzed on the basis of four distinct regions of the modeled membranes
(Figure 1). These regions correspond to the
changing properties of the membrane, and also allow direct comparison
to previous computational and experimental reports,[21,22,24,47] which made
use of this regional analysis scheme. The original definition of the
regions was based on the free volume accessible to spherical particles.[24] Here, region I (RI-core) is defined to be |z| ≤ 10 Å (with z = 0 representing
the midpoint of the membrane), where liquid DCLE, representing the
hydrophobic core of the HMMM membrane, predominates. Region II (RII-tails),
10 Å< |z| ≤ 17.5 Å,
is the region encompassing the acyl chains of the short lipid tails.
This region is predominantly composed of the acyl tails, and resembles
a soft polymer that introduces restrictions on rotational and translational
degrees of freedom of penetrants. Region III (RIII-heads), 17.5 Å
< |z| ≤ 25 Å, is the lipid headgroup
region which also contains water molecules and ions that are strongly
bound to the head groups. The RIII-heads region contains most of the
phosphate atomic density and is the interfacial region of the membrane.
Region IV (RIV-water) includes all atoms with |z|
> 25 Å and contains primarily bulk water. The HMMM model[14,18] was developed to facilitate studies of peripheral protein interactions
with membranes; therefore, special attention in the following analyses
is devoted to RII-tails and RIII-heads regions, where most of the
membrane-anchoring protein domains appear to interact with lipids.[5,14] For ease of understanding, we use descriptive abbreviated names
(e.g., RI-core) throughout the text.
Figure 1
(top) A snapshot of the system used to
calculate the PMFs of membrane
insertion of the 10 side chain analogues. In the HMMM membrane, DCLE
is shown in green, bulk water in blue, and the short-tailed PC lipids
as sticks with carbon in gray, oxygen in red, nitrogen in blue, and
phosphorus in gold. The Ala analogue, methane, is included to demonstrate
the initial positioning of the two copies in the system. (bottom)
The atomic density of various chemical groups in the HMMM system.
The dashed lines show the demarcation between the different regions
used in the analysis of PMF plots. Region I, RI-core, is defined to
be the area in the center of the membrane with |z| ≤ 10 Å and is composed mostly of liquid DCLE. Region
II, RII-tails, occupies the area 10 Å < |z| ≤ 17.5 Å and encompasses the tails of the st-lipids
as well as the glycerol moiety and some phosphate density. Region
III, RIII-heads, consists of 17.5 Å < |z|
≤ 25 Å and contains the majority of the phosphate density
as well as all of the choline density and associated water molecules
and ions. Region IV, RIV-water, is |z| > 25 Å
and is comprised of bulk aqueous solution.
(top) A snapshot of the system used to
calculate the PMFs of membrane
insertion of the 10 side chain analogues. In the HMMM membrane, DCLE
is shown in green, bulk water in blue, and the short-tailed PClipids
as sticks with carbon in gray, oxygen in red, nitrogen in blue, and
phosphorus in gold. The Ala analogue, methane, is included to demonstrate
the initial positioning of the two copies in the system. (bottom)
The atomic density of various chemical groups in the HMMM system.
The dashed lines show the demarcation between the different regions
used in the analysis of PMF plots. Region I, RI-core, is defined to
be the area in the center of the membrane with |z| ≤ 10 Å and is composed mostly of liquid DCLE. Region
II, RII-tails, occupies the area 10 Å < |z| ≤ 17.5 Å and encompasses the tails of the st-lipids
as well as the glycerol moiety and some phosphate density. Region
III, RIII-heads, consists of 17.5 Å < |z|
≤ 25 Å and contains the majority of the phosphate density
as well as all of the choline density and associated water molecules
and ions. Region IV, RIV-water, is |z| > 25 Å
and is comprised of bulk aqueous solution.The main goal of this report is to quantitatively assess
the accuracy
of the HMMM model membrane in describing protein side chain insertion
into distinct regions of a membrane and, in doing so, to facilitate
further development and application of model membranes. We compare
our calculations to the previously reported computational studies
of full-tail membrane models described with all-atom OPLS (FULL-AA)[22] and coarse-grained MARTINI (FULL-CG)[23] force fields. Additionally, we compare our results
to the free energy values reported on the basis of experiments by
Wimley and White (WW),[47] Hessa et al.,[48] Radzicka and Wolfenden (RW),[21] and Moon and Fleming.[49]
Aliphatic Side
Chains
Aliphatic protein side chains
are critical in the binding and insertion of peripheral proteins into
the membrane. The calculated PMFs for insertion of representative
aliphatic side chains, Ala and Ile, into the HMMM membrane show excellent
agreement, both in the shape and in the absolute values, when compared
to the FULL-AA and FULL-CG calculations (Figure 2). The PMFs display a small (∼1 kcal/mol or 1.5 kT) barrier
at the interface between water and the membrane, the RIII-heads region,
followed by an attractive basin that reflects the hydrophobic nature
of the side chains. The free energy steeply decreases from the RIII-heads
and RII-tails regions into the RI-core region as the side chains move
into a less dense and more nonpolar environment. The liquid core of
the HMMM reproduces the free energy of transfer from water to a full-tail
membrane core for both the linear Ile side chain (n-butane) and for the nearly spherical Ala (methane). The absolute
values of the transfer free energies of Ala and Ile from water into
the center of the membrane (RI-core region) agree very well with the
values reported from early experiments of Radzicka and Wolfenden[21] on partitioning of the same side chain analogues
between water and cyclohexane: Ala, −2.0 kcal/mol (HMMM) vs
−1.8 kcal/mol (RW[21]) and Ile, −4.7
kcal/mol (HMMM) vs −4.9 kcal/mol (RW[21]).
Figure 2
PMFs for representative aliphatic side chain analogues, Ala (left)
and Ile (right). Data are presented for the HMMM membrane (blue),
FULL-AA (black),[22] and FULL-CG (purple).[23] No FULL-CG data was reported for Ala. All PMFs
are presented by setting the free energy to zero in aqueous solution.
Regions I–IV are defined in Figure 1. Error estimates were obtained using bootstrap analysis.
PMFs for representative aliphatic side chain analogues, Ala (left)
and Ile (right). Data are presented for the HMMM membrane (blue),
FULL-AA (black),[22] and FULL-CG (purple).[23] No FULL-CG data was reported for Ala. All PMFs
are presented by setting the free energy to zero in aqueous solution.
Regions I–IV are defined in Figure 1. Error estimates were obtained using bootstrap analysis.Free energy of Ile transfer from water into the
center of the RII-tails
region (−3.0 kcal/mol at z = 13.75 Å)
is in closer agreement with the experimental measurements by Wimley
and White of the partitioning of specifically designed peptides from
water to the POPC membrane interface (−4.5 kcal/mol)[47] than the calculated value for the transfer from
water into the center of the RIII-heads region (0.75 kcal/mol at z = 21.25 Å). This suggests that the interfacial interactions
between membrane and peptides reported by Wimley and White[47] were likely reflecting localization of the side
chain at the beginning of the lipid tails, just below the lipid head
groups, which agrees well with computational results for similar systems.[50] The small differences in the absolute values
between the HMMM and experimental measures can be attributed to the
absence of the protein backbone in our calculations.
Aromatic Side
Chains
Aromatic side chains studied here
(Tyr, Trp, Phe) display a more complex behavior due to variations
in shape, hydrogen bonding capacity, and dipole moments.[22,51] The free energies of aromatic side chain insertion into all regions
of HMMM agree well with FULL-AA[22] and FULL-CG[23] PMFs, except in RI-core where insertion into
the liquid DCLE is more favorable than it is in FULL-AA or FULL-CG
membranes, and will be discussed at length below (Figure 3). Tyr and Trp are nearly twice as overstabilized
as Phe in the RI-core region of the HMMM membranes as compared to
full-tailed membranes (FULL-AA[22] and FULL-CG[23]).
Figure 3
PMFs for aromatic side chain analogues, Phe
(top), Tyr (middle),
and Trp (bottom). Data are presented for the HMMM membrane (blue),
FULL-AA (black),[22] and FULL-CG (purple).[23] All PMFs are presented by setting the free energy
to zero in aqueous solution. Regions I–IV are defined in Figure 1. Error estimates were obtained using bootstrap
analysis.
PMFs for aromatic side chain analogues, Phe
(top), Tyr (middle),
and Trp (bottom). Data are presented for the HMMM membrane (blue),
FULL-AA (black),[22] and FULL-CG (purple).[23] All PMFs are presented by setting the free energy
to zero in aqueous solution. Regions I–IV are defined in Figure 1. Error estimates were obtained using bootstrap
analysis.The RII-tails region, particularly
the lipid tail–headgroup
interface, displays stabilization relative to the solution in the
calculated PMFs (Figure 3). Trp and Tyr are
especially known for their abundance in the “interfacial belt”
of membrane proteins and for their role in anchoring transmembrane
helices.[51−53] Indeed, we observe the deepest minimum in the PMF
of Trp (−5.0 kcal/mol), followed by slightly shallower minima
for Tyr (−3.5 kcal/mol) and Phe (−4.1 kcal/mol) (Figure 3). While preserving the general form of the PMFs,
the free energies within the RII-tails region deviate slightly but
are in good agreement with previous computational[22,23] and experimental data (adjusted to the value for Ala) on interfacial
free energies:[47] Trp, −2.85 kcal
(HMMM) vs −3.7 kcal/mol (FULL-AA[22]) vs −2.0 kcal/mol (WW[47]); Tyr,
−2.15 kcal/mol (HMMM) vs −2.0 kcal/mol (FULL-AA) vs
−1.1 kcal/mol (WW); and Phe, −2.25 kcal (HMMM) vs −1.8
kcal/mol (FULL-AA) vs −1.3 kcal/mol (WW).The RI-core
region of the HMMM membrane shows the largest free
energy deviation from the FULL-AA[22] and
FULL-CG[23] data for aromatic side chains
(Figure 3). Insertion free energies of aromatic
side chains to the center of the membrane are more favorable in the
liquid core of HMMM than in the center of FULL-AA membranes[22] by 4 kcal/mol for Tyr and Trp versus 2 kcal/mol
for Phe. These differences can be partially attributed to additional
translational and rotational freedom offered by the liquid DCLE as
compared to the lipid tails in the center of the FULL-AA and FULL-CG
membranes. In RI-core of the HMMM, bulky side chains are free to rotate,
and are not constrained laterally by lengthy acyl tails.This
is supported by the distribution of the orientation of Tyr
in the different regions of the HMMM (Figure 4). The orientation of Tyr in RI-core of the HMMM is random, similar
to RIV-water, demonstrating that Tyr is not constrained in orientation
in the membrane interior. In RII-tails, where Tyr primarily interacts
with acyl tails, Tyr preferentially orients itself along the membrane
normal in both HMMM and FULL-AA systems.[22] Since the interior of a HMMM membrane is liquid, we expect all larger
side chains to freely sample orientational space, lowering the free
energy in RI-core relative to FULL-AA values by at least 5/2 kT, with
3 rotational and 2 translational additional degrees of freedom that
can be populated.
Figure 4
Distribution of the orientation of Tyr at different regions
in
the HMMM membrane: RI-core (top), RII-tails (middle), and RIV-water
(bottom). The distribution of orientations in RI-core and RIV-water
is fairly unbiased, whereas the orientation in RII-tails shows a dramatic
skew toward remaining parallel to the membrane normal. The orientation
is determined by measuring the angle between the membrane normal and
the long axis of Tyr (i.e., the vector from the carbon at the para position to the phenol oxygen atom).
Distribution of the orientation of Tyr at different regions
in
the HMMM membrane: RI-core (top), RII-tails (middle), and RIV-water
(bottom). The distribution of orientations in RI-core and RIV-water
is fairly unbiased, whereas the orientation in RII-tails shows a dramatic
skew toward remaining parallel to the membrane normal. The orientation
is determined by measuring the angle between the membrane normal and
the long axis of Tyr (i.e., the vector from the carbon at the para position to the phenoloxygen atom).The polar nature of DCLE also contributes to discrepancies
in RI-core
between HMMM and FULL-AA PMFs. DCLE has been shown to efficiently
orient its dipole around neighboring polar groups in order to reduce
the energy penalty for burying these species.[28] Thus, the HMMM and FULL-AA PMFs in RI-core for Trp and Tyr are more
greatly separated than the Phe PMFs, due to their polar functional
groups that orient surrounding DCLE. This can also be seen from the
solvation free energies for solvating Tyr and Phe in DCLE, water,
and dodecane (Table 1). ΔDCLE-waterTyr > ΔDCLE-waterPhe suggests that DCLE
has
water-like interactions with the hydroxyl of Tyr, as the two values
should be the same when considering the solvation of the phenyl ring.
This hypothesis is also supported by the fact that ΔDCLE-dodecaneTyr < ΔDCLE-dodecanePhe, suggesting that
there are additional stabilizing interactions when solvating Tyr into
DCLE relative to solvating Phe.
Table 1
Free Energy (kcal/mol)
of Side Chain
Solvation in Different Solvents Calculated Using the Free Energy Perturbation
Method
DCLE
water
dodecane
ΔDCLE-water
Δdodecane-water
ΔDCLE-dodecane
Tyr
–6.31 ± 0.07
–4.27 ± 0.06
–4.61 ± 0.07
–2.04
–0.34
–1.70
Phe
–4.57 ± 0.05
0.29 ± 0.05
–4.02 ± 0.06
–4.89
–4.31
–0.55
The solvation free
energy differences for Tyr and Phe in water
relative to DCLE for Tyr and Phe calculated using FEP (−2.04
and −4.28 kcal/mol, respectively) agree closely with the free
energy difference between RIV-water and RI-core recovered using umbrella
sampling (Figure 3). We believe the differences
in the free energy of insertion into the RI-core region are due to
an increased entropic stabilization of these bulky groups and the
polar nature of DCLE. As the HMMM model is designed primarily for
studies of peripheral proteins interacting with the membrane, the
variances in the free energy of insertion into the membrane center
are unlikely to be of a major concern for specific systems of interest.
Polar Side Chains and Cysteine
Representative polar
side chains, Ser (methanol) and Asn (acetamide), show good agreement
with the FULL-AA[22] and FULL-CG[23] PMFs in the RIII-heads and RIV-water regions
(Figure 5), while the minima in the RII-tails
region appear to be more shallow in the HMMM membrane. Interestingly,
the FULL-CG PMF calculated with the MARTINI coarse-grained force field[23] similarly failed to capture the minimum in RII-tails
for Asn (Figure 5). We believe that dipole
interactions are essential to capturing the correct depth of the minima
in polar groups, which may have arisen due to favorable interactions
between the polar moieties and the acyl tail carbonyl. These interactions
would be perturbed in a coarse-grain representation by an inaccurate
dipole representation, and are perturbed by DCLE occasionally intercalating
into the acyl tail region.[14] Similar to
the aromatic amino acids, the PMFs for polar amino acids in the HMMM
show overstabilization in the RI-core region compared to FULL-AA and
FULL-CG. This is again due to the dipole–dipole interactions
between the side chains and DCLE, and their tumbling within the solvent.
Figure 5
PMFs for
representative polar side chain analogues, Asn (top),
Ser (middle), and Cys (bottom). Data are presented for the HMMM membrane
(blue), FULL-AA (black),[22] and FULL-CG
(purple).[23] All PMFs are presented by setting
the free energy to zero in aqueous solution. Regions I–IV are
defined in Figure 1. Error estimates were obtained
using bootstrap analysis.
PMFs for
representative polar side chain analogues, Asn (top),
Ser (middle), and Cys (bottom). Data are presented for the HMMM membrane
(blue), FULL-AA (black),[22] and FULL-CG
(purple).[23] All PMFs are presented by setting
the free energy to zero in aqueous solution. Regions I–IV are
defined in Figure 1. Error estimates were obtained
using bootstrap analysis.The calculated PMF for Cys is in good agreement with the
FULL-AA
PMF[22] in regions II–IV (Figure 5), particularly the slope of the free energy from
the RIII-heads to the RII-tails regions, which is mainly due to the
amphipathic nature of the side chain. Once again, interactions between
the side chain and DCLE solvent lead to a low calculated free energy
within RI-core of the HMMM relative to comparison membranes.
Charged
Side Chains
Calculated PMFs of representative
charged side chains, Asp (acetate) and Arg (N-propylguanidinium),
show good agreement with both types of full-tail lipid calculations,
FULL-AA[22] and FULL-CG,[23] in the regions RIII-heads and RIV-water (Figure 6). Negatively charged Asp displays a continuous
increase in free energy as it moves from bulk water to the membrane
center. For a charged species like Asp, it is unsurprising that dipole
interactions between the carboxylate of Asp and DCLE result in a stabilization
of Asp in RI-core relative to comparison membranes. The flat profile
for Asp within the interior of RI-core reflects the position at which
Asp is fully immersed in DCLE, and the further insertion results in
no free energy change.
Figure 6
PMFs for representative charged side chain analogues,
Asp (left)
and Arg (right). Data are presented for the HMMM membrane (blue),
FULL-AA (black),[22] and FULL-CG (purple).[23] All PMFs are presented by setting the free energy
to zero in aqueous solution. Regions I–IV are defined in Figure 1. Error estimates were obtained using bootstrap
analysis.
PMFs for representative charged side chain analogues,
Asp (left)
and Arg (right). Data are presented for the HMMM membrane (blue),
FULL-AA (black),[22] and FULL-CG (purple).[23] All PMFs are presented by setting the free energy
to zero in aqueous solution. Regions I–IV are defined in Figure 1. Error estimates were obtained using bootstrap
analysis.Since Arg is amphipathic, our
simulations, as well as the FULL-AA[22] and
FULL-CG[23] simulations
that use an identical protocol (Figure 6),
show a sizable free energy well across RII-tails and RIII-heads. The
wide minimum can be attributed to the interaction of Arg’s
charged guanadinium group with the polar region of up to three lipids
(Figure 7) simultaneous to partitioning of
its alkyl chain into the membrane core, creating a significantly favorable
environment and lowering the free energy in these regions. Indeed,
this orientation is so favorable that it has been proposed to facilitate
membrane penetration by arginine-rich peptides,[54] such as antimicrobial peptides. When the guanadinium starts
to be buried in the hydrophobic region (RI-core), however, the energetic
penalty rapidly rises, as is expected for burying naked charge in
a membrane.[21,22,55] These high energy penalties arise from the deformation of the membrane
to hydrate the charge (Figure 8), which accounts
for a significant portion of the energy penalty,[55] which may be reduced in vivo by the surrounding
protein environment.[56]
Figure 7
Snapshot of the system
with an Arg side chain analogue (spheres)
in the interfacial region (RIII-heads) of the HMMM membrane. Oxygen
atoms (red) of PC lipid head groups (sticks) interact with hydrogen
atoms (white) of the guanidinium group of Arg. Other atoms shown are
carbon (gray), nitrogen (blue), and phosphorus (gold).
Figure 8
Snapshots of systems with polar and charged residues that
display
formation of the water defects when amino acids are positioned: at
the membrane center - charged Arg (A) and near the membrane center
- polar Asn (B).
Snapshot of the system
with an Arg side chain analogue (spheres)
in the interfacial region (RIII-heads) of the HMMM membrane. Oxygen
atoms (red) of PClipid head groups (sticks) interact with hydrogen
atoms (white) of the guanidinium group of Arg. Other atoms shown are
carbon (gray), nitrogen (blue), and phosphorus (gold).Snapshots of systems with polar and charged residues that
display
formation of the water defects when amino acids are positioned: at
the membrane center - charged Arg (A) and near the membrane center
- polar Asn (B).Partitioning of polar
and charged side chains into the membrane
has been shown to be accompanied by the formation of stable water-filled
membrane defects.[22,57] Additionally, Johansson and Lindahl
have shown correlation between the hydration level of transmembrane
helices and hydrophobicity scales.[57] During
our simulations, we observed formation of a stable water-filled defect
when charged side chains, Arg or Asp, are positioned in the center
of HMMM membrane (Figure 8). The water-filled
defect was the widest at the base on the membrane interface and was
narrowed down to a few water molecules surrounding the side chain
in the center of the membrane. In the case of a polar side chain,
Asn, a water-filled defect is only present when Asn is positioned
closer to the ends of the tails and not when the residue is near the
center of the membrane (Figure 8).
PMF Comparison
to Hydrophobicity Scales
Through analysis
of the calculated free energy profiles at particular points along
the HMMM normal, we can compare the transfer free energy from solution
to a specific region of the HMMM with developed hydrophobicity scales.[21,22,47−49] These scales
are based on different experimental measurements, including partitioning
of side chain analogues from water to cyclohexane,[21] partitioning of specifically designed pentapeptides from
water to the interface of the membrane,[47] membrane protein insertion into a membrane via the Sec translocon,[48] and equilibrium between folded and unfolded
states of a membrane protein.[49] Naturally,
these different experiments are measuring the energetic difference
between the aqueous solution and different regions of a membrane.
As the HMMM model is designed to capture partitioning into the membrane
interface, the Wimley–White hydrophobicity scale[47] based on partitioning of pentapeptides to the
membrane interface is of particular importance for this study. Comparing
the insertion free energy of the HMMM to any experimental scale is
not intended to reproduce exact free energy differences. Due to the
differences in protocols between each scale, the uncertainty
in exactly which region the peptides partition, and the fact that
the simulation system used here does not replicate any of these protocols,
there will necessarily be differences in insertion free energies between
the HMMM and experimental studies. Computational agreement with experimental
free energy scales is improved if side chain interactions with neighboring
residues are also included.[58,59] The purpose of this
discussion is merely to compare trends in free energy differences
for individual amino acids between hydrophobicity scales to gain a
better understanding of where the amino acids might partition in experimental
studies.First, we compare HMMM free energies to the computational
FULL-AA data reported for a full-tail membrane[22] for different regions from the center of the membrane to
lipid head groups (Figure 9). The correlation
between all regions studied (Figure 9) suggests
that the overall energetic trends for side chain–membrane interactions
are preserved in the HMMM in all four regions. The slopes of the trend
lines for all four membrane regions are also near unity (Figure 9), suggesting that the conversion of a full-tail
membrane to the HMMM preserves population-based interaction statistics
in all four regions of membrane. Notably, though, the RIV-water →
RI-core trend line (Figure 9) has the largest
vertical shift of +2.52 kcal/mol with respect to the FULL-AA data,[22] a systematic shift in the free energy profiles
as a result of the increased entropic contribution due to the liquidity
of the DCLE and the larger dipole of DCLE relative to acyl tails that
promotes stronger interaction between amino acids with polar groups
and the membrane core which replace the membrane core in the HMMM.
In regions RII-tail–RIV-water, where DCLE is less prevalent,
we expect and observe native-like membrane interactions and forces
in the HMMM system. The preservation of contacts and interaction patterns
upon membrane conversion has been observed in studies on peripheral
proteins, specifically coagulation factor binding domains and cytochrome
P450.[14,16]
Figure 9
Comparison of the transfer free energy of the
side chains from
solution (RIV-water) to the regions within the membrane. The points
for RII-tails and RIII-heads were taken at the midpoint of the region
(z = 13.75 Å and z = 21.25
Å, respectively), while the RI-core position was taken to be
the bilayer center. An additional measurement was taken at the interface
between RII-tails and RIII-heads (RII/RIII, at z =
17.5 Å). The positions of points along the x-axis are determined by the HMMM free energy values, while the y-axis values were computed for a full-tail membrane.[22] The dotted lines represent the linear fit of
the points, and essential fit information is reported.
Comparison of the transfer free energy of the
side chains from
solution (RIV-water) to the regions within the membrane. The points
for RII-tails and RIII-heads were taken at the midpoint of the region
(z = 13.75 Å and z = 21.25
Å, respectively), while the RI-core position was taken to be
the bilayer center. An additional measurement was taken at the interface
between RII-tails and RIII-heads (RII/RIII, at z =
17.5 Å). The positions of points along the x-axis are determined by the HMMM free energy values, while the y-axis values were computed for a full-tail membrane.[22] The dotted lines represent the linear fit of
the points, and essential fit information is reported.Comparisons of transfer free energies calculated
with the HMMM
model to experimental hydrophobicity scales[21,47−49] show good agreement for most side chains where the
HMMM design matches experimental conditions, such as in RII-tails
and RIII-heads. In particular, comparison of free energy values for
RIV-water → RII-tails transfer in the HMMM membrane to these
scales (Figure 10) agrees best with the hydrophobicity
scale proposed by Wimley and White, where a designed pentapeptide
interacts with the membrane interface.[47] The WW hydrophobicity scale is most similar to the conditions in
RII-tails, as the peptide explores the region corresponding to the
free energy wells for hydrophobic and aromatic side chains (Figures 2 and 3). The behavior in
the HMMM for Arg is much more different than that of most experiments.
Due to the favorable interactions Arg can form in our simulation system
(Figure 7) while keeping its long tail buried
in the membrane, our simulations show Arg insertion to be more favorable
than the consensus of experimental findings, where such configurations
for Arg are not possible.
Figure 10
Comparison of hydrophobicity scales to the
RIV-water–RII-tails
transfer free energy of the HMMM. Published hydrophobicity scales
from Wimley and White,[47] Hessa et al.,[48] Radzicka and Wolfenden,[21] and Moon and Fleming[49] were compared
against the transfer free energy from RIV-water to the midpoint of
RII-tails in the HMMM model. The dotted lines represent the linear
fit of the points, and essential fit information is reported.
Comparison of hydrophobicity scales to the
RIV-water–RII-tails
transfer free energy of the HMMM. Published hydrophobicity scales
from Wimley and White,[47] Hessa et al.,[48] Radzicka and Wolfenden,[21] and Moon and Fleming[49] were compared
against the transfer free energy from RIV-water to the midpoint of
RII-tails in the HMMM model. The dotted lines represent the linear
fit of the points, and essential fit information is reported.A comparison of free energy for
RIV-water → RI-core transfer
in the HMMM membrane to the same scales (Figure 11) shows good agreement with the cyclohexane–water scale
proposed by Radzicka and Wolfenden[21] and
modest agreement with scales based on a transfer of side chains within
larger transmembrane proteins.[48,49] Agreement with the
cyclohexane–water scale, as well a related octanol–water
scale[60] (Figure S1, Supporting Information), is based on the use of an organic
solvent-rich RI-core in the HMMM. The low slopes of the trendline
that compares the two experimental studies employing membrane proteins[48,49] to the HMMM transfer free energies (Figure 11) might be a result of the complexity of the environment surrounding
the side chains. Rather than proceeding from a fully solvated to a
fully inserted side chain, as in the case of side chain analogues,
in the presence of a protein, interactions between neighboring residues
lower the energetic cost for membrane entry by providing favorable
interactions for buried side chains.[59] Comparison
to the computational and experimental hydrophobicity scales indicates
the relative accuracy of the HMMM model membranes in capturing the
energetics of the membrane interface.
Figure 11
Comparison of hydrophobicity
scales to the RIV-water–RI-core
transfer free energy of the HMMM. Published hydrophobicity scales
from Wimley and White,[47] Hessa et al.,[48] Radzicka and Wolfenden,[21] and Moon and Fleming[49] were compared
against the transfer free energy from RIV-water to the midpoint of
the membrane (within RI-core) in the HMMM model. The dotted lines
represent the linear fit of the points, and essential fit information
is reported.
Comparison of hydrophobicity
scales to the RIV-water–RI-core
transfer free energy of the HMMM. Published hydrophobicity scales
from Wimley and White,[47] Hessa et al.,[48] Radzicka and Wolfenden,[21] and Moon and Fleming[49] were compared
against the transfer free energy from RIV-water to the midpoint of
the membrane (within RI-core) in the HMMM model. The dotted lines
represent the linear fit of the points, and essential fit information
is reported.
Conclusions
The
energetic characterization of the highly mobile membrane mimetic
(HMMM)[14] representation has been presented.
The strength of the HMMM model is in its accelerated lipid dynamics,
which expedites the formation of optimal protein–lipid interactions,
while maintaining an atomistic description of the lipid head groups.
A potential drawback of the use of the liquid organic solvent to represent
the bilayer core is the introduction of additional fluidity of the
core of the membrane and additional polarity, as DCLE[14,28] is not as hydrophobic as the lipid tails in a conventional full-tail
membrane. Nevertheless, this report shows that the HMMM model captures
the interaction energetics of side chains along the membrane interface,
a feature that is essential for studying peripheral proteins.We demonstrate that the energetics of insertion into the interfacial
membrane regions for representatives of all classes of protein side
chains are generally in good agreement with previously reported computation-
and experiment-based values. On the other hand, we observe overstabilization
of aromatic, polar, and charged side chains in the center of the HMMM
membrane due to the more liquid and polar nature of the organic solvent
currently used in HMMM (DCLE) compared to acyl lipid tails. These
variations do not appear to interfere with the phenomena at the membrane
interface, for which HMMM was specifically developed and is currently
used.[14,16−20] In particular, it is of value that the HMMM model
is capable of capturing the energetic cost of Trp and Tyr insertion
into the membrane interface. These amino acids are known to serve
as anchors of the transmembrane helices,[51−53] especially
in single-pass membrane proteins where they ensure proper positioning
and tilting within the membrane bilayer. We expect that the HMMM will
perform well with single-pass transmembrane helices where aliphatic
residues in the core and aromatic side chains at the interface are
the most important determinants of the depth of insertion and tilting.
Further development to address inaccuracies in the membrane core and
to extend the applicability of the model to larger transmembrane systems
is currently underway.
Authors: Dmitriy Krepkiy; Mihaela Mihailescu; J Alfredo Freites; Eric V Schow; David L Worcester; Klaus Gawrisch; Douglas J Tobias; Stephen H White; Kenton J Swartz Journal: Nature Date: 2009-11-26 Impact factor: 49.962
Authors: Christopher G Mayne; Mark J Arcario; Paween Mahinthichaichan; Javier L Baylon; Josh V Vermaas; Latifeh Navidpour; Po-Chao Wen; Sundarapandian Thangapandian; Emad Tajkhorshid Journal: Biochim Biophys Acta Date: 2016-05-06
Authors: Josh V Vermaas; Javier L Baylon; Mark J Arcario; Melanie P Muller; Zhe Wu; Taras V Pogorelov; Emad Tajkhorshid Journal: J Membr Biol Date: 2015-05-22 Impact factor: 1.843
Authors: Gregory T Tietjen; Javier L Baylon; Daniel Kerr; Zhiliang Gong; J Michael Henderson; Charles T R Heffern; Mati Meron; Binhua Lin; Mark L Schlossman; Erin J Adams; Emad Tajkhorshid; Ka Yee C Lee Journal: Biophys J Date: 2017-10-03 Impact factor: 4.033
Authors: Michael J Hallock; Alexander I Greenwood; Yan Wang; James H Morrissey; Emad Tajkhorshid; Chad M Rienstra; Taras V Pogorelov Journal: Biochemistry Date: 2018-12-04 Impact factor: 3.162