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FEATURE ARTICLE Assembly of Lipids and Proteins into Lipoprotein Particles Amy Y. Shih,†,‡ Anton Arkhipov,‡,§ Peter L. Freddolino,†,‡ Stephen G. Sligar,†,‡,| and Klaus Schulten*,†,‡,§ Center for Biophysics and Computational Biology, Beckman Institute for AdVance Science and Technology, Departments of Physics and Biochemistry, UniVersity of Illinois at UrbanasChampaign, Urbana, Illinois 61801 ReceiVed: March 23, 2007; In Final Form: June 21, 2007
The self-assembly of reconstituted discoidal high-density lipoproteins, known as nanodiscs, was studied using coarse-grained molecular dynamics and small-angle X-ray scattering. In humans, high-density lipoprotein particles transport cholesterol in the blood and facilitate the removal of excess cholesterol from the body. Native high-density lipoprotein exhibits a wide variety of shapes and sizes, forming lipid-free/poor, nascent discoidal, and mature spherical particles. Little is known about how these lipoprotein particles assemble and transform from one state to another. Multiple 10 µs coarse-grained simulations reveal the assembly of discoidal high-density lipoprotein particles from disordered protein-lipid complexes. Small-angle X-ray scattering patterns were calculated from the final assembled structures and compared with experimental measurements carried out for this study to verify the accuracy of the coarse-grained simulations. Results show that hydrophobic interactions assemble, within several microseconds, the amphipathic helical proteins and lipids into roughly discoidal particles, while the proteins assume a final approximate double-belt configuration on a slower time scale.
Introduction The assembly of protein-lipid particles is a complex, dynamic process vital to the transport of cholesterol by highdensity lipoproteins (HDLs) in the blood. The primary protein component of human HDL is apolipoprotein A-I (apo A-I), a 243-residue amphipathic protein containing an N-terminal globular domain and a primarily helical C-terminal lipid binding domain.1 Apo A-I is synthesized in the liver and intestines and excreted into the blood, initially forming lipid-free/poor particles. The efflux of lipids and cholesterol from peripheral tissues results in the formation of discoidal HDL particles. Continued absorption of lipids and cholesterol and the conversion of cholesterol to esterified cholesterol by the enzyme lecithin cholesterol acyl transferase results in the formation of spherical lipoprotein particles. These mature spherical HDL particles continue to grow in size by accumulating additional lipid and cholesterol and are eventually degraded and recycled in the liver.2 The assembly of lipoprotein particles from lipid and proteins is essential for maintaining human health and also poses a fascinating challenge to the physical chemistry of molecular assembly. Although two crystal structures of lipid-free human apo A-I have been solved,3,4 a structure of HDL in any of its lipid associated states is lacking and, due to the expected disordered * To whom correspondence should be addressed. E-mail: kschulte@ ks.uiuc.edu. † Center for Biophysics and Computational Biology. ‡ Beckman Institute for Advanced Science and Technology. § Department of Physics. | Department of Biochemistry.
Figure 1. Coarse-grained representation of a discoidal HDL particle. The protein-lipid particle is formed by two identically redesigned28,29 apolipoproteins in a double-belt configuration (shown in blue and green) wrapped around a lipid bilayer (shown in dark and light brown).
character of lipids, may never be attainable. Several models have been proposed for discoidal HDL based on a variety of experimental5-11 and theoretical1,12-26 evidence. These include the picket-fence,15 double-belt,17 and helical-hairpin models.14 In the picket-fence model, the protein helices are oriented parallel to the lipid acyl chains, while, in both the double-belt and helical-hairpin models, the proteins are oriented perpendicular to the lipid acyl chains. In the double-belt model, the two apo A-I strands are wrapped around a lipid bilayer core in a beltlike fashion, as shown in Figure 1, whereas, in the helicalhairpin model, each strand of apo A-I forms a single hairpin turn, resulting in intrahelical protein interactions unlike the interhelical interactions found in the double-belt model. Most experimental evidence rules out the picket-fence model, sug-
10.1021/jp072320b CCC: $37.00 © 2007 American Chemical Society Published on Web 08/14/2007
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Amy Y. Shih received a B.S. in Biochemistry from the University of Michigan in 1999 and a M.S. in Computer Science from Eastern Michigan University in 2003. She is currently a Ph.D. candidate in Biophysics and Computational Biology at the University of Illinois at Urbana-Champaign, doing research under the guidance of Klaus Schulten and Stephen G. Sligar. Her research uses combined computational and experimental methods to study the structure and assembly of lipoprotein particles.
Anton Arkhipov received a B.S. and M.S. in Physics from the Moscow Institute of Physics and Technology in 2002 and 2004, respectively. He then became a graduate student in Physics at the University of Illinois at Urbana-Champaign, joining Klaus Schulten’s group. His research focuses on the development of coarse-grained models for molecular dynamics simulations and on studying the mechanics of macromolecular assemblies.
Peter L. Freddolino received a B.S. in Biology from the California Institute of Technology in 2004, at which point he joined the research group of Klaus Schulten. Peter is currently an NSF Graduate Research Fellow and Ph.D. candidate in Biophysics and Computational Biology at the University of Illinois at Urbana-Champaign. His current research involves the development and application of multiscale simulations to study large biological aggregates.
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Stephen G. Sligar received his Ph.D. in Physics from the University of Illinois at Urbana-Champaign in 1975. Dr. Sligar holds the I. C. Gunsalus endowed chair in Biochemistry at the University of Illinois at Urbana-Champaign. His current research centers on understanding the structure and mechanistic function of metalloenzymes and membrane bound receptors and transporters.
Klaus Schulten received his Ph.D. from Harvard University in 1974. He is Swanlund Professor of Physics at the University of Illinois at Urbana-Champaign. His professional interests are theoretical physics and theoretical biology. His current research focuses on the structure and function of supramolecular systems in the living cell, as well as on the development of nonequilibrium statistical mechanical descriptions and efficient computing tools for structural biology.
gesting instead the double-belt model for discoidal HDL particles.5-11 Reconstituted HDL (rHDL) is commonly used in experimental studies of discoidal HDL particles and is thought to be structurally equivalent to native HDL. rHDL can be assembled from a starting mixture of detergent solubilized lipid and apo A-I protein. The self-assembly procedure is then initiated upon the removal of the detergent27 and results in the formation of discoidal HDL particles. Nanodiscs are a particular form of rHDL particles in which the self-assembly procedure has been optimized through the use of specific ratios of starting components and through the use of engineered, namely, appropriately truncated, apo A-I protein, termed membrane scaffold protein. In particular, the original membrane scaffold protein28 (named MSP1) was synthesized to reproduce the 200-residue C-terminal lipid binding domain of apo A-I, i.e., an apo A-I with the first 43 N-terminal residues removed (apo A-I ∆(1-43)). Unlike native discoidal HDL, nanodiscs are homogeneous particles of discrete size and composition.28,29 Nanodiscs can be exploited as soluble platforms for embedding membrane proteins.30-43 Since embedded membrane proteins often require nanodisc platforms of varying diameters (whether larger or smaller than the initial 9.6 nm29), scaffold
Feature Article proteins with additional truncations or extensions have been engineered, which result in nanodiscs of different diameters.29 Nanodiscs made with MSP1 ∆(1-11) and MSP1 ∆(1-22) membrane scaffold proteins, analogous to apo A-I ∆(1-54) and apo A-I ∆(1-65), respectively, in which 11 and 22 further residues are deleted from MSP1, resulted in particles of the same diameter as original MSP1 nanodiscs,23,29 suggesting that the truncated residues are not involved in forming nanodiscs. Given their ability to self-assemble into homogeneous particles of identical size and composition (unlike native HDL particles which are heterogeneous), and due to their extensive characterization,28,29,44 nanodiscs furnish an ideal system for computer simulations investigating HDL particles and are utilized in our studies on lipoprotein assembly. The present study on nanodisc self-assembly complements a recent computational and experimental investigation of nanodisc disassembly with the addition of the detergent cholate.45 Little is known about how the amphipathic proteins and lipids in lipoproteins and nanodiscs assemble and form discoidal particles. Molecular dynamics (MD) simulations, in particular, can offer a view of the assembly process. Unfortunately, this process is too long for conventional atomic resolution molecular dynamics simulations that presently cover only a 100 ns to 1 µs time scale. However, so-called coarse-grained (CG) molecular dynamics provides a computational method that can be utilized in studying the assembly process beyond 1 µs, but at the cost of atomic level detail. A variety of CG models have been developed for systems ranging from proteins46,47 to polymers48-52 to lipids.53-68 In particular, CG lipid models have been developed and effectively utilized in describing lipid dynamics and assembly.53-68 Lipid aggregation relies on hydrophobic and hydrophilic properties of lipids, and in this regard bears a close similarity to HDL assembly, involving amphipathic proteins and lipids. We have recently developed a CG protein-lipid model that was successfully used to study the initial phase (several microseconds) of lipoprotein aggregation24,25 and disassembly of nanodiscs with detergent.45 Other groups have used similar CG models to study membrane proteins.69-74 Using our prior CG lipoprotein simulations as a starting point,25 we have performed in the present study four g10 µs CG simulations which elucidate the overall mechanism of discoidal HDL formation by extending simulations long enough to reach mature lipoprotein particles. In order to verify that the simulated structures are indeed viable, we carried out smallangle X-ray scattering (SAXS) experiments, which provide lowresolution structural information,75 and compared the results with the simulated structures. The greatly increased sampling of CG simulations along with comparisons with experimental data reveals in startling detail how amphipathic proteins gather lipids to form discoidal particles. Methods A detailed description of the CG protein-lipid model employed in this study, which extends Marrink’s CG lipidwater model,61 has already been provided.24,25 In our CG model, an all-atom structure is mapped onto a CG structure, in which groups of atoms are represented by CG “beads”. In fact, each amino acid of a protein is represented by two CG beads, one for the backbone and one for the side chain (glycine is represented by a single backbone CG bead). Following Marrink,61 a DPPC lipid is represented by twelve CG particles: one for the choline group, one for the phosphate group, two for each of the glycerol groups, and eight to represent the two hydrocarbon tails. Four water molecules are represented by a single
J. Phys. Chem. B, Vol. 111, No. 38, 2007 11097 CG bead; an ion together with its first hydration shell (six water molecules) is also represented by one CG bead. An average correspondence of four heavy (non-hydrogen) atoms per CG bead is maintained in the overall description. For each protein CG bead, a cumulative mass and charge of the atomic groups that it represents is used, whereas, for lipids, water, and ions, a uniform mass of 72 amu is assumed.61 The CG beads carry out desired mechanical motion with force resulting from interaction potentials. Harmonic potentials are used to maintain bonds and angles between bonded CG beads. A dihedral potential is used to maintain the secondary structure of the proteins;25 this term acts upon each quadruple, l, of consecutive backbone CG beads and has the form
Vdihedral ) Φl[1 + cos(nχl - δl)] l
(1)
where Φl is a force constant, the integer n defines the multiplicity of the periodic potential, δl is a phase shift, and the variable χl is the dihedral angle formed by the four CG beads. Parameters for this potential were derived from all-atom simulations of R-helical segments of apo A-I25 by means of Boltzmann inversion.50,76-79 Nonbonded interactions are described by Lennard-Jones and Coulomb potentials. In general, parameters of the interaction potentials are tuned to reproduce certain properties known from experiments or all-atom simulations.61 The Lennard-Jones interactions are all described by the same radius (5.3 Å in the format of the CHARMM80 force field), while the energy values for each pair of the CG bead types are assigned to one of five interaction levels, from 0.43 to 1.195 kcal/mol.24,61 The bead types are chosen on the basis of the properties of the atomic group represented by the bead: hydrophobic or polar, donor or acceptor of hydrogen bonds, charged or neutral. Polar-polar pairs are then assigned strong interaction energies, while, for example, hydrophobic-hydrophobic pairs have weaker interactions. This description allows one to simulate the hydrophobic/hydrophilic partition and various phases in water-lipid-protein systems, for which many observed geometrical properties are reproduced remarkably well.24,25,45,61,70,72,74 CG MD Simulation Protocol. All CG simulations were performed using NAMD 2.5.81 Each nanodisc assembly system was minimized using 10 000 steps of conjugate gradient minimization to eliminate steric clashes between system components. CG molecular dynamics was performed in the NPT ensemble at 323 K temperature and 1 atm pressure. Temperature constancy was maintained by means of Langevin dynamics81 with a damping coefficient of 5 ps-1; constant pressure was maintained using a Langevin Nose´-Hoover piston81 with a period of 1000 fs and a decay time of 500 fs. A time step of 25 fs was used for all simulations, except for simulation SimMC (described below) which used a 20 fs time step. Nonbonded interactions were calculated using 1-2 exclusion81 with shifting starting at 9 Å and a cutoff at 12 Å.24,61 Each assembly simulation was run for 10 µs or longer (see Table 1). Analysis and visualization of the CG simulations were performed with the program VMD.82 Nanodisc Assembly Simulations. Nanodisc self-assembly is initiated upon the removal of the detergent cholate from an optimized starting mixture of detergent solubilized lipid and scaffold proteins.28 Cholate removal generally occurs over a period of hours, i.e., over a time scale that cannot be covered even using CG molecular dynamics simulations. Thus, we elected to do an instantaneous cholate removal by simply not including cholate in our initial starting systems.
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Figure 2. Comparison of SAXS curves calculated from an all-atom double-belt nanodisc (in black) using the program CRYSOL85 and a CG double-belt nanodisc (shown in Figure 1) using chosen d values (see text) of 0.15, 0.21, 0.28, 0.2, -0.04, and -0.21 e/Å3 for protein (both backbone and side chain), lipid choline, lipid phosphate, lipid glycerol ester, lipid tail, and lipid tail terminus beads, respectively.
TABLE 1: Description of CG Nanodisc Assembly Simulations simulation name
no. of proteins
initial protein orientation
initial distribution of lipids
total simulation time
SimRN SimRN2 SimMC SimHP
2a 2a 2a 2b
half-circles half-circles half-circles hairpins
random random pseudo-micelle random
10.0 µs 10.0 µs 11.6 µs 12.1 µs
a MSP1 ∆(1-22) scaffold proteins (i.e., apo A-I ∆(1-65). b MSP1 scaffold proteins (i.e., apo A-I ∆(1-43)).
The self-assembly of nanodiscs was previously simulated using two different starting conditions.25 In the present study we extend the prior simulations, called SimRN and SimMC (see Table 1), from 4 and 1.5 µs to a total simulation time of 10 and 11.6 µs, respectively. In addition to these two simulations, we carried out two new assembly simulations, each starting from a different configuration. Details about each of these systems are provided below. In the two previously simulated systems, the assembly simulation referred to as SimRN started from two scaffold proteins formed into half-circles, separated by 40 Å with 160 DPPC lipids randomly scattered throughout the periodic cell (Figure 3a); simulation SimMC had the lipids arranged in a pseudo-micelle (Figure 4a).25 Each system was solvated with CG water.24 CG sodium ions were added to neutralize the net electrostatic charge. The overall system size for SimRN was 180 Å × 181 Å × 137 Å with 36 018 CG beads, and that for SimMC was 166 Å × 193 Å × 134 Å with 35 011 CG beads. The SimMC system was resolvated at 1596 ns into a water box of dimensions 142 Å × 261 Å × 107 Å with 33 653 CG beads; the resolvation was needed, since in the course of the assembly the proteins formed a long “handle” that required an extended cell. In the first of the two new nanodisc assembly simulations, SimRN2, the system was set up as in SimRN but with the lipids rerandomized. Two scaffold proteins were formed initially as half-circles, separated by 40 Å (as in SimRN), but the 160 DPPC lipids rescattered (Figure 5a). After solvation with water and neutralization with ions, this resulted in an overall system size of 36 865 CG beads. In the second new nanodisc assembly simulation, SimHP, a different initial configuration for the proteins was assumed. Since simulations SimRN, SimRN2, and SimMC used an initial
protein conformation which closely resembled a double-belt model of two long circular helical proteins, we chose for SimHP an initial helical-hairpin conformation, with the hairpin turn introduced at K133.9 Since the proposed hairpin model for discoidal lipoproteins9 uses apo A-I ∆(1-43) proteins (i.e., MSP1 scaffold proteins), we chose to do the hairpin assembly simulation with the apo A-I ∆(1-43) proteins as opposed to the apo A-I ∆(1-65) proteins (i.e., MSP1 ∆(1-22) scaffold proteins) used in simulations SimRN, SimRN2, and SimMC. 160 DPPC lipids were scattered around the proteins (Figure 6a) and solvated with water and neutralized with CG sodium ions, resulting in a system size of 37 096 CG beads. Preparation of Disc Samples. The general experimental procedure for the self-assembly of nanodiscs has been published.28,29 Briefly, a solution of purified MSP1 ∆(1-11) membrane scaffold protein (i.e., apo A-I with the first 54 residues truncated)23,29 at 0.15-0.3 mM concentration was combined with cholate and phospholipid [either dipalmitoylphosphatidylcholine (DPPC) or dimyristoylphosphatidylcholine (DMPC)]. After incubation at 38 °C (DPPC) or at room temperature (DMPC), the self-assembly process is initiated by dialysis against 1000-fold excess buffer (20 mM Tris, pH 7.4, 100 mM NaCl, 1 mM NaN3) for 36 h with fresh buffer exchange every 12 h at the same temperature using 10 000 MW cutoff membranes. After this process, the main fractions of selfassembled nanodiscs were isolated by size exclusion chromatography as described earlier.29 SAXS Measurements and Analysis. SAXS was measured at the DND-CAT Sector 5 at the Advanced Photon Source (Argonne National Laboratory). The nanodisc solutions were sealed into glass capillaries with 1.5 mm diameters (Charles Supper Co., Natick, MA) and placed into a Peltier temperature controlled aluminum sample holder. Vacuum chambers with Mylar windows were used along the beam path before and after the sample holder to minimize scattering by air. Silver behenate with 58.38 Å spacing83 was employed for calibration, and reference buffer solvents were used for background correction. Measurements were performed at a 2043.95 mm sample to 2D detector distance and a nominal photon energy of 15 keV (wavelength 0.826 Å). MSP1 ∆(1-11) DPPC nanodiscs were measured at 46 °C and MSP1 ∆(1-11) DMPC nanodiscs at 32 °C with 100 s of exposure per measurement. The raw data were processed using the program FIT2D84 to give the scattering curves in the form log(I/I0) versus Q ) 4π sin(θ)/λ, where 2θ is the scattering angle and λ is the wavelength. SAXS patterns were also calculated for the final structures (averaged over 200 ns) stemming from the CG assembly simulations SimRN, SimRN2, SimMC, and SimHP described above, as well as for a previously simulated preformed CG MSP1 ∆(1-11) nanodisc25 (Figure 1) using in-house programs. These programs implement the spheres method75 for calculating the scattering of a particle defined by a set of spheres (or in this case CG beads) with radius a. The total scattering intensity, I(Q), of a particle composed of n spheres is
[
I(Q) ) nφ2(Qa) 1 +
2 n-1
n
∑ ∑ (didj) n i)1 j)i+1
]
sin(Qrij) Qrij
(2)
where rij is the distance between the ith and jth sphere and di and dj are the relative electron densities of the ith and jth sphere. The scattering intensity from a uniform sphere, φ2, is
φ2(Qa) ) 9
(
)
sin(Qa) - Qa cos(Qa) (Qa)
3
2
(3)
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Figure 3. Nanodisc assembly simulation SimRN in which the two scaffold proteins are initially formed as half-circles (shown in green and blue) with the lipids (shown in dark and light brown) randomly scattered (a). Snapshots over the course of the 10 µs simulation are shown (b-e) and reveal the formation of a discoidal lipoprotein particle in a double-belt conformation. See also the Supporting Information for a movie of the entire SimRN assembly simulation. The various snapshots are scaled to minimize white space; a scale bar for the final snapshot is shown.
Figure 4. Nanodisc assembly simulation SimMC in which the two scaffold proteins are initially formed as half-circles (shown in green and blue) around a pseudo-lipid micelle (shown in dark and light brown) (a). Snapshots over the course of the 11.6 µs simulation are shown (b-e) and reveal the formation of a discoidal lipid bilayer with portions of the two scaffold proteins oriented along the perimeter perpendicular to the lipid acyl chains. A large portion of each of the two protein strands has not made contact with the lipid disc, although over the course of the simulation this protein handle is being slowly drawn into contact with the lipids. The various snapshots are scaled to minimize white space; a scale bar for the final snapshot is shown.
For calculation of SAXS curves from the CG simulations, the CG beads were divided into six groups: protein (both backbone and side chains), lipid choline, lipid phosphate, lipid glycerol ester, lipid tail, and lipid tail terminus. The relative electron densities, d (i.e., the difference between the electron density of water, 0.334 e/Å3, and the average electron density of the CG beads), were chosen as 0.15, 0.21, 0.28, 0.2, -0.04, and -0.21 e/Å3 for protein (both backbone and side chain), lipid choline, lipid phosphate, lipid glycerol ester, lipid tail, and lipid tail terminus beads, respectively. The d values assumed yielded close agreement with the SAXS curves calculated from an ideal all-atom double-belt model nanodisc25 using the program CRYSOL85 which does not include any adjustable electron density parameters (see Figure 2). Additional analysis of SAXS curves was performed using the program GNOM86 to obtain the distance distribution function, p(R), for monodisperse systems.
Results and Discussion The CG nanodisc assembly dynamics as seen in simulations SimRN, SimRN2, SimMC, and SimHP are depicted through a series of snapshots in Figures 3-6. The mechanism of nanodisc self-assembly as reflected in these snapshots can be characterized quantitatively through three properties: solvent-exposed hydrophobic surface area (Figure 7), total interaction energy (conformation and nonbonded) of the two scaffold proteins (Figure 8), and total potential energy of the nanodisc (excluding solvent) (Figure 9). In general, the snapshots shown in Figures 3-6 reveal that, during the initial assembly phase, nanodisc formation is driven mainly by the hydrophobic effect. This is evident from the quick formation of small lipid micelles, followed by fusion of the small micelles into larger particles. Since many of the lipid micelles are aggregated to the scaffold proteins, fusion of the lipids draws the two protein strands together and induces the formation of a single lipoprotein particle. The hydrophobic-effect-driven self-
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Figure 5. Nanodisc assembly simulation SimRN2 in which the two scaffold proteins are initially formed as half-circles (shown in green and blue) with the lipids (shown in dark and light brown) randomly scattered (a) in a different orientation than in SimRN (cf. Figure 3). Snapshots over the course of the 10 µs simulation are shown (b-e) and reveal the formation of a discoidal lipoprotein particle with portions of the two scaffold proteins oriented along the top of the discs interacting at the interface of the lipid head and tail groups. The various snapshots are scaled to minimize white space; a scale bar for the final snapshot is shown.
Figure 6. Nanodisc assembly simulation SimHP in which the two scaffold proteins are initially formed with a hairpin turn at K133 (shown in green and blue) and with the lipids (shown in dark and light brown) randomly scattered (a). Snapshots over the course of the 12.1 µs simulation are shown (b-e) and reveal the formation of a discoidal lipoprotein particle with the scaffold proteins oriented along the perimeter of a lipid bilayer patch. However, many lipids are trapped in the hairpin turn region of the scaffold proteins. The various snapshots are scaled to minimize white space; a scale bar for the final snapshot is shown.
aggregation occurs within 3 µs and is characterized by a sharp decrease in solvent-exposed hydrophobic surface area for all simulated systems, as shown in Figure 7. In the case of simulations SimRN and SimHP, values for the solvent-exposed hydrophobic surface area reach the average values of ideal discoidal double-belt nanodiscs. The initial phase in nanodisc self-assembly is followed by a slower protein tertiary structure rearrangement, which is characterized through formation of favorable protein-protein interactions. The protein-protein interaction energy is plotted in Figure 8 for all four simulated systems; one can discern a very gradual decrease in this energy which appears to drive protein tertiary rearrangement, but the decrease is hardly discernible over the 12 µs of simulations and in none of the simulations do
the values reach those of ideal double-belt nanodiscs. The overall total potential energy of the nanodiscs in the CG assembly simulations, the time evolution of which is shown in Figure 9, shows a rather good convergence to the values corresponding to ideal double-belt nanodiscs, but this can be due to the fact that the total energy is dominated by the solvent-exposed hydrophobic surface area, while protein-protein interaction energies, although important for formation of protein tertiary structure, contribute little to the total energy. Simulation SimRN, presented in Figure 3 and in the Supporting Information, resulted in the formation of a nearly perfect double-belt model lipoprotein particle. Lipid aggregation and formation of a single lipoprotein particle within the first 900 ns of simulation lead to the reduction of solvent-exposed
Feature Article
Figure 7. Solvent-exposed hydrophobic surface area over the course of the CG nanodisc assembly simulations, SimRN (shown in black), SimRN2 (in red), SimMC (in blue), and SimHP (in green). The gray bar shows the average (and standard deviation) of previously preformed CG double-belt model nanodisc simulations25 and forms a baseline value for comparison.
Figure 8. Total interaction energy (bonded and nonbonded) between all residues of the two scaffold proteins. All energies are normalized by the number of CG beads in the two protein strands. The protein interaction energy is plotted over the course of the CG nanodisc assembly simulations, SimRN (shown in black), SimRN2 (in red), SimMC (in blue), and SimHP (in green). The gray bar shows the average surface area (and standard deviation) of preformed CG doublebelt nanodiscs studied in prior simulations25 and forms a baseline value for comparison.
hydrophobic surface area (Figure 7) to levels matching those of double-belt nanodiscs (∼35 nm2). A much more gradual decrease in protein-protein interaction energy occurred throughout the entire 10 µs simulation (Figure 8). After initially aggregating into a single particle, the two scaffold protein strands were oriented with a gradual bend (Figure 3c) so that one portion of the scaffold proteins was oriented along the perimeter of the lipid disc perpendicular to the lipid acyl chains and another portion was oriented on top of the lipid disc interacting at the interface of the lipid head and tail groups. The regions of the proteins which were lying on top of the lipid disc were observed to slowly drift around, and between 5.4 and 7.2 µs, both strands of the scaffold proteins transitioned from the gradual hairpinbend structure to a straight double-belt-like structure in which the entire protein length was oriented along the perimeter of
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Figure 9. Total potential energy of the nanodiscs (excluding solvent) plotted over the course of the CG nanodisc assembly simulations, SimRN (shown in black), SimRN2 (in red), SimMC (in blue), and SimHP (in green). All energies are normalized by the number of CG beads present in the system in question. The gray bar shows the average (and standard deviation) of previously preformed CG double-belt model nanodisc simulations25 and forms a baseline value for comparison.
the lipid disc (Figure 3c-e). At the end of the 10 µs simulation, there were still nine lipids caught between the two protein strands, which is likely the reason why the protein-protein interaction energy is still 0.2 kcal/mol per CG protein bead higher than in the ideal double-belt model nanodiscs (Figure 8). In simulation SimRN2, presented in Figure 5, and SimHP, presented in Figure 6, the final scaffold protein tertiary structure, in which the proteins form bends and turns (with lipids inserted in the interface) along the edges and on top of the lipid disc, resembles an intermediate stage of simulation SimRN (Figure 3c). It appears likely that, given enough time, both of the simulated particles would form a double-belt nanodisc, especially since the protein-protein interaction energy for both SimRN2 and SimHP (Figure 8), and the solvent-exposed hydrophobic surface area for SimRN2 (Figure 7), has not yet reached levels of preformed nanodiscs. The movement of the scaffold proteins along the top surface of the lipid discs, at the interface of the lipid head and tail groups, in simulations SimRN, SimRN2, and SimHP (see Figures 3, 5, and 6) is particularly interesting, as such an interaction is suggested to occur in spherical HDL particles.87 In such particles, a hydrophobic core is formed from cholesterol esters surrounded by a lipid monolayer, leading to a spherical particle. It has been suggested that apo A-I proteins orient themselves along the surface of this monolayer with the hydrophobic protein face interacting with the lipid acyl tails while the hydrophilic faces of the protein interact with the lipid head groups.87 The free movement of the amphipathic scaffold proteins at the interface of the lipid head and tail groups in the CG assembly simulations presented here suggests that such an interaction is indeed possible and occurs not only in spherical HDL particles, but also during the formation of the discoidal HDL particles. In simulation SimMC, the two scaffold protein strands do not achieve contact with the lipid disc along their entire length (Figure 4), even by the end of the 12 µs simulation. Instead, the portions of the two proteins, which remained unassociated with lipid, attached to each other, forming double-stranded protein-protein interactions. However, protein that is associated with lipid forms structures which are consistent with the double-
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Figure 10. Changes in SAXS curves computed over the time course of simulation SimRN. SAXS curves at various time points (0 ns in thin black, 150 ns in blue, 850 ns in purple, 1 µs in red, 4 µs in green, and 10 µs in thick black) show that SAXS can be used to track the transformation from a completely disordered system to the formation of a discoidal lipid bilayer surrounded by scaffold proteins.
belt model. The need for this system to continue to minimize its solvent-exposed hydrophobic surface area (Figure 7) and to optimize protein-protein interactions should continue to draw in the lipid unassociated protein, eventually forming a pure double-belt nanodisc. In fact, during the final 9 µs of SimMC, 7 residues were drawn into association with the lipid disc, with a remaining ∼55 residues of each protein still not in contact with lipid. SAXS permits the structural characterization of macromolecules in solution and has been used to study phase transitions and structural properties of nanodiscs.29,36,44 Although a lowresolution experimental method, SAXS is particularly sensitive to changes in the packing of nanodisc lipids, and this feature is exploited in order to obtain structural information on nanodiscs. As seen in Figure 10, the SAXS curves change considerably when going from a disordered initial system to an ordered nanodisc, revealing the sensitivity of SAXS to nanodisc structure. Experimentally measured SAXS curves of nanodiscs prepared with DPPC and DMPC at 46 and 32 °C, respectively (temperatures are above the main phase transition temperature for the lipids in nanodiscs44), are used for comparison with theoretical SAXS curves, calculated using the spheres method described in the Methods section, of the final SimRN, SimRN2, SimMC, and SimHP structures. Both DPPC and DMPC nanodiscs are used for comparison because in the CG lipid model these two lipids are identical. Also, for comparison, a theoretical SAXS curve was calculated for a previously simulated preformed MSP1 ∆(1-11) nanodisc.25 The experimentally obtained and theoretically calculated SAXS curves along with the corresponding distance distribution functions, p(R), are shown in Figure 11. The shape of the scattering curves calculated for the simulated MSP1 ∆(1-11),25 as well as for SimRN, SimRN2, SimMC, and SimHP nanodiscs, exhibit a sharp minimum followed by a broad maximum which is characteristic of nanodiscs.29 The scattering curves from SimRN2 and SimMC are slightly different from the remaining calculated scattering curves as well as from the experimentally obtained measurements. For SimRN2, this is likely due to the presence of significant amounts of protein along the top of the nanodisc particle at the interface between the lipid head and tail groups. For SimMC, although the general shape of the scattering curve is similar, it has a much shallower minimum
Shih et al.
Figure 11. SAXS (left) along with corresponding distance distribution functions, p(R) (right). Shown are SAXS curves and p(R) for experimentally obtained (1) MSP1 ∆(1-11) DPPC and (2) MSP1 ∆(1-11) DMPC nanodiscs as well as for a simulated (3) preformed MSP1 ∆(1-11) nanodisc,25 for (4) simulation SimRN, for (5) simulation SimHP, for (6) simulation SimRN2, and for (7) simulation SimMC. The curves are vertically separated for clarity.
which is also shifted to slightly smaller angles, due to the presence of the protein handle which sticks out from the remaining particle. The distance distributions, shown in Figure 11 and calculated from the SAXS curves using the program GNOM,86 provide additional lipid structural information as well as the overall particle diameter, the latter in the range 10.2-10.3 nm, except for SimMC which has a slightly larger diameter, namely, 10.5 nm. The maximum seen in p(R) for the theoretical CG structures at 48-53 Å corresponds to the lipid bilayer thickness, which for DPPC nanodiscs above phase transition temperatures is 5253 Å and for DMPC nanodiscs is 46-48 Å.44 The lipid bilayer thickness in the CG simulations appears to be between that of a typical DPPC and DMPC bilayer, which is reasonable given that there is no difference in these two lipids in the CG model. The increased magnitude of this peak in the SimRN2 nanodiscs is likely due to the presence of protein along the top of the lipid discs providing additional density to this region. The good correlation of experimental and theoretical SAXS curves provides evidence that the assembled structures in the CG descriptions offer an accurate representation of nanodiscs in solution. Conclusions Several 10 µs CG simulations of the self-assembly of discoidal HDL particles were performed. The aggregation of disordered amphipathic protein and lipid components of a lipoprotein system was observed, and in one instance, the formation of a nearly ideal double-belt discoidal human HDL particle was achieved. The CG simulations provide a dynamic image of the initial self-assembly of amphipathic proteins and lipids. SAXS, a low-resolution structural technique, was used to experimentally validate the simulations. SAXS curves calculated from the simulations compared to experimentally measured curves revealed that the simulated structures obtained are an accurate image of discoidal lipoprotein particles. The experimental and computational results strongly support the so-called double-belt model of nanodiscs and discoidal HDL particles. The CG model employed for our self-assembly simulations provides a description of proteins, lipids, water, and ions, and may be used to study other transitions in HDL systems such as the discoidal-to-spherical transition, or other lipoprotein particles such as low-density lipoproteins.
Feature Article Acknowledgment. The authors would like to thank Drs. Timothy Bayburt and Ilia Densiov for advice on preparing nanodiscs and analysis of SAXS data as well as Steven Weigand and Denis Keane for their expertise in setting up the beamline. This work was supported by grants R01-GM067887, P41RR05969, and R01-GM33775 from the National Institutes of Health to K.S. and S.G.S. The authors acknowledge supercomputer time provided by the National Science Foundation grant MCA93S028. Portions of this work were performed at the DuPont-Northwestern-Dow Collaborative Access Team (DNDCAT) Synchrotron Research Center located at Sector 5 of the Advanced Photon Source. DND-CAT is supported by the E.I. DuPont de Nemours and Co., the Dow Chemical Company, the U.S. National Science Foundation through grant DMR-9304725, and the State of Illinois through the Department of Commerce and the Board of Higher Education Grant IBHE HECA NWU 96. Use of the Advanced Photon Source was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Contract No. W-31-109-Eng-38. Supporting Information Available: Movie of the 10 µs nanodisc assembly simulation SimRN. The formation of a double-belt discoidal lipoprotein particle from an initially disordered system of two membrane scaffold proteins (in blue and green) and 160 randomly scattered lipids (in tan). This material is available free of charge via the Internet at http:// pubs.acs.org. References and Notes (1) Segrest, J. P.; Garber, D. W.; Brouillette, C. G.; Harvey, S. C.; Anantharamaiah, G. M. AdV. Protein Chem. 1994, 45, 303-369. (2) Wang, M.; Briggs, M. R. Chem. ReV. 2004, 104, 119-137. (3) Borhani, D. W.; Rogers, D. P.; Engler, J. A.; Brouillette, C. G. Proc. Natl. Acad. Sci. U.S.A. 1997, 94, 12291-12296. (4) Ajees, A. A.; Anantharamaiah, G. M.; Mishra, V. K.; Hussain, M. M.; Murthy, H. M. K. Proc. Natl. Acad. Sci. U.S.A. 2006, 103, 21262131. (5) Koppaka, V.; Silvestro, L.; Engler, J. A.; Brouillette, C. G.; Axelsen, P. H. J. Biol. Chem. 1999, 274, 14541-14544. (6) Li, H.; Lyles, D. S.; Thomas, M. J.; Pan, W.; Sorci-Thomas, M. G. J. Biol. Chem. 2000, 275, 37048-37054. (7) Panagotopulos, S. E.; Horace, E. M.; Maiorano, J. N.; Davidson, W. S. J. Biol. Chem. 2001, 276, 42965-42970. (8) Tricerri, M. A.; Behling, Agree, A. K.; Sanchez, S. A.; Bronski, J.; Jonas, A. Biochemistry 2001, 40, 5065-5074. (9) Silva, R. A. G. D.; Hilliard, G. M.; Li, L.; Segrest, J. P.; Davidson, W. S. Biochemistry 2005, 44, 8600-8607. (10) Gorshkova, I. N.; Liu, T.; Kan, H. Y.; Chroni, A.; Zannis, V. I.; Atkinson, D. Biochemistry 2006, 45, 1242-1254. (11) Li, Y.; Kijac, A. Z.; Sligar, S. G.; Rienstra, C. M. Biophys. J. 2006, 91, 3819-3828. (12) Segrest, J. P. Chem. Phys. Lipids 1977, 18, 7-22. (13) Segrest, J. P.; Jones, M. K.; De Loof, H.; Brouillette, C. G.; Venkatachalapathi, Y. V.; Anantharamaiah, G. M. J. Lipid Res. 1992, 33, 141-166. (14) Brouillette, C. G.; Anantharamaiah, G. M. Biochim. Biophys. Acta 1995, 1256, 103-129. (15) Phillips, J. C.; Wriggers, W.; Li, Z.; Jonas, A.; Schulten, K. Biophys. J. 1997, 73, 2337-2346. (16) Sheldahl, C.; Harvey, S. C. Biophys. J. 1999, 76, 1190-1198. (17) Segrest, J. P.; Jones, M. K.; Klon, A. E.; Sheldahl, C. J.; Hellinger, M.; De Loof, H.; Harvey, S. C. J. Biol. Chem. 1999, 274, 31755-31758. (18) Segrest, J. P.; Harvey, S. C.; Zannis, V. Trends CardioVasc. Med. 2000, 10, 246-252. (19) Klon, A. E.; Jones, M. K.; Segrest, J. P.; Harvey, S. C. Biophys. J. 2000, 79, 1679-1685. (20) Klon, A. E.; Segrest, J. P.; Harvey, S. C. Biochemistry 2002, 41, 10895-10905. (21) Klon, A. E.; Segrest, J. P.; Harvey, S. C. J. Mol. Biol. 2002, 324, 703-721. (22) Li, L.; Chen, J.; Mishra, V. K.; Kurtz, J. A.; Cao, D.; Klon, A. E.; Harvey, S. C.; Anantharamaiah, G.; Segrest, J. P. J. Mol. Biol. 2004, 343, 1293-1311.
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