Molecular Simulation of Protein Encapsulation in Vesicle Formation

Article pubs.acs.org/JPCB

Molecular Simulation of Protein Encapsulation in Vesicle Formation Bram van Hoof,†,‡ Albert J. Markvoort,*,†,‡ Rutger A. van Santen,‡,§ and Peter A. J. Hilbers†,‡ †

Department of Biomedical Engineering, ‡Institute for Complex Molecular Systems, and §Department of Chemical Engineering and Chemistry, Eindhoven University of Technology, P. O. Box 513, 5600 MB Eindhoven, The Netherlands S Supporting Information *

ABSTRACT: Liposomes composed of fatty acids and phospholipids are frequently used as model systems for biological cell membranes. In many applications, the encapsulation of proteins and other biomacromolecules in these liposomes is essential. Intriguingly, the concentration of entrapped material often deviates from that in the solution where the liposomes were formed. While some reports mention reduced concentrations inside the vesicles, concentrations are also reported to be enhanced in other cases. To elucidate possible drivers for efficient encapsulation, we here investigate the encapsulation of model proteins in spontaneously forming vesicles using molecular dynamics simulations with a coarse grained force field for fatty acids and phospholipids as well as water-soluble and transmembrane proteins. We show that, in this model system, the encapsulation efficiency is dominated by the interaction of the proteins with the membrane, while no significant dependence is observed on the size of the encapsulated proteins nor on the speed of the vesicle formation, whether reduced by incorporation of stiff transmembrane proteins or by the blocking of the bilayer bulging by the presence of another membrane.

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observed.15,16 Important insight into the encapsulation has been gained by techniques able to count trapped molecules in individual vesicles.25,26 Apart from elucidating the overall encapsulation efficiencies, the possibility to count trapped molecules inside individual vesicles also allowed for the investigation of the distributions of molecular occupancy. This showed in certain cases Poisson distributions27 but in other cases also the coexistence of superfilled and empty vesicles.15,16 The underlying molecular mechanisms of this encapsulation are as yet unknown. In an experimental setup, it is impossible to follow the molecules involved at the temporal and spatial resolution required to observe these mechanisms directly. Therefore, in the literature a range of different simulation techniques has been used to investigate the formation of vesicles at the molecular level.28−39 These simulations either follow the spontaneous aggregation of initially dispersed lipids into subsequently micelles, bicelles, and finally small vesicles or focus on the curling into vesicles of larger preformed hydrated bilayers. In our previous work, this latter bilayer−vesicle transition and the resulting encapsulation of water-soluble model proteins have been studied using coarse grained molecular dynamics.40 We showed that the bilayer−vesicle transition of fatty acid bilayers follows a bilayer bulging pathway, where the center of the membrane bulges out, which is accompanied by an influx of solvent, rather than a folding of

INTRODUCTION Encapsulation of solute molecules in nano- and micrometer scale liposomes composed of fatty acids or phospholipids is of interest for applications ranging from drug delivery,1−4 biomedical imaging,5 food technology,6 (biomimetic) microreactors,7 the origin of life/protocells, and artificial living cells8−10 to the fundamental biophysical and molecular biological study of individual biomolecules or protein networks.11,12 Therefore, the encapsulation of drugs, proteins, DNA, and other biomacromolecules in liposomes has been studied extensively in recent years.13−22 Liposomes, and related lipid nanoparticles,23,24 may be formed via various procedures that all involve out-of-equilibrium steps. For many of these applications a predictable loading of the vesicles with a small number of the molecules of interest is essential, as well as a high efficiency with which those target molecules are encapsulated. Moreover, for artificial cells, it is often required to include at least a single copy of many different molecule types in order to produce viable cells, making a high encapsulation efficiency even more important as the probability of producing such viable cells decreases inversely proportional to the number of molecule types needed.15 Intriguingly, studies on encapsulation of macromolecules by liposomes have shown that the concentration of entrapped material does not always correspond to the concentration in the buffer. Often the concentration of entrapped macromolecules is below the buffer concentration; 12,18−20,25 that is, the encapsulation efficiency is smaller than one. In contrast, however, for other systems an overall enhanced encapsulation of proteins and RNA in vesicle formation has been © 2014 American Chemical Society

Received: October 27, 2013 Revised: February 12, 2014 Published: March 5, 2014 3346

dx.doi.org/10.1021/jp410612k | J. Phys. Chem. B 2014, 118, 3346−3354

The Journal of Physical Chemistry B

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the edge of the membrane encircling a certain volume of solvent. Also, it was shown that encapsulation of the model proteins could be enhanced by increasing the protein−lipid interaction, without the latter resulting in irreversible association of the proteins with lipid membranes. Here, we further investigate the bilayer−vesicle transition and drivers for efficient encapsulation of dissolved molecules. These extend the model systems used previously by varying the size of the model proteins to be encapsulated, by varying the composition of the membrane, and last, but not least, by constraining the bilayer−vesicle transition by the presence of a second membrane. From the molecular mechanism of the vesicle formation observed in our previous work we hypothesized that the slow diffusion of large proteins into the volume left by the bulging bilayers may limit the encapsulation efficiency (EE). Therefore, on the one hand we create model proteins of different sizes to test the dependence of EE on the diffusion rates of the proteins, and on the other hand, we investigate the effect of the vesicle formation mechanism on the protein encapsulation by (i) blocking the bilayer bulging by placing a periodic membrane directly below the free-floating bilayer, (ii) employing bilayers containing stiff transmembrane proteins, and (iii) using bilayers composed of model phospholipids instead of fatty acids. It results that the encapsulation efficiency can be fully accounted for by the extent of adsorption of the proteins to the membranes.

Figure 1. Illustration of the different coarse grained molecules used: fatty acids (H2T4) and phospholipids (H4T4T4), which are built of hydrophilic H particles (colored white) and hydrophobic T particles (green); transmembrane proteins (TMprot), built of the same hydrophilic H particles (shown in orange for visual distinctability only) and hydrophobic T particles (again green); water-soluble model proteins P197, P53, P17, P5, P2, which are dendritic molecules composed of 197, 53, 17, 5, and 2 hydrophilic P particles (magenta), respectively; and water particles W (blue).

Simulations of Vesicle Formation. Simulations of the bilayer−vesicle transition are performed using different systems, in a series of simulations for each system. The initial configurations are created by first equilibrating periodic bilayer membranes. After equilibration of the membrane, a circular patch with a radius of 17 nm is cut out from the bilayer and surrounded by water in a rectangular water box of 24 × 37 × 37 nm3. Four different dissolved circular membranes were created in this way: an H2T4 fatty acid membrane (bilayer I), an H4T4T4 phospholipid membrane (bilayer II), a H2T4 fatty acid membrane containing transmembrane proteins (TMprot) in a TMprot:H2T4 ratio close to 1:25 (bilayer III), and one with a TMprot:H2T4 ratio close to 1:40 (bilayer IV). The first membrane (bilayer I) is composed of 3,445 H2T4 molecules. This membrane was already employed in our previous work40 without proteins as well as with 40 P17 proteins added to the water phase. These series are referred to here as “H2T4-control” and “P17-H2T4-neutral”, respectively. The term “neutral” refers to the fact that the interaction strength, ε, between two protein particles is exactly the same as that between a protein particle and a water or a lipid headgroup particle; that is, εP−P = εP−W = εP−H. Here, this membrane is also used with 40 proteins of other sizes added to water phase. These series are denoted as the “P2-H2T4-neutral”, “P5-H2T4neutral”, “P53-H2T4-neutral”, and “P197-H2T4-neutral”, for the P2, P5, P53, and P197 model proteins, respectively. Also in the “P2-H2T4-associated” series this H2T4 membrane with 40 watersoluble P2 proteins is employed, but now the protein− headgroup interaction is increased to εP−H = 4.44 kJ mol−1, analogous to the “associated” series from our previous work with P17 proteins, and which we here refer to as “P17-H2T4associated”. The second membrane is composed of 1,825 H4T4T4 model phospholipids (bilayer II). This membrane is simulated without proteins in the “H4T4T4-control” series. In the “P17-H4T4T4neutral” series, the water phase surrounding these H4T4T4 membranes contains 40 randomly distributed P17 proteins. The term neutral refers again to the fact that the ε between two

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METHODS Coarse Grained Model. The coarse grained model employed here is an extension of the model used previously to study the bilayer−vesicle transition,32,40 fusion of membranes,41 and membrane proteins,42,43 as well as vesicle deformation, budding, and fission.44−46 The model consists of four particle types: W particles that represent four water molecules, T particles that represent four CHx groups in the apolar lipid tails, H particles that represent the lipid headgroups, and P particles that form water-soluble proteins. Here, we employ as membrane components not only the H2T4 fatty acids40,44 but also the model phospholipid H4T4T4,32 a model transmembrane protein (TMprot) as previously used by Smeijers et al.,41 and the dendritic water-soluble model protein from ref 40, which we here refer to as P17. New is a range of other generations of the dendritic water-soluble protein P17 composed of two (P2), five (P5), 53 (P53), and 197 (P197) of the same P beads as used for the P17, respectively. An overview of all molecules used is shown in Figure 1. Molecular Dynamics Simulations. The molecular dynamics simulations are performed using our molecular dynamics code PumMa,32 with most simulations run on 12− 32 processors on a Rocks Cluster and other simulations run on 32 processors of the supercomputer Huygens (at SARA), which is an IBM pSeries 575 symmetric multiprocessing system. The simulations are performed in the same manner as described in our previous work.40 The employed time step is 25 fs, whereas temperature and pressure control (at 307 K and 1.0 atm) are performed by a Berendsen thermostat and barostat, respectively. The nonbonded interactions are cut off at 1.2 nm. The used force field is an extended version of that used previously,40 where the only extension entails an additional angle interaction for the angle between the three outermost particles of each branch of the P197 protein, with θ0 = 180° and kangle = 31.46 kJ mol−1, to maintain the spherical shape of the proteins. 3347



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Table 1. Overview of the Different Vesicle Formation Simulation Series Performed and Their Averaged Results seriesa

Nsim

H2T4-controlc P2-H2T4-neutral P5-H2T4-neutral P17-H2T4-neutralc P53-H2T4-neutral P197-H2T4-neutral

12 24 24 24 24 24

H4T4T4-control P17-H4T4T4-neutral

12 24

P17-H2T4-neutralplusc P2-H2T4-associated P17-H2T4-associatedc

12 24 24

TM1:25-control P17-TM1:25-neutral P17-TM1:25-associated P17-TM1:40-associated

12 24 24 24

P17-blocked-neutral

20

bilayerb

εP−H (kJ mol−1)

ω0

Fatty Acid Membranes with Varying Protein Size I I 3.70 1.0 I 3.70 1.0 I 3.70 1.0 I 3.70 1.0 I 3.70 1.0 Phospholipid Membranes II II 3.70 1.0 Fatty Acid Membranes with Enhanced Protein−Membrane Interaction I 3.70 1.5 I 4.44 1.5 I 4.44 1.5 Fatty Acid Membranes with Transmembrane Proteins III III 3.70 1.0 III 4.44 1.5 IV 4.44 1.5 Two Fatty Acid Membranes I 3.70 1.0

Nencapsulated

1.6 1.6 1.6 1.6 1.8

± ± ± ± ±

1.0 1.0 1.2 1.2 1.0

tclose (ns) 30.9 29.5 29.9 30.9 30.7 34.5

± ± ± ± ± ±

3.0 2.8 3.2 2.9 2.6 2.5

1.1 ± 0.7

19.1 ± 1.4 19.8 ± 1.5

1.7 ± 1.5 3.0 ± 1.4 5.5 ± 2.4

28.8 ± 3.3 31.1 ± 3.4 30.4 ± 2.7

1.0 ± 0.8 7.9 ± 2.4 6.7 ± 1.9

60.5 56.6 56.3 41.2

1.0 ± 0.9

67.8 ± 15.2

± ± ± ±

13.2 6.5 4.6 4.1

a

For each series the number of simulations (Nsim), the composition of the bilayer, the protein−headgroup interaction (εP−H), the relative membrane density near the membrane in the initial configuration (ω0), the number of proteins encapsulated in the vesicle after membrane closure (Nencapsulated), and the closure time (tclose) are given. bBilayer composition as described in Methods. cIncluded from ref 40 for comparison.

different randomly assigned initial velocities and randomly inserted water-soluble proteins in the water phase. In each simulation, the solvent and the water-soluble proteins, when present, are allowed to equilibrate for 2.5 ns while the membrane is kept fixed. Subsequently, the membrane is released and an unconstrained molecular dynamics simulation is performed. EE is determined as the protein concentration inside the vesicle that is formed divided by the overall concentration of proteins ρ0. Protein Adsorption to the Membrane. To measure the membrane adhesion of the water-soluble proteins as a function of protein size, membrane composition, and P−H interaction parameter εP−H, we performed simulations of a solvated periodic bilayer of 21.8 × 18.8 nm2 in a box of 30.0 nm high, with 24 water-soluble proteins in the water phase. For both the neutral (3.70 kJ mol−1) and associated (4.44 kJ mol−1) P−H interaction, we measured the adsorption of P2, P5, P17, P53, and P197 to an H2T4 bilayer, as well as the adsorption of P17 to H2T4 bilayers with transmembrane proteins at a 1:25 and 1:40 TMprot:H2T4 ratio (named “P17-TM1:25” and “P17-TM1:40”, respectively), and also the adsorption of P17 to a H4T4T4 bilayer (“P17-H4T4T4”). For P2, P17, and P197, the adsorption is measured also for three intermediate P−H interactions, “N-I” (3.88 kJ mol−1), “intermediate” (4.07 kJ mol−1), and “I-A” (4.25 kJ mol−1). A frame is written to the trajectory files every 25 ps, and the total duration of the simulations is 250 ns, including 75 ns of equilibration that is not used in the calculations. Each frame is used in the calculation of the adsorption of proteins to the membrane, which is performed by dividing the solvent surrounding the membrane into equidistant segments of 0.05 nm width, and measuring the protein concentration ρx in each segment. This concentration is calculated by dividing the amount of protein particles by the amount of water particles in this segment. ρx is normalized by the overall concentration of

protein particles is exactly the same as that between a protein particle and a water or a lipid headgroup particle; that is, εP−P = εP−W = εP−H. In the third membrane (bilayer III) 112 transmembrane proteins (TMprot) are embedded in a bilayer consisting of 2,873 H2T4 molecules. This TMprot:H2T4 ratio (close to 1:25) is selected to ensure a significant slow-down of the vesicle formation. In the “TM1:25-control” series, this membrane is simulated without proteins. In the “P17-TM1:25-neutral” and “P17-TM1:25-associated” series, the same membrane is used, but again 40 water-soluble P17 proteins are added to the water phase. The difference between the two series is that for the neutral one the P−H interaction strength is again εP−H = 3.70 kJ mol−1, while for the associated one the protein−headgroup interaction is increased to εP−H = 4.44 kJ mol−1. In the fourth membrane (bilayer IV) 70 transmembrane proteins (TMprot) are embedded in a bilayer consisting of 3,031 H 2 T 4 molecules. This membrane with a lower TMprot:H2T4 ratio (near 1:40) was used in the “P17-TM1:40associated” series in combination with 40 water-soluble P17 proteins in the water phase with a P−H interaction strength of εP−H = 4.44 kJ mol−1. For the “P17-blocked-neutral” series, the initial configuration of the “P17-H2T4-neutral” series (bilayer I) is extended with a periodic H 2 T4 membrane separated from the circular membrane patch by a 1.5 nm thick water layer. The size of the simulation box in this series is 27 × 39 × 39 nm3. The periodic membrane consists of 5705 H2T4 molecules. Thirtytwo of those were randomly chosen to be fixed in place in order to keep the periodic membrane at its original position during the simulation. In this P17-blocked-neutral series again 40 watersoluble P17 proteins are present in the water phase, with the P− H interaction strength being εP−H = 3.70 kJ mol−1. In order to obtain proper statistics, each system is simulated 12−24 times, where each simulation is performed using 3348



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Figure 2. Snapshots of representative simulations from different simulation series: (a) P2-H2T4-neutral, (b) P17-H4T4T4-neutral, (c) P17-TM1:25associated, and (d) P17-blocked-neutral. For each, the initial configuration is shown on the left and subsequent configurations at different simulation times (noted in the upper left corner) are shown from left to right. The lipid and protein molecules are shown in a spheres representation, while for visibility the water is not shown explicitly but instead as a continuous blue opaque solvent. Coloring is the same as in Figure 1 (with the water-soluble proteins colored magenta, the fatty acids and phospholipids in the bilayers forming vesicles shown in green and white, and the transmembrane proteins shown in green and orange) except for the fatty acids in the periodic membrane in the P17-blocked-neutral simulation which are shown in black and gray. Both stiffening of the membrane by the incorporation of transmembrane proteins (c) and the hindrance of bilayer bulging by an additional membrane (d) significantly increase the vesicle formation time as compared to pure free-floating H2T4 (a) and H4T4T4 (b) membranes. The numbers of proteins encapsulated in the vesicles formed, however, is not influenced significantly by this formation speed but rather by the membrane−protein adhesion (vide supra).

proteins, ρ0, resulting in a relative protein density, ξ. The calculation of ξ for each equidistant segment results in graphs for each of the simulations. Furthermore, we calculated the average protein density within 1.2 nm of the membrane, ρm, which results in a single relative adsorbed protein concentration, ω, for each simulation, defined as ω = ρm/ρ0. The threshold of 1.2 nm was chosen as (i) the largest deviations from the bulk density are observed within this distance from the bilayer (as can be seen from the protein density profiles in the Supporting Information) and (ii) this distance coincides with the range over which the nonbonded interactions in our model span.

diffusion rates of the proteins are inversely dependent on the square root of their mass (see Figure S1 in the Supporting Information), and thus differ over 1 order of magnitude. Comparison in Table 1 of the protein encapsulation in the different simulation series with a neutral lipid headgroup− protein interaction, i.e., the P2-H2T4-neutral, P5-H2T4-neutral, P17-H2T4-neutral, P53-H2T4-neutral, and P197-H2T4-neutral series, reveals that the amount of encapsulated proteins is independent of the protein size. Moreover, in all cases the concentration of proteins inside the vesicles is lower than the concentration outside of it; that is, the 1.6 proteins that are encapsulated on average correspond to an EE value of approximately 0.7. Comparison to the reference simulation series without proteins (H2T4-control) also shows that the vesicle formation process, and its duration, has not notably changed. Only for the simulations with the largest proteins (P197-H2T4-neutral series) a slightly slower vesicle formation than in the control simulations without proteins (H2T4control) is observed. Visual inspection of the trajectories reveals that this is caused, in a number of simulations, by a single P197 protein near the edge of the closing membrane, being larger than the membrane width, temporarily hindering the closure of the vesicle. To investigate whether the observed bilayer bulging pathway is specific for the H2T4 lipid model and whether the membrane composition influences the encapsulation, also simulations of the bilayer−vesicle transition of phospholipid (H4T4T4) membranes have been performed. Snapshots of one such simulation are shown in Figure 2b. In Table 1 it can be seen that the average closure time for the H4T4T4 vesicles, i.e., both without proteins (the H4T4T4-control series) as well as with 40 P17 proteins (the P17-H4T4T4-neutral series), is significantly shorter than that of the H2T4 vesicles. However, apart from the

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RESULTS Encapsulation during Bilayer−Vesicle Transition. The bilayer−vesicle transition and the resulting encapsulation of dissolved (macro)molecules is studied in a series of molecular dynamics simulations where we varied (i) the size of the molecules to be encapsulated, (ii) the interaction between these molecules and the membrane, (iii) the composition of the membrane, and (iv) constraints on the bilayer−vesicle transition. An overview of the results from these simulations is provided in Table 1. In this table the simulations are divided into five categories. These are described one by one in the following five paragraphs. Snapshots of four representative simulations of distinct systems are shown in Figure 2. To test the effect of the diffusion rate of dissolved molecules on their encapsulation efficiency in forming vesicles, we introduced water-soluble model proteins of five different sizes, ranging from 2 to 197 coarse grained P beads per protein molecule. Four snapshots of a simulation with the smallest proteins are shown in Figure 2a. As expected, the 3349



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to the large differences between individual simulations the difference is not significant. Effect of Protein−Membrane Interaction. Given the observations that increased protein−membrane interaction results in enhanced encapsulation and that this encapsulation enhancement differs considerably with protein size and membrane composition, it is interesting to investigate the effect of the protein−membrane interaction on different proteins and membranes more closely. Therefore the adhesion of the water-soluble model proteins to flat periodic membranes has been investigated, varying the protein−membrane interaction, for the H4T4T4 membrane as well as for the H2T4 membranes with and without transmembrane proteins. As a measure of this adhesion, the average relative protein density within 1.2 nm of the membrane, ω, has been calculated, as described in Methods. In Figure 3a, ω is shown as a function of

speed of the vesicle formation, the vesicle formation occurs in the same manner as previously observed for the H2T4 membranes (see Figure S2 in the Supporting Information). Table 1 also shows that for these phospholipid membranes the number of proteins encapsulated during vesicle formation is even slightly lower than for the H2T4 membranes. To test whether the distribution of the proteins in the initial configurations of our simulations has an influence on the reduced interior protein concentration, also a series of simulations has been performed where the concentration of protein near the H2T4 bilayer in the initial configurations was increased by 50%, the P17-H2T4-neutralplus series. No significant difference was noted, neither on the final number of proteins encapsulated nor on the vesicle formation process and speed. The influence of the concentrations near the bilayer was further checked using simulations with an enhanced lipid headgroup−protein interaction for the system with P2 proteins (the P2-H2T4-associated series) and with P17 proteins (P17H2T4-associated series). These series still showed the same vesicle formation mechanism and closure time but resulted on average in a significantly larger amount of proteins encapsulated as compared to the neutral series (see again Table 1). In order to test the influence of the speed of the vesicle formation process on the encapsulation, also series of simulations of the bilayer−vesicle transition have been performed with H2T4 membranes containing model transmembrane proteins. Snapshots of one such simulation are shown in Figure 2c. Table 1 shows that the transmembrane proteins decrease the speed of vesicle formation by a factor of 2 for a 1:25 ratio of transmembrane proteins to lipids (TM1:25control, P17-TM1:25-neutral, and P17-TM1:25-associated) and by a factor of 4/3 for a 1:40 ratio (P17-TM1:40-associated). Moreover, the table shows that while for the neutral lipid headgroup−protein interaction the transmembrane proteins result in a decreased encapsulation efficiency, for the enhanced lipid headgroup−protein interaction it oppositely results in an enhanced encapsulation as compared to the pure H2T4 membranes discussed before. For instance, the amount of P17 proteins encapsulated in the P17-TM1:25-neutral series of 1.0 is lower than the 1.6 in the P17-H2T4-neutral series, whereas the amount of P17 proteins encapsulated in the P17-TM1:25associated series of 7.9 is higher than the 5.5 in the P17H2T4-associated series. However, the relatively high standard deviations of these values make interpretation of these results hard. Finally, to study the influence of diffusion and the vesicle formation process further, also a series of simulations was performed where the bilayer bulging was hindered by the presence of another, periodic, bilayer. A representative simulation of this series is shown in Figure 2d. In all simulations the edge of the bilayer closed away from the periodic bilayer, resulting in a slow-down of the vesicle formation process by at least a factor of 2 as compared to the vesicle formation from unhindered membranes. Because the periodic bilayer prevents the center of the bilayer from bulging out, the vesicle now closes by encircling the solvent rather than by forming a cup that is filled with solvent. If limited diffusion of the larger molecules would account for the reduced protein concentrations inside the vesicles, both the encircling and the slow-down of the bilayer closure would be expected to enhance the encapsulation of water-soluble proteins. However, instead of a higher concentration compared to the bulging case, we observe an even further decreased concentration, although due

Figure 3. (a) Average protein density within 1.2 nm of a periodic membrane (ω) as a function of the P−H interaction strength (εP−H). The density is shown for the P2, P5, P17, P53, and P197 proteins with a H2T4 membrane (named P2-H2T4, P5-H2T4, P17-H2T4, P53-H2T4, and P197-H2T4, respectively), for P17 with H2T4 membranes containing transmembrane proteins at a 1:40 and a 1:25 concentration (P17TM1:40 and P17-TM1:25), and for P17 with the H4T4T4 membrane (P17H4T4T4). (b) Logarithm of the protein density near the H2T4 membrane (log(ω)) for each of the proteins for the neutral and associated protein−membrane interactions.

the protein−membrane interaction strength, which is defined by εP−H. Interestingly, for the lower interaction strengths ω decreases with protein size, whereas for the highest interaction strength the trend is exactly the other way around. Moreover, for the lowest interaction ω is reduced by the presence of the transmembrane proteins, whereas for the highest interaction it is increased. In Figure 3b, the logarithm of ω for the neutral and associated interactions are shown for each of the different protein sizes interacting with a H2T4 membrane. Not only does it again show the respective increasing and decreasing trends with protein size, it also exhibits that while for the largest proteins the enhanced protein−membrane interaction increases the protein density strongly, the difference between the membrane association with the neutral and the associated 3350



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formation, but that it can be solely attributed to the extent of adsorption of the proteins to the membranes. This confirms the earlier experimental observation of the importance of the membrane−protein interaction on the encapsulation efficiency.19 The only determinant of the encapsulation efficiency in our results appears to be the protein adsorption to the membrane, which strongly affects the EE in a linear manner, according to

interaction diminishes when the proteins become smaller. Full protein density profiles (ξ) for each of these systems are shown in Figure S3 in the Supporting Information. Interestingly, the systems with high values for the membrane adsorption, ω, in Figure 3a, correspond to systems that demonstrate high protein encapsulation in the vesicle formation simulations. This is also illustrated in Figure 4, where EE,

EE = α + βω

(1)

where α and β are constants that may vary for different systems. Because α determines the offset of the measured EE, it may be that α depends on the ratio between the volume and the surface area of the vesicle. Since only the protein concentration in the water near the membrane is affected by the membrane adhesion, larger vesicles will encapsulate a larger volume of solvent that is more distant from the membrane and is expected to have a protein concentration close to that of the bulk. This agrees with the observation from experimental study on single vesicles that, for various encapsulants and lipids, the encapsulation efficiency is inversely proportional to the vesicle diameter, i.e., related to the surface-to-volume ratio of the vesicles.47 The constant β is a scaling factor that may depend on the shape, size, or diffusion rate of the proteins, as well as on other properties of the system. In Figure 3b, we have observed that in this coarse grained model with a neutral lipid headgroup−protein interaction the proteins are rather in the bulk than near the membrane. This thus causes the lower than outside protein concentrations inside the vesicles for this neutral protein−membrane interaction. The same figure also illustrates that the effect of the protein−membrane interaction on ω is stronger for larger proteins than for smaller ones; that is, the difference between the values of ω with a neutral and associated membrane interaction increases with the protein size. This could be due to their larger area, allowing multiple protein particles to interact with the membrane surface, but it could also indicate an entropic effect. As in experimentally created vesicles often multiple protein types of different size are encapsulated, it would be interesting to investigate the mechanism behind this size effect in future research. For each of the employed simulation series, we have measured the adsorption of the used water-soluble proteins to flat membranes. However, as during the bilayer−vesicle transition the membrane is curved, this curvature may influence the adsorption. Therefore, in future work it would be interesting to investigate the adsorption of proteins to curved membranes. Also, it would be interesting to further investigate whether the found linear correlation between the adsorption and the encapsulation efficiency holds for more systems than those studied here and, if so, whether the constants α and β can be quantified. Furthermore, if the relationship in eq 1 is investigated in in vitro experiments, it might be a useful tool for the molecular design of loaded lipid vesicles. While curvature may affect adhesion, also the reverse is true. Adhesion of proteins to the membrane may also affect curvature, and consequently the bilayer to vesicle transition. A variety of mechanisms is known by which proteins may influence membrane curvature.48−50 Two important mechanisms that also have been observed in molecular simulations are (partial) insertion of a protein into the membrane51,52 and proteins functioning as scaffolds,53,54 such as also BAR domain proteins55,56 or clathrin.57 Moreover, proteins could result in

Figure 4. Encapsulation efficiency in vesicle formation simulations with different protein sizes and different membranes, compared to the adsorption of the proteins to planar bilayers (ω). Shown are EE values of the P2-H2T4-neutral, P2-H2T4-associated, P5-H2T4-neutral, P17H2T4-neutral, P17-H2T4-associated, P53-H2T4-neutral, P197-H2T4-neutral, P17-TM1:25-neutral, P17-TM1:25-associated, P17-TM1:40-associated, and P17-H4T4T4-neutral vesicle formation simulation series versus their corresponding planar bilayer simulation, together with the linear fit 0.495 + 0.531ω.

defined as the protein concentration in the vesicle interior divided by the overall protein concentration, is plotted against the protein adsorption to the membrane ω. The series with a neutral protein−membrane interaction all have a similar EE around 0.7, while the P2-H2T4-associated, P17-H2T4-associated, P17-TM1:40-Associated, and P17-TM1:25-associated series have distinctly higher EE values of 1.4, 2.5, 3.0, and 3.8, respectively.

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DISCUSSION Using a series of molecular dynamics simulations, we have shown that (i) the presence of water-soluble proteins hardly influences the bilayer−vesicle transition; (ii) for a neutral membrane−protein interaction, i.e., εPP = εPH = εPW, the encapsulation of such macromolecules during the vesicle formation results in a lower than bulk inside protein concentration both for H2T4 membranes as well as for H4T4T4 membranes; (iii) for this neutral membrane−protein interaction this protein concentration is independent of the protein size; (iv) the addition of transmembrane proteins reduces the vesicle formation speed, where the extent of this reduction depends on the concentration of transmembrane proteins stiffening the membrane, but this does not increase the lower than bulk inside protein concentration; (v) also influencing the vesicle formation mechanism by blocking the bilayer bulging with a second membrane does not increase the inside protein concentration; (vi) the encapsulation strongly enhances with increased membrane−protein interaction; and (vii) there is an almost linear relation between encapsulation efficiency and adsorption of the proteins to planar membranes. From this we conclude that in our model system the encapsulation of proteins during spontaneous vesicle formation is not limited by the diffusion of the macromolecules and that it also does not depend on the precise mechanism of the vesicle 3351



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asymmetric distribution of the lipids over both membrane leaflets, which in turn yields curvature preference.44,58,59 Recently it has also been suggested that even proteins unrelated to membrane curvature can bend membranes when sufficiently concentrated, a mechanism denoted protein−protein crowding.60 However, all of these mechanisms are especially effective when proteins cluster.53,61 In the absence of protein aggregation, the influence of the proteins on the bilayer− vesicle transition appears to be very small in our simulations. In order to make the simulations presented in this work computationally feasible, we have used a coarse grained model where a pseudoatom represents a group of typically four heavy atoms. We have used this coarse grained model previously to study the bilayer−vesicle transition,32,40 fusion of membranes,41 membrane proteins,42,43 as well as vesicle deformation, budding, and fission.44−46 Because the applied coarse graining of course reduces the detailedness of the simulations as compared to fully atomistic simulations, we do not compare our simulations to specific lipids and proteins but rather aim to elucidate generic physical chemical mechanisms of macromolecule encapsulation. Earlier studies of vesicle formation without proteins started either from randomly distributed lipids or from planar bilayers.28−39 Although performed with different models, the pathways observed in all of these simulations are rather similar. In the case in which the lipids are placed randomly, they first form micelles, then these micelles grow by fusion into bicelles (small bilayers), and once a bilayer has grown sufficiently large, it curls into a vesicle. The first step, i.e., aggregation into a sufficiently large bilayer, is relatively slow, whereas the curling is very fast and does not seem to depend on how the bilayer was formed. Here we only focused onto the latter bilayer−vesicle transition. One reason for this is that it enabled us to run sufficiently many simulations to obtain proper statistics. Second the formation of these small bilayers may vary between different liposome preparation methods, but that they are very likely intermediates for instance also easily imaginable when sonicating or dissolving large planar bilayers. Our simulations showed that the encapsulation efficiency can be fully understood based on the protein−lipid interaction. As the protein concentration around the membrane equilibrates fast compared to the vesicle formation, the initial configuration being an artificial nonequilibrium structure seems reasonable. Here, we have extended our previous results with new coarse grained molecular dynamics simulations of the bilayer−vesicle transition for systems containing model water-soluble proteins of different sizes, membranes with incorporated transmembrane proteins, and phospholipid membranes. The bilayer bulging pathway is shown to apply to phospholipid as well as fatty acid membranes. The encapsulation of proteins in the vesicles being formed, however, does not seem to depend on the precise bilayer−vesicle transition mechanism, where the encapsulation efficiency does not depend on the size of the proteins nor on the speed of vesicle formation but can be fully accounted for by the extent of protein adsorption to the membrane. Not only do these simulations provide new insight into the molecular mechanisms of macromolecule encapsulation by liposomes, they also suggest that all earlier mentioned applications, ranging from pharmaceutical nanocarriers to microreactors and from food technology to the fundamental study of protein networks, in all of which a highly efficient loading of the liposomes is needed, may benefit from an increased focus on the membrane−macromolecule interaction.

Article

ASSOCIATED CONTENT

S Supporting Information *

Text describing the analysis of the self-diffusion rates of the water-soluble model proteins employed in this work and of the vesicle formation simulations with differently sized proteins and transmembrane proteins and figures showing self-diffusion rate of the coarse grained water and protein molecules, averages for the simulation series with both different protein sizes and transmembrane proteins, and the protein density profiles as obtained in the protein adsorption study. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS B.v.H. acknowledges financial support from the Dutch National Research School Combination Catalysis Controlled by Chemical Design (NRSC-Catalysis). We also acknowledge NWO Physical Sciences for the assigned computer time.

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REFERENCES

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Molecular Simulation of Protein Encapsulation in Vesicle Formation

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