Inclusion of Terpenoid Plant Extracts in Lipid Bilayers Investigated by

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J. Phys. Chem. B 2010, 114, 15825–15831

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Inclusion of Terpenoid Plant Extracts in Lipid Bilayers Investigated by Molecular Dynamics Simulations† Sarah Witzke,‡,§ Lars Duelund,‡,§ Jacob Kongsted,§ Michael Petersen,⊥,§ Ole G. Mouritsen,‡,§ and Himanshu Khandelia*,‡,§ MEMPHYS - Center for Biomembrane Physics, Nucleic Acids Center, Department of Physics and Chemistry, UniVersity of Southern Denmark, CampusVej 55, DK-5230 Odense M, Denmark tel: +4565503510 Fax: +4565504048 ReceiVed: June 15, 2010; ReVised Manuscript ReceiVed: October 19, 2010

The plant Perilla frutescens is widely employed in Asian medicine. The active components of Perilla include cyclic terpenes, which have a diverse range of antimicrobial, anticancer, sedative, and anti-inflammatory properties, hinting at a membrane-mediated mechanism of action. We have used molecular dynamics (MD) simulations and isothermal titration calorimetry (ITC) to investigate the interaction of four terpenes with model lipid bilayers. The ITC and MD data are mostly in accordance. The terpenes partition into membranes, pack along the lipid tails, and alter bilayer structure and dynamics. Three of the four molecules could cross the bilayer. The carboxylate-group-containing terpene modifies headgroup repulsion and increases the area per lipid by more than 10%, in a manner reminiscent of membrane-thinning peptides and solvents such as DMSO. Our results support the possibility that at least some medicinal properties of volatile Perilla extracts might arise from interactions with the lipid bilayer component of biological membranes. Introduction Perilla frutescens is an annual herb widely distributed in eastern Asia, i.e., China, Korea, and Japan and is used as a condiment and preservative in food. In traditional eastern medicine Perilla is used for treating a highly diverse and comprehensive list of ailments ranging from colds and cough, bacterial infection,1 to asthma.2 The leaf extracts and seed oils from Perilla also have similar medicinal properties.3 The main active components of Perilla are perillaldehyde (4-isopropenyl1-cyclohexene-1-carboxaldehyde, PALD) and limonene (4isopopenyl-1-methyl-1-cyclohexene, LIM).4 A small amount of perillyl alcohol (4- isopropenyl-1-cyclohexenylmethanol, PALC) is also present. LIM and PALD (Figure 1) belong to a class of natural products called terpenes. LIM is readily metabolized to PALD, perillic acid (4-isopropenyl-1-cyclohexene-1-carboxylic acid), and PALC.5 The pKa value of perillic acid is estimated as 5.0 by the computer program Marvin, (Chemaxon, www.chemaxon.com), and it is therefore deprotonated at physiological pH. The deprotonated perillic acid is here termed DPAC. All four terpenes have a common 4-isopropenyl-1-cyclohexene hydrophobic skeleton, which will be referred to as ISOHEX from now on. One or more of the four terpenes, LIM, PALC, PALD, and DPAC, have antibacterial, * Corresponding author. E-mail: [email protected]. † Abbreviations: MD, molecular dynamics; ITC, isothermal titration calorimetry; P.f., Perilla frutescens; LIM, limonene, PALD, perillaldehyde; PALC, perillyl alcohol; DPAC, deprotonated perillic acid; DMPC, 1,2dimyristoyl-sn-glycero-3-phosphocholine; DPPC, 1,2-dipalmitoyl-sn-glycero-3-phosphocholine; POPC, 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine; POPS, 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoserine; DMSO, dimethyl sulfoxide; NMR, nuclear magnetic resonance; ISOHEX, 4-isopropenyl-1-cyclohexene; AL, projected area per lipid; QM, quantum mechanics; TMA: tetramethylammonium. ‡ MEMPHYS - Center for Biomembrane Physics. § Department of Physics and Chemistry. ⊥ Nucleic Acids Center.

Figure 1. The four monoterpenes limonene (LIM), perillyl alcohol (PALC), perillaldehyde (PALD), and deprotonated perillic acid (DPAC). Hydrogen atoms attached to carbons are united with the corresponding carbon atoms. The partial charges are shown only for particles with a nonzero charge.

antifungal,6 antiprotozoan,7 and anticarcinogenic activity and sedative properties.8,9 The mechanism of action of terpenes is presently unknown. The remarkably diverse medicinal properties of these simple molecules suggest that like antimicrobial peptides,10 the biological action of terpenes might be mediated through the lipid bilayer component of the plasma membrane. Leakage of phospholipid

10.1021/jp108675b  2010 American Chemical Society Published on Web 11/11/2010

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vesicles and changes caused in the main phase transition temperature of DMPC have been documented for menthol and thymol, two cyclic terpenes with antibacterial properties and structurally quite similar to the LIM family of monoterpenes.11 There is ample evidence that LIM can perturb bacterial12 and fungal membranes.13 Being very nonpolar, LIM can perturb the mechanical barrier of the skin possibly via lipid reorganization and is commonly used to enhance the transdermal absorption of drugs such as steroids.14 The objective of this work is to obtain physical insights into terpene-lipid interaction and ultimately obtain molecular and thermodynamic details of the mechanism of action of Perilla plant extracts. Natural products have historically served as key seed compounds for drug design,15 and understanding their mode of action will expedite and facilitate future drug development. To quantify the interactions of terpenes with membranes, we have performed molecular dynamics (MD) simulations and isothermal titration calorimetry (ITC) measurements of the four terpenes LIM, PALD, PALC, and DPAC in model lipid bilayers. MD simulation is a powerful technique now routinely used to probe interactions of small molecules such as drugs,16 small organic molecules,17,18 and peptides10 with lipid membranes. We have employed long-time scale MD to probe terpene-lipid interactions. ITC is routinely used to obtain thermodynamic parameters19 and has often been used to study interactions of small molecules with membranes.20-23 For our application, ITC provides information about the membrane partitioning coefficient (K), the enthalpy, entropy, and free energy of the partitioning of the terpenes from the water phase into the lipid membrane. We find that all four terpenes perturb the lipid bilayer significantly. To our best knowledge, this is the first report of interactions of small natural cyclic plant extracts with lipid bilayers investigated using long time-scale MD simulations. Our results provide strong evidence for the first time that the mechanism of action of all four terpenes might be membranemediated. Three of the terpenes act as “molecular glues” which order the membrane. Surprisingly, DPAC, which is also most amphipathic, thins the bilayer and was the only terpene that altered headgroup orientation. The insertion into the bilayer of each terpene is driven by a different balance of enthalpy and entropy as indicated by ITC. The balance is determined by the functional groups on the terpenes. In Results, the physical interactions of the terpenes with lipid bilayer components are discussed in molecular detail. In the Discussion, the significance of the physical interactions is elaborated, and detailed comparisons are drawn with the bilayer interactions of other small compounds. Materials and Methods Molecular Dynamics Simulations. Simulations of the four terpenes LIM, PALC, PALD, and DPAC with model lipid bilayers of DMPC and POPC, all in the fluid phase, were performed. Six different terpene concentrations ranging from 1:128 to 1:4 terpene:lipid ratios were used. With DPAC, two different counterions were used. A total of 28 simulations, each 220 ns long, were implemented. For the interaction with model lipid bilayers, the stereochemistry of the terpenes is not of importance. Therefore we chose to perform studies with only one of the enantiomers, that with an R-configuration. Force Field Parameters. For all lipids simulated in this work, the modified Berger force field was used.24 Parameters for the lipids DMPC and POPC were adapted from http://moose.bio. ucalgary.ca/. The water is represented by a simple point charge

Witzke et al. (SPC) water model.25 Not all force field parameters for the terpenes were available, and hence these parameters were obtained based on density functional theory calculations. The details about the parametrization of the terpenes are provided in the Supporting Information. Sodium and chloride ions are often used as counterions to keep simulation cells electrostatically neutral. However, it is debatable whether the condensing effect of sodium ions on phosphotidylcholine lipids using the modified Berger force field is realistic or a force field artifact.26 To sidestep the possible artifactual phenomenon of sodiuminduced bilayer condensation, we used the larger cation tetramethylammonium (TMA) as a counterion. The larger TMA ions are less likely to penetrate into the lipid headgroup region, and we thus avoid any bilayer condensation attributable to counterions. The topology and force field parameters for TMA were adapted from the parameters of the choline group in the Berger force field. System Construction and Simulation Parameters. Two different lipid bilayers were used for starting configurations DMPC and POPC. The pure DMPC and POPC bilayers both contain 64 lipids in each leaflet. Both of the bilayers had been pre-equilibrated and simulated for approximately 100 ns. The initial rectangular box sizes were 64.705 Å × 64.998 Å × 107.560 Å for DMPC and 65.886 Å × 65.886 Å × 108.401 Å for POPC. The terpene molecules were rotated randomly about their axes and placed at a random position in the aqueous phase. All water molecules within a 1.0 Å distance of any terpene were deleted. For simulations containing DPAC, TMA or sodium ions were also added to keep the system electrostatically neutral. Simulations of the pure lipid bilayers, DMPC in water and POPC in water, were run for 200 and 167.4 ns, respectively. All simulations were performed with the GROMACS package version 4.0.4.27-30 An energy minimization using the steepest decent method was performed, after which the systems were heated during 10 ps of MD by assigning random velocities to the particles according to a Maxwell distribution at 310 K. For the production run, the leapfrog integrator31 was used with a time step of 2 fs. All bond lengths were constrained using the LINCS algorithm,32 and water molecules were constrained with SETTLE.33 Periodic boundary conditions were applied in all directions. A neighbor list with a 10 Å cutoff was used for nonbonded interactions and was updated every 20 fs. The van der Waals interactions were truncated with a cutoff of 10.0 Å, and the electrostatic interactions were treated with the Particle Mesh Ewald (PME) method using default parameters.34,35 The NPT statistical ensemble was used. Temperature coupling was performed using the Berendsen thermostat36 separately for the lipids and for the rest of the system with a reference temperature of 310 K; a time constant of 0.1 ps for both subgroups. A semiisotropic pressure coupling was applied using the Berendsen barostat36 with a coupling constant of 0.1 ps and a reference pressure of 1.0 bar in all directions and a compressibility of 4.5 × 10-5 bar-1. Trajectories were sampled every 10 ps. For calculation of ensemble-averaged properties, the last ∼120 ns of each simulation were used. The analysis was carried out using the GROMACS suite or custom-made programs. Visualization and snapshots were rendered using VMD.37 Isothermal Titration Calorimetry (ITC). DMPC was obtained from Avanti polar lipids (Alabaster, AL). LIM, PALC, and PALD were from Aldrich (Copenhagen, Denmark). DPAC was obtained from Fluka (Copenhagen, Denmark). Sodium phosphate was from Sigma (Copenhagen, Denmark), and sodium chloride was from Merck (VWR, Copenhagen Denmark). All solvents were from Aldrich and of HPLC quality or

Terpenoid Plant Extracts in Lipid Membranes better. Lipid samples for the ITC were prepared by hydrating dry DMPC powder in 50 mM phosphate buffer at pH ) 7.5 and an ion strength of 154 mM adjusted with NaCl, followed by extrusion at 308 K through two stacked WHATNAM nucleopore filters with a hole diameter of 100 nM in a Lipex extruder from Northern Lipids (Vancouver, Canada). See ref 38 for more details. ITC was performed on a VP-ITC calorimeter from Microcal (Northampton, MA). In general the membrane partition coefficient, K, was determined by injection of small aliquot of the lipid suspension (concentration between 1 and 20 mM) into a ca. 300 µM solution of the terpene. Data analysis was performed in Origin 7.0 (Origin Lab, Northampton, MA). Details of the experimental setup and data analysis can be found in ref 39. The model used for calculating the membrane partition coefficients assumes that the following equation holds for all concentrations:

Ct,b ) KCt,f CL where CL is the lipid concentration, K is the membrane partition coefficient, Ct,b and Ct,f are the concentration of bound and free terpene respectively, and it is assumed that their sum is the total terpene injected in the system. For determining K, the experimentally observed integrated heats per injection, δhi was fitted to the following equation:

δhi ) Ct0∆HtVcell

K δCl0 + Qd (1 + iKδCl0)2

where C0t is the terpene concentration in the cell, ∆Ht is the enthalpy for transferring the terpene from the water into the membrane, Vcell is the cell volume (1.409 mL), i is the injection number, δC0l is the change in lipid concentration in the cell per injection, and Qd is the heat of dilution for the injection. The equation differs from the one given in ref 39 by the term Qd. The latter includes both the heat of dilution for the lipid suspension and the terpene solution. Both the terpene and lipid concentrations were corrected for dilution effects by multiplication with a dilution factor, calculated as (Vcell)/(Vcell + iVcell), where i is the injection number. The other thermodynamic parameters were obtained from:

∆G ) -RT ln K ∆G ) ∆H - T∆S Results All simulations were stable and in thermodynamic equilibrium as indicated by the convergence of the total potential energy, area per lipid, and the partitioning of the terpenes inside the membranes (data not shown). The effects on the bilayer exerted by the terpenes were found to gradually increase with increasing terpene concentration (Supporting Information Figures S2 and S3). We only describe results from the highest investigated terpene concentrations, 1:4 terpene:lipid corresponding to ∼180 mM terpene, for which the effect on the bilayer is highest. Although 180 mM sounds like a very high concentration in relation to drug concentrations in blood, the local concentration of drug near a membrane might be much higher than in plasma. The effects of the terpenes on POPC were qualitatively very

J. Phys. Chem. B, Vol. 114, No. 48, 2010 15827 similar to the effect on DMPC, except that the changes in bilayer properties were slightly less pronounced. We therefore discuss only the DMPC data. Partitioning of Terpenes in the Bilayer. In all simulations, the terpenes partition into the bilayer, but the time course of partitioning was not identical. LIM partitioned readily into the membrane being the most hydrophobic terpene. The insertion of LIM into the membranes took up to 20 ns. While in the aqueous phase, most LIM molecules congregated into a micellelike cluster of 18-20 molecules. All molecules that belonged to the same cluster partitioned into the membrane simultaneously. Like LIM, both PALC and PALD formed clusters consisting of ∼20 molecules in the aqueous phase. DPAC, being less hydrophobic and charged, formed smaller clusters (7-10 molecules) in the aqueous phase. Insertion of DPAC molecules into the bilayer took a significantly longer time (∼90 ns). Some representative snapshots from the PALC/DMPC simulation are shown in Figure 2. The terpenes were oriented with their principal axis aligned along the lipid tails (angle distributions not shown). Except LIM, all terpenes had an angle distribution that peaked near 30°, similar to the tilt angle of the lipid tails. LIM had two peaks at ∼30° and ∼150°, because no polar groups anchored it to the interface, and the isopropenyl moiety could either point into the bilayer center or toward the bilayer interface. LIM penetrated deepest into the hydrophobic core of the membrane, and a significant number of the molecules localized to the bilayer center (Figure 3). Conversely, the negatively charged DPAC molecules interacted with the positively charged choline groups at the lipid-water interface and therefore penetrated least into the bilayer. The choline peaks are closer to the bilayer center than the phosphate peaks only in the DPAC simulation, indicating that the P-N vector of DMPC was altered upon interaction with DPAC. The penetration of PALC and PALD into the membrane was deeper than DPAC, and their functional groups interacted with the polar lipid headgroup and the glycerol backbone. Bilayer Thickness, Area per Lipid, and Segmental Order Parameters. The bilayer thickness was calculated from the distance between the two maxima in the electron density profiles of the lipids. Relative to the pure DMPC bilayer, the bilayer thickened by 2.4 Å, 1.7 Å, and 1.3 Å in the presence of LIM, PALC, and PALD, respectively, while the thickness decreased by 1.1 Å upon DPAC insertion (Figure 4a). A more pronounced ‘shoulder’ in the hydrophobic region around z ) (10 Å of the lipid electron density profiles appears upon terpene partitioning (Figure 4a). The shoulder disappears in the total electron density, except in the LIM/DMPC system (Figure 4b). The position of the shoulders coincides with the position of the density peaks of PALC, PALD, and DPAC, which distribute between the bilayer center and the interface (Figure 2), thus increasing the total electron density in this region and eliminating the shoulder. The projected area per lipid (AL) of the bilayer was obtained by dividing the xy area of the simulation box by the number of lipids in one leaflet. AL increased slightly upon insertion of LIM, PALC, and PALD while insertion of DPAC caused a marked 11% increase in the area. The small change caused by LIM, PALC, and PALD is due to two opposing effects: partitioning of small molecules into the bilayer increases AL while ordering of the lipid chains decreases the area occupied by each lipid. In the case of LIM, PALC, and PALD, these opposite effects almost cancel out. DPAC disorders the lipid acyl tails, modifies headgroup-headgroup repulsions, and thus increases AL. The orientational order parameters of the hydrocarbon tails of the lipids were used to quantify the fluidity of the membrane.

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Witzke et al.

Figure 2. Four snapshots from the DMPC/PALC simulation. Lipids are shown in orange, lipid phosphorus atoms are shown as orange spheres, PALC is shown in licorice, PALC OH functional groups are shown in red and white spheres. Water is omitted for clarity. (a) 0 ns: The 32 PALC molecules placed at random positions in the aqueous phase. (b) 8 ns: Most PALC molecules have formed a cluster interacting with the bilayer surface. (c) 16 ns: Most of the PALC molecules have entered the bilayer. (d) 220 ns: PALC molecules are mainly located with their hydroxyl group interacting with the lipid glycerol backbone or phosphate groups.

The z-component of the order parameter for a given vector is defined by

3 1 Sz ) 〈cos2 θz〉 2 2 where θz is the angle between the vector and the z-axis of the simulation box. For the pure bilayer, the values of the order parameters and overall appearance of the curves are in agreement with both experiment40,41 and MD simulations.42-44 The partitioning of LIM, PALC, and PALD resulted in an ordering of the lipid tails, which correlates with the terpene-induced increase in bilayer thickness (Figure 5). LIM penetrates deeper and therefore has a slightly larger ordering effect near the bilayer center compared to PALC and PALD. DPAC perturbed the membrane order only slightly.

Specific Lipid-Terpene Interactions. Radial distribution functions (RDFs) between the terpenes’ functional groups and various chemical moieties of the lipid were calculated in order to extract more detailed information about terpene-lipid interactions. For the RDF analysis, the headgroup region of the lipids was divided into three parts: the choline nitrogen, the phosphate group, and the glycerol carbonyl region. For comparison with the other terpenes, the methyl group of LIM was chosen for the RDF calculations. Stable hydrogen bonds are formed between the hydroxyl groups on PALC and the carbonyl region of the lipids (Figure 6b). The OH group also interacts with the lipid phosphates, but in most cases, the nonpolar region of PALC pulls it into the hydrophobic membrane, and the hydroxyl group can only reach to the glycerol oxygen atoms. The charged carboxylate group

Terpenoid Plant Extracts in Lipid Membranes

Figure 3. Electron density profiles of components of the DMPC lipids and terpenes. Each panel is for a different terpene simulation. The simulation box was divided into 200 slabs for the calculation. All profiles were centered to the origin. The curves for the terpenes (thick black lines) are not symmetric about the origin, because not an equal number of terpenes were placed on either side of the bilayer in the starting conformation. Terp: terpene; Chol: choline; Glyc: glycerol; Phos: phosphate. DPAC penetrated the least into the bilayer while LIM penetrated farthest. Only DPAC alters the relative positions of the phosphate and choline peaks.

Figure 4. (a) Lipid electron density profiles. A shoulder near z ) (10 Å appears when terpenes are introduced into the system. (b) Total electron density profiles. The shoulders in (a) disappear from the total electron density profile, because terpenes partition in that region. The bilayer is thickened by addition of LIM, PALC, and PALD while it is thinned by DPAC.

Figure 5. Segmental order parameters for the sn-1 tail of DMPC. Except DPAC, all terpenes order the acyl tail. DPAC disorders the acyl tails, particularly near the bilayer center.

of DPAC has a strong ionic interaction with the positively charged choline nitrogen (Figure 6d). The peak is located at ∼4 Å because the four methyl groups on choline prevent direct access of the DPAC carboxylate to the nitrogen atom. Hydrogen bonding between PALC and the lipids was subject to detailed analysis. Two molecular groups were considered hydrogen bonded if the distance between the hydrogen donor and acceptor was no more than 3.5 Å and the angle between the hydrogen,

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Figure 6. Radial distribution functions between lipid head groups and terpenes. For the terpenes, the following moieties were used: CH3 group of LIM, CH2OH group of PALC, CHO group of PALD, COO- group of DPAC. Note that the scale of the y-axis is different for each panel. PALC forms hydrogen bonds with phosphate and carbonyl (glycerol) region. DPAC makes salt bridges with the choline group while PALD is anchored to the interface by electrostatic interactions with the carbonyl region.

TABLE 1: Thermodynamic Data for Partitioning of the Terpenes from Water into DMPC Vesicles (303 K) terpene

∆Ginsertion (cal M-1)

∆Hinsertion (cal M-1)

∆Sinsertion (cal M-1 K-1)

Kinsertion (M-1)

LIM PALC PALD

-8167 -5932 -6217

-80 -3706 -830

26.7 7.3 17.5

10870 216 305

hydrogen donor, and hydrogen acceptor (∠HDA) was below 30°. Of the 32 PALC molecules, 28.2 ( 3.3 molecules on an average were involved in hydrogen bonding in a given time frame of the simulation. Ionic interactions between the choline nitrogen and the carboxylate of DPAC were monitored by searching for DPAC carboxyl-lipid nitrogen pairs within a distance of 5.5 Å. The average coordination numbers for different DPAC molecules ranged from 1.5 ( 0.4 to 2.9 ( 0.1 with an average of 2.2 ( 0.5. Salt bridges were formed and broken during the simulation with the average time for an unbroken interaction being ∼1 ns. Terpene Flip-Flop within the Bilayers. The rate at which individual terpenes diffuse from one leaflet of the bilayer to the other indicates the ability of the terpenes to diffuse across a membrane and perhaps eventually bind to an intracellular target in the cell. Flip-flop events were recorded when the center of mass of the terpene moved from an outer headgroup slice to the corresponding slice of the other leaflet. The total number of flip-flop events for LIM, PALD, PALC, and DPAC were 711, 74, 1, and 0, respectively, during 220 ns. The flip-flop rates correlate inversely with the free energy penalty of carrying a more hydrophilic group across the membrane, and inversely with the strength of interactions between the lipid headgroups and the terpenes. DPAC never crossed the membrane. However, if protonated at the interface, its propensity to traverse the bilayer might increase. Isothermal Titration Calorimetry (ITC). ITC was used to determine the thermodynamic properties of terpene insertion into lipid bilayers. Very little DPAC partitioned into DMPC vesicles according to the ITC experiments, and the data for DPAC are not shown in Table 1. We address this observation in the Discussion. The data for the other three terpenes are shown in Table 1. The negative ∆Ginsertion shows that LIM, PALC, and PALD partition spontaneously into the membrane. The partitioning coefficient of LIM is much larger than those of PALC and PALD. The similar values of ∆Ginsertion for LIM,

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PALC, and PALD span large differences in ∆Hinsertion and ∆Sinsertion. The insertion of LIM is driven mostly by entropy while the insertion of PALC is largely enthalpic. PALC forms a multitude of hydrogen bonds with the DMPC headgroup, which explains the large gain in enthalpy. LIM, on the other hand, is nonpolar, has no large enthalpic interactions with the headgroups, and its insertion into the bilayer is driven by the hydrophobic effect, which is the source of the increase in entropy. PALD is more polar than LIM but not capable of forming hydrogen bonds like PALC, hence the enthalpic and entropic contributions to the free energy are intermediate between those of LIM and PALC. Discussion The interactions of the four terpenes, LIM, PALC, PALD, and DPAC, with model lipid bilayers of DMPC and POPC were investigated using atomistic MD simulations and ITC experiments. This combination of theoretical and experimental investigations has provided insight into the physical nature of the interactions and is in support of a general picture within which the terpenes exert their action on the target cell membranes by an alteration of the physical properties of the lipid-bilayer component of the membranes. LIM has no polar functional group and freely diffused in the hydrophobic region of the bilayer. Unlike isoprene, which, according to MD simulations, preferentially partitions into the bilayer center,18 LIM partitions between the bilayer center and the head groups, and there were two density maxima of LIM on the two sides of the bilayer center (Figure 3). The partitioning of the linear butane from the water phase into the membrane center is more favorable than the partitioning of the branched isobutane, indicating that the molecular shape is an important factor in partitioning of small hydrophobic molecules into bilayers.45 The larger surface area of LIM, compared to isoprene, and its disk-like shape make it suitable for van der Waals interactions with the lipid tails, resulting in a snug fit into the lipid acyl tails. If small hydrophobic molecules can pack well inside lipid bilayers in the fluid phase, particularly in the free volume, such molecules can serve as such as a “molecular glue” which would order the membrane and increase bilayer thickness.18 A similar mechanism applies to isoprene18 and LIM. Interestingly, the effects of PALC and PALD are also similar. The effects that LIM, PALC, and PALD exerted on the DMPC bilayer in the simulations were similar with respect to changes in area per lipid, thickness, and order parameters. The decrease of lipid tilt upon insertion of LIM, PALC, and PALD (data not shown) and the simultaneous ordering effect of the terpenes is reminiscent of the effect of cholesterol and epicholesterol. In MD simulations, cholesterol (β-OH cholesterol) decreased the lipid tilt of the sn-1 chain from 28° to 22° and the tilt of the sn-2 chain from 27° to 20°.46 However, epicholesterol (R-OH cholesterol) only reduced the sn-1 chain tilt to 25° and did not affect the tilt of the sn-2 chain. Like LIM, both cholesterol and epicholesterol increased the acyl tail order and both decreased the lipid tilt, but cholesterol was more efficient. The structure of DPAC is similar to salicylate (deprotonated 2-hydroxybenzoic acid), except for the absence of a hydroxyl group in DPAC, and the six-membered ring being aromatic in the latter. Like DPAC, salicylate interacted with the lipid-water interface and its long axis orientational distribution was also along the lipid acyl tails.16 Unlike, DPAC, however, salicylate apparently ordered the lipid tails. The discrepancy has been addressed elsewhere47 and is an effect of the choice of counterions.26 The disordering and membrane thinning effect

Witzke et al. of DPAC is reminiscent of DMSO.17 Like DMSO, DPAC molecules act as spacers between adjoining lipids, and alter the lipid P-N angle distribution, resulting in a marked increase in projected area per lipid. The partitioning thermodynamics of LIM, PALC, and PALD is in excellent agreement with the ITC data. However, unlike the simulations, ITC predicts no partitioning of DPAC into model bilayers. The solvent-null method48 was employed to calculate the partitioning coefficient in an attempt to reconcile the results, but the calculated partitioning coefficient was found to be very small: e5 M-1. In the simulations, it was notable that DPAC behaved differently from the other terpenes, with some of the molecules that bound to the water-membrane interface inserted into the membrane after a long time. DPAC might also be protonated at the lipid-water interface, which has not been taken into account in the simulations. However, given the highly amphipathic structure of DPAC, we still believe that irrespective of protonation state it should partition into the membrane. Moreover, other small cyclic molecules with a pendant carboxylic group such as salicylate (2-hydroxybenzoic acid) and methyl salicylate can all partition at the oil-water interface.16,49 Our simulations are long enough (total of 7 µs) to confidently predict the preferred position of the molecules in a model DMPC lipid bilayer. LIM, PALC, and PALD can all diffuse across the membrane and reach potential intracellular targets, albeit at different rates. Upon diffusion into the cell, PALD and LIM can be enzymatically modified to DPAC or to PALC. Chemical evidence for membrane alteration by the terpenes in bacteria and fungi is so far not convincing, and further experiments will be required to verify if the antimicrobial action of the terpenes is indeed membrane-mediated. However, the results presented here partially vindicate our original hypothesis that Perilla plant extracts might exert their remarkably diverse medicinal properties via membrane modulation. LIM, PALC, and PALD all have an ordering effect on the lipid bilayer, which may influence the function of membrane-associated proteins and processes. However, most drugs interact with and traverse plasma membranes, and it is not possible to conclusively determine from our data if the membrane-altering properties of LIM, PALC, and PALD are directly responsible for their function. DPAC, which is a metabolic product of PALD, has a marked thinning effect on the DMPC and POPC bilayer reminiscent of antimicrobial peptides, which are known to mediate their antimicrobial action via membrane modulation.10 It is possible that with higher concentration of DPAC, the lipid bilayer might undergo lysis, with a mechanism similar to DMSO, but more experiments are needed to confirm this. Furthermore, the functions of proteins in the membrane might be altered as a result of membrane thinning. How does DPAC reach the membrane? One possibility is that LIM and PALD, the two dominant components of Perilla plants, can bind to and traverse cellular plasma membranes and subsequently get metabolized to PALC or DPAC. The sedative effect of PALD and PALC9,50 might indeed be membrane-mediated, via a mechanism previously described for anesthetics.51 It is possible that the terpenes bind intracellular protein targets in the cell, and such a possibility can perhaps never be ruled out. We have described the interaction of these fascinating plant extracts with model membranes, information which will be useful in understanding their mechanism of action and perhaps in the future design of drugs or flavorful medicinal components in food, a paradigm common to Asian cuisine.

Terpenoid Plant Extracts in Lipid Membranes Acknowledgment. MEMPHYS-Center for Biomembrane Physics is supported by the Danish National Research Foundation. The computations were performed at the Danish Center for Scientific Computing (DCSC). J.K. thanks the Danish Natural Science Research Council/Danish Councils for Independent Research for financial support. Supporting Information Available: Figure S1: The atom types used in PALD. The vector connecting atoms C3 and C10 was used to calculate the orientation of the terpene molecules. Figure S2: (A) Increase in the sn-1 lipid tail order parameters upon addition increases with the increase in the concentration of PALD applied. The curves are similar for LIM and PALC. (B) In the case of DPAC, a higher concentration of applied DPAC results in a greater decrease in the order parameters. Figure S3: Concentration-dependent changes in the P-P DMPC bilayer thickness. Higher concentrations of LIM, PALC, and PALD successively increase the thickness proportionately. For DPAC, the trend is the opposite, although only two different concentrations were simulated. This material is available free of charge via the Internet at http://pubs.acs.org. References and Notes (1) Nitta, M.; Lee, J.; Kobayashi, H.; Liu, D.; Nagamine, T. Genet. Resour. Crop EVol. 2005, 52, 663. (2) Deng, Y. M.; Xie, Q. M.; Zhang, S. J.; Yao, H. Y.; Zhang, H. Planta Med. 2007, 73, 53. (3) Kang, R.; Helms, R.; Stout, M. J.; Jaber, H.; Chen, Z. Q.; Nakatsu, T. J. Agric. Food. Chem. 1992, 40, 2328. (4) Hori, M. Appl. Entomol. Zool. 2004, 39, 357. (5) Crowell, P. L.; Gould, M. N. Crit. ReV. Oncogen. 1994, 5, 1. (6) Jin, K. S.; Jun, M.; Park, M. J.; Ok, S.; Jeong, J. H.; Kang, H. S.; Jo, W. K.; Lim, H. J.; Jeong, W. S. Food Sci. Biotechnol. 2008, 17, 447. (7) Arruda, D. C.; Miguel, D. C.; Yokoyama-Yasunaka, J. K. U.; Katzin, A. M.; Uliana, S. R. B. Biomed. Pharmacother. 2009, 63, 643. (8) Marostica, M. R.; Pastore, G. M. Food Sci. Biotechnol. 2009, 18, 833. (9) Saito, K.; Okabe, T.; Inamori, Y.; Tsujibo, H.; Miyake, Y.; Hiraoka, K.; Ishida, N. Mokuzai Gakkaishi 1996, 42, 677. (10) Khandelia, H.; Ipsen, J. H.; Mouritsen, O. G. Biochim. Biophys. Acta 2008, 1778, 1528. (11) Trombetta, D.; Castelli, F.; Sarpietro, M. G.; Venuti, V.; Cristani, M.; Daniele, C.; Saija, A.; Mazzanti, G.; Bisignano, G. Antimicrob. Agents Chemother. 2005, 49, 2474. (12) Di Pasqua, R.; Betts, G.; Hoskins, N.; Edwards, M.; Ercolini, D.; Mauriello, G. J. Agric. Food. Chem. 2007, 55, 4863. (13) Adegoke, G. O.; Iwahashi, H.; Komatsu, Y.; Obuchi, K.; Iwahashi, Y. FlaVour Fragrance J. 2000, 15, 147. (14) Erasto, P.; Viljoen, A. M. Nat. Prod. Commun. 2008, 3, 1193. (15) Newman, D. J.; Cragg, G. M. J. Nat. Prod. 2007, 70, 461.

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