Characterization of Interactions between Curcumin and Different

(b) Area per lipid (APL) of different types of lipid bilayer in the presence and in ...... Jalili , S.; Saeedi , M. Study of curcumin behavior in two ...
0 downloads 0 Views 6MB Size
Article pubs.acs.org/JPCB

Cite This: J. Phys. Chem. B 2018, 122, 2341−2354

Characterization of Interactions between Curcumin and Different Types of Lipid Bilayers by Molecular Dynamics Simulation Yuan Lyu,† Ning Xiang,† Jagannath Mondal,‡ Xiao Zhu,*,§ and Ganesan Narsimhan*,† †

Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, Indiana 47907, United States Centre for Interdisciplinary Sciences, Tata Institute of Fundamental Research, 36/P, Gopanapally Village, Serilingampally Mandal, Ranga Reddy District, Hyderabad 500107, India § Research Computing, Rosen Center for Advanced Computing, Purdue University, West Lafayette, Indiana 47907, United States Downloaded via KAOHSIUNG MEDICAL UNIV on June 30, 2018 at 17:38:06 (UTC). See https://pubs.acs.org/sharingguidelines for options on how to legitimately share published articles.



S Supporting Information *

ABSTRACT: Curcumin (CUR) is a natural food ingredient with known ability to target microbial cell membrane. In this study, the interactions of CUR with different types of model lipid bilayers (POPE, POPG, POPC, DOPC, and DPPE), mixtures of model lipid bilayers (POPE/POPG), and biological membrane mimics (Escherichia coli and yeast) were investigated by all-atom explicit solvent molecular dynamics (MD) simulation. CUR readily inserts into different types of model lipid bilayer systems in the liquid crystalline state, staying in the lipid tails region near the interface of lipid head and lipid tail. Parallel orientation to the membrane surface is found to be more probable than perpendicular for CUR, as indicated by the tilt angle distribution. This orientation preference is less significant as the fraction of POPE is increased in the system, likely due to the better water solvation of perpendicular orientation in the POPE bilayer. In E. coli and yeast bilayers, tilt angle distributions were similar to that for POPE/POPG mixed bilayer, with water hydration number around CUR for the former being higher. Insertion of CUR resulted in membrane thinning. The results from these simulations provide insights into the possible differences in membrane disrupting activity of CUR against different types of microorganisms. cell membranes,36−39 understanding of the detailed interaction mechanism between CUR and cell membranes is still not adequate. Commonly used experimental techniques for directly detecting membrane disruption include (1) measurement of fluorescence intensity of the dye that leaked from cells or liposomes36,38,40 and (2) observation of the membrane structure change through scanning electron microscopy (SEM)36,41 and transmission electron microscopy (TEM).39,42 All-atom molecular dynamics (MD) simulation provides an efficient way to understand the interactions between molecules and lipid bilayer at an atomic level for time scales not accessible by experiments; therefore, it complements experimental methods.43 It is well known that cell membranes are very complex, with a heterogeneous architecture that contains a variety of phospholipids, cholesterol, and membrane proteins. It is also known that the lipid compositions vary with different bacterial strains and in response to changing environment or to exposure to other molecules.44 Model lipid bilayer MD simulation has been widely used for many years due to its capability of providing feasible insights for understanding atomic inter-

1. INTRODUCTION Natural antimicrobial molecules, such as enzymes,1−3 bacteriocins,4−6 essential oils,7−9 organic acids,10,11 and phenolic compounds,12−18 have attracted great attention for use in controlling infectious food-borne outbreaks in recent decades. Among these agents, phenolic compounds have shown the capability to interact with membranes by altering the properties of the cell,19−21 but the exact mechanism responsible for this alteration remains largely unclear. Therefore, curcumin (CUR, 1,7-bis(4-hydroxy-3-methoxyphenyl)-1,6-heptadiene-3,5dione]), as a typical hydrophobic polyphenol molecule extracted from Curcuma longa, was selected for investigation of its interaction with lipid bilayers in this study. CUR has been widely used as a natural food coloring and seasoning from ancient times. It has two aromatic groups with hydroxyl groups and other substituents at each end of the molecule, and the two aromatic rings are linked by a diene chain, similar to the structure of stilbenoids. Isomerization of CUR with keto−enol form has been confirmed by NMR studies.22 As the active component of C. longa turmeric, CUR has been studied worldwide and reported to possess multiple functions, including antimicrobial,23−25 antioxidant,26−28 antiAlzheimer’s,29−31 anticancer,32,33 anti-inflammatory,34,35 etc. Although various studies have reported that CUR is able to inhibit the growth of several microorganisms by targeting their © 2018 American Chemical Society

Received: October 25, 2017 Revised: February 2, 2018 Published: February 2, 2018 2341

DOI: 10.1021/acs.jpcb.7b10566 J. Phys. Chem. B 2018, 122, 2341−2354

Article

The Journal of Physical Chemistry B actions. Simulations of model lipid bilayer not only greatly reduce the complexity of structure construction but also provide us clearer data interpretation to compare with experimental results. Systematic understanding of the effect of lipid properties on the interaction of molecules with the lipid bilayer is important. On the other hand, studying complicated lipid bilayers is necessary to understand the function of a drug in a more realistic system. MD studies on more complex lipid bilayers have been shown to describe more accurately the behavior of a microorganism membrane (such as Escherichia coli and yeast) than simple model lipid bilayers.45−49 It has been shown that several specific components, such as ergosterol,47 cardiolipin (CL),49 and cyclopropane moieties,45 affect the properties of membranes. In this work, we investigated the interaction of CUR with different lipid bilayers through MD simulations: (1) lipids with various size and charge on lipid heads: phosphatidylcholine (PC) vs phosphatidylethanolamine (PE) vs phosphatidylglycerol (PG); (ii) lipids with different degrees of saturation in lipid tails: 1,2-dioleoyl- (DO) vs 1-palmitoyl-2-oleoyl- (PO) vs 1,2-dipalmitoyl- (DP); (iii) mixed model lipid bilayer: 1palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine (POPE)/1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoglycerol (POPG) with ratio of 3:1 to mimic bacteria cell membrane; and (iv) two realistic microorganism cell membrane systems: E. coli and yeast cell membrane. The results obtained from this study will not only provide us specific insights into the interactions between curcumin and different bilayer systems but also give us a more generalized idea for choosing a lipid bilayer on the basis of simulation parameters in the future.

Table 1. System Information of Lipid Bilayers Model Lipid Bilayers lipid type POPE POPG POPC DOPC DPPE

charge

tail info [sn-1/sn-2]

transition temp51

no. of lipids

0 −1 0 0 0

16:0/18:1 16:0/18:1 16:0/18:1 18:1/18:1 16:0/16:0

25 °C (298.15 K) −2 °C (275.15 K) −2 °C (275.15 K) −17 °C (256.15 K) 63 °C (336.15 K)

128 128 128 128 128

Mixture Lipid Bilayer lipid type

no. of lipids

lipid type

no. of lipids

total no. of lipids

POPE

96

POPG

32

128

E. coli Membrane49 lipid type

charge

tail info [sn-1,sn-2/sn-3,sn-4]

no. of lipids

PMCL2 TXCL2 DYPE DPPE PYPE

−2 −2 0 0 0

16:0,16:0/16:0,16:0 16:1,16:1/16:1,16:1 16:1/16:1 16:0/16:0 16:0/16:1

48 18 12 6 6

Yeast Membrane48

2. METHODS 2.1. System Description. We conducted MD simulations of CUR in six different model membranes (pure POPE, POPG, 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC), 1,2-dipalmitoyl-sn-glycero-3-phosphoethanolamine (DPPE), and a mixture of POPE/POPG with ratio of 3:1) and two realistic membrane systems (E. coli membrane consisting of 1,2dipalmitoyl-1′-palmitoyl-2′-cis-9,10-methylenehexadecanoylcardiolipin (PMCL2), 1,2,1′,2′-tetra-hexadecenoyl-cardiolipin (TXCL2), 1,2-dipalmitoleic-phosphatidylethanolamine (DXPE/DYPE), 1,2-dipalmitoyl-phosphatidylethanolamine (DPPE), and 1,2-dioleoyl-sn-glycero-3-phosphoethanolamineN-(1-pyrenesulfonyl) (PYPE); yeast membrane consisting of DOPC, POPE, 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphate (POPA), 1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-L-serine (POPS), 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC), and cholesterol). Detailed information on lipid membrane compositions is listed in Table 1. The E. coli membrane system is almost the same as that employed by Wu et al.,49 with the only difference being their 1-palmitoyl-2-cis9,10-methylenehexadecanoyl-phosphatidylethanolamine (PMPE) replaced by our PYPE. The yeast membrane system contains the same components as that employed by Sunhwan et al.,50 for which the reported properties are similar to our experimental results. The structure of CUR is shown in Figure 1. The initial CUR-membrane systems were constructed using CHARMM-GUI’s Membrane Builder module (http://www. charmm-gui.org/?doc=input/membrane).48 CUR was initially placed either parallel or perpendicular to the lipid bilayer, testing both alignments. The closest distance between a CUR atom and one of the bilayer leaflets was about

lipid type

charge

tail info [sn-1/sn2]

transition temp

no. of lipids

POPA POPS POPE DOPC DPPC CHL

−1 −1 0 0 0 0

16:0/18:1 16:0/18:1 16:0/18:1 18:1/18:1 16:0/16:0 not applicable

28 °C (301.15 K) 14 °C (287.15 K) 25 °C (298.15 K) −17 °C (256.15 K) 41 °C (314.15 K) not applicable

20 10 60 100 20 60

Figure 1. Structure of CUR. Color code: cyan, carbon; red, oxygen; and white, hydrogen.

1 nm (Figure 2a,b). For E. coli and yeast membrane system, CUR was additionally placed in a transmembrane orientation (Figure 2c). The initial arrangements of CUR relative to the lipid bilayer are shown in Figure 2. A 3 nm minimum height of water was added on both the top and the bottom of the system to simulate a fully hydrated bilayer system. A 0.15 M salt (both potassium and chloride were added) concentration was set by mimicking the physiological conditions, and the final system was neutral in charge. All simulations used the CHARMM36 force field for lipids52 and ions and the CHARMM-modified TIP3P water model.53−55 The CUR parameter was generated from the CHARMM general force field (CGenFF).56 2.2. Curcumin Force Field Validation. To validate the molecular model of CUR generated from CGenFF, careful benchmark calculations have been performed, which included a single CUR simulation in both water and 1-octanol and solvation free energy in both solvents, partition coefficient in the water/1-octanol system (log Poctanol/water), and multiple CUR molecules in aqueous solution. 2342

DOI: 10.1021/acs.jpcb.7b10566 J. Phys. Chem. B 2018, 122, 2341−2354

Article

The Journal of Physical Chemistry B

Figure 2. Initial position of CUR at different locations relative to the lipid bilayer: (a) parallel, (b) perpendicular, and (c) transmembrane. Color code: cyan, carbon; red, oxygen; white, hydrogen; brown, phosphate. Water molecules are not shown for clarity.

junction with Truhlar and co-workers’ SMD solvation model.65 The quantum mechanical calculations were performed using the Gaussian 09 package.66 The equilibrium molecular geometry under vacuum is obtained by geometry optimization, using the both M05-2X67 and B3LYP68,69 density functionals with both 6-31G* and 6-31G** quality basis sets. 2.3. Molecular Dynamics Simulations. All simulations were performed with both GROMACS (version 5.1.1)70 and NAMD (version 2.10).71 Simulations performed with NAMD were used to monitor the insertion of CUR (up to 200 ns), whereas GROMACS simulation results were used for analyzing behavior of CUR inside the lipid bilayer (up to 1 μs). In NAMD simulation, periodic boundary conditions were applied in all directions. In all simulations, the cutoff distance for the Coulomb and van der Waals (vdW) interactions was set to 1.2 nm. The force-based switching function was used for the vdW interactions with switching range of 1.0−1.2 nm, as this range was considered to be a standard to compare the lipid properties with other studies.72 Coulomb interactions were calculated by the Particle Mesh Ewald (PME) method.73 The temperature was maintained at 303.15 K, which is above the gel−liquid transition temperatures of 298.15 K for POPE, 275.15 K for POPG, 275.15 K for POPC, and 256.15 K for DOPC, and below 336.15 K for DPPE. The pressure was maintained at 1 atm. The constant temperature was controlled by Langevin dynamics, and constant pressure was controlled by Nosé−Hoover Langevin piston method.74,75 The hydrogen covalent bonds were fixed using the RATTLE algorithm.76The simulation was performed with minimization of 50 000 steps, equilibrium of 5 ns, followed by production of 200 ns with a time step of 2 fs. First 100 ns of simulation were taken for analysis of insertion of CUR into the bilayer. GROMACS simulation setup was similar to NAMD simulation. Periodic boundary conditions and PME method were also applied in the simulations. The force-based switching functions with range of 1.0−1.2 nm for the LJ interactions were used. The reference temperature was set at 303.15 K using a Nosé−Hoover thermostat57,58 extended ensemble thermostat, and the reference pressure was set at 1 atm, coupled with semiisotropically using a Parinello−Rahman barostat59,60 and a time constant of 5 ps. The bonds with H-atoms were constrained using the LINCS algorithm.61 The simulation was performed with minimization of 50 000 steps, equilibrium of 5 ns, followed by production of 1000 ns with a time step of 2 fs. The first 100 ns of simulation was taken for analysis of insertion of CUR into the bilayer, and the last 300 ns was used for analysis of CUR

For a single CUR simulation, the solute molecule was solvated separately in a box (5 × 5 × 5 nm3) containing 4409 water molecules and the same size box with 471 octanol molecules. The CHARMM-modified TIP3P water model53−55 was used for water simulation, and 1-octanol from CGenFF was used in octanol simulation. After energy minimization by the method of steepest descent, the system was equilibrated for 1 ns. Both systems were extended for 200 ns under constant temperature and pressure. In simulations of multiple copies of CUR, 8, 12, or 16 molecules were randomly placed in the simulation box, containing 20 448, 31 488, and 40 084 water molecules, respectively. Simulation procedures similar to those described for a single CUR system were applied except, that the length of production run was 100 ns. Periodic boundary conditions and PME method were applied in all simulations. Force-based switching functions with a range of 1.0−1.2 nm were used for the Lennard-Jones (LJ) interactions. The reference temperature was set at 303.15 K using a Nosé− Hoover57,58 extended ensemble thermostat, and the reference pressure was set at 1 atm, coupled isotropically with a Parinello−Rahman barostat.59,60 The bonds with H-atoms were constrained using the LINCS algorithm.61 The final structures of CUR in water and octanol were used as the starting structures for the calculation of solvation free energy and partition coefficient. The solvation free energy values of CUR in water (ΔGwater) and octanol (ΔGoctanol) were calculated using the thermodynamic integration (TI) method.62 The coupling parameters, λ, were scaled to 21 points (0.00, 0.05, 0.10, 0.15, 0.20, 0.25, 0.30, 0.35, 0.40, 0.45, 0.50, 0.55, 0.60, 0.65, 0.70, 0.75, 0.80, 0.85, 0.90, 0.95, and 1.00). For each value of λ, a complete workflow was conducted by steepest descents minimization, NVT equilibration (100 ps), NPT equilibration (100 ps), and production run (2 ns). The initial 200 ps of the production simulation was removed when calculating the solvation free energy. The partition coefficient (log Poctanol/water) was calculated from the equation63 log Poctanol/water =

ΔGwater − ΔGoctanol 2.303RT

where ΔGwater and ΔGoctanol were obtained from the previous calculation, R is the molar Boltzmann constant, and T is the temperature (300 K in this case). All the MD simulations were performed using the GROMACS (version 5.1.1) software package.64 In addition, solvation free energy of CUR in water was also obtained from Density Functional Theory (DFT) in con2343

DOI: 10.1021/acs.jpcb.7b10566 J. Phys. Chem. B 2018, 122, 2341−2354

Article

The Journal of Physical Chemistry B Table 2. Details of Simulation Timesa GROMACS CUR orientation

POPE

POPG

POPC

DOPC

POPE/POPG

E. coli

yeast

parallel perpendicular transmembrane control

1000 1000

1000 1000

1000 1000

1000 1000

1000 1000

300

300

300

300

300

1000 1000 1000 300

1000 1000 1000 300

CUR orientation

POPE

POPG

POPC

DOPC

POPE/POPG

DPPE

E. coli

yeast

parallel ×3b perpendicular ×2c transmembrane control

200 200

200 200

200 200

200 200

200 200

200 200

200

200

200

200

200

200

300 300 300 300

300 300 300 300

NAMD

a

All values in ns. bThree independent MD runs with different random seed. cTwo independent MD runs with different random seed.

Figure 3. Snapshots of CUR in different model lipid bilayers after 1000 ns simulation. DPPE is 200 ns simulation result. Color codes are the same as Figure 2. Water molecules are not shown for clarity.

S1d. The peak values and positions of [H5, H17]-OW and [O2, O6]-OW were consistent with the work of Ilnytskyi et al., whereas the RDF of [O1, O5]-OW showed a local maximum (0.75) at 0.28 nm, but this value was still much lower than that of the first peak of [O2, O6]-OW (1.41) at 0.29 nm. This qualitative comparison indicated that O1 and O5 in our case had higher possibility to interact with water molecules than CUR with OPLS-UA force field. The structure and solvation properties of CUR (RDF) in octanol were compared with the work of Samanta et al.81 using GROMOS96 parameters. The distribution of distance between H9 and O4 is plotted in Figure S1e. However, in our case, there was a single peak for both water (0.18 nm) and octanol (0.17 nm) cases, indicating the internal hydrogen bond between H9 and O4 was very stable in our case. The RDF for the oxygen of side parts (O1, O2, and O5, O6) and central part (O3, O4) of CUR with respect to the oxygen atoms of the solvent molecules were shown in Figure S1f. It was obvious that the RDF values of CUR in octanol were higher than that in water indicating octanol has higher attraction to CUR. The solvation free energy of CUR was obtained with the values of −75.53 ± 2.25 kJ/mol in water and −100.24 ± 3.15 kJ/mol in octanol. The resulting partition coefficient log Poctanol/water is 4.3, which was higher than the one obtained by Samanta and co-workers (1.17)81 using GROMOS96 force field, but much closer to other theoretically calculated value (3.07 ± 0.4)82 or 2.517 (with CONFLEX/PM3 method).83 Our result agrees with the available values, at least qualitatively, and is consistent with the known solvation property of CUR, i.e. it is more soluble in 1-octanol than water. On the other hand, CGenFF tends to slightly overestimate favorable interaction of CUR with the organic solvent. It is interesting to note that solvation free energies of CUR based on CGenFF model are quite negative in water and 1-octanol. Previous TI simulations reported positive solvation free energy of CUR in

inside the bilayer. The simulation times are summarized in Table 2. 2.4. Data Analysis. Order parameter (SCD), area per lipid (APL), and 2D lateral membrane thickness were calculated using the membrane plug-in77 implemented in VMD. The analysis accounted for lateral area occupied by curcumin, and APL was calculated through a Voronoi diagram using the qvoronoi program from the Qhull package.78 Bilayer thickness was defined as the distance between peaks of the phosphate atoms calculated from density profile. RDF, number of hydrogen bonds, density profile, and potential energy were calculated using tools implemented in VMD79 and GROMACS. The hydrogen bond was determined on the basis of the following criteria: (i) cutoff for the donor−acceptor distance within 0.35 nm, and (ii) cutoff for the hydrogen−donor− acceptor angle within 30°. The standard error of the mean (SEM) was obtained from six independent MD simulations.

3. RESULTS AND DISCUSSION 3.1. Simulation of Curcumin in Water and Octanol. We performed the simulation of CUR in water and octanol, respectively. Several general properties of CUR (including dipole moment, radial distribution function (RDF), and dihedral angles as shown in Figure S1) obtained from water simulation were compared with the work of Ilnytskyi et al., who used OPLS united atom (OPLS-UA) force field.80 For example, the most probable dipole moment obtained from the histogram of CUR in water appeared around 3.5 D (Figure S1b), agreed well with the estimation of CUR in vacuum and water.80 The histogram of the probability of dihedral angle PhD2 (denoted in Figure S1 caption) showed a peak at 0° and small nonzero wings close to ±180° (Figure S1c), indicating H17 was able to point outward to O5. The RDF for the hydrogen (H5, H17) and oxygen (O1, O5, and O2, O6) of side parts of CUR with respect to the oxygen of water (OW) were presented in Figure 2344

DOI: 10.1021/acs.jpcb.7b10566 J. Phys. Chem. B 2018, 122, 2341−2354

Article

The Journal of Physical Chemistry B

Figure 5. Orientation distribution of curcumin in different model lipid bilayers.

Figure 4. Number density profile of CUR and different model lipid bilayers.

aqueous media using different force fields, showing opposite affinity toward water. While there are no available chemical data to verify the results from our simulations, DFT/SMD gives similar solvation free energy in water, for example, −86.5 kJ/ mol with MX05-2X/6-31G* and −72.9 kJ/mol with B3LYP/631G*. In SMD calculations, the nonelectrostatic energy indeed is positive (∼12 kcal/mol in MX05-2X/6-31G*); however, the electrostatics still dominates (−31 kcal/mol), and the dipole moment of the molecule is 5.3 D in water with the MX05-2X/ 6-31G* method. Other functional and basis set combinations give consistent results. Our calculations suggest that parameters for CUR from CGenFF better describe a single CUR molecule interacting with the aqueous media, compared to other force field models that display qualitatively opposite effect. CUR is also known to aggregate in water. Harza et al. reported hydrophobic hydration driven self-assembly of curcumin in water from 40 ns simulation using GROMOS 53a6 force field.84 Bonab and co-workers also observed curcumin−curcumin aggregation in aqueous media by MD simulations.85 Our simulations of multiple CUR molecules in water qualitatively concur with these previous studies. Curcumin monomers form clusters with hydrophilic groups pointing outward, and representative structures are shown in Figure S1g−i. RDF of middle carbon atom in CUR shows a large peak at 0.55 nm for all cases (see Figure S1j,k), but we did

Figure 6. Definition and comparison of CUR in different lipid bilayer. (a) Definition of tilt angle orientation of CUR according to bilayer norm. (b) Tilt angle probability of CUR inside different types of model lipid bilayer.

not observe the different layers of cluster formation as seen by Harza and co-workers. We speculate that the well-known insolubility of CUR in water is caused by its self-aggregation. CUR does have a favorable interaction with water (by those polar hydroxyl and carbonyl) but less compared to organic solvent and also itself. 3.2. Insertion of Curcumin into Model Lipid Bilayer. The snapshots of simulation systems with CUR and different lipid bilayers after 1000 ns are shown in Figures 3 and S2. The replicate snapshots (Figure S2) are found to be similar to the ones presented in Figure 3. We therefore discuss the behavior of CUR based on Figure 3 in the following. CUR is found to 2345

DOI: 10.1021/acs.jpcb.7b10566 J. Phys. Chem. B 2018, 122, 2341−2354

Article

The Journal of Physical Chemistry B

bilayers at the local region near CUR (Figure 3a,c). Time evolution (only the first hundred nanoseconds are shown for clarity) of center of mass of CUR interacting with different lipid bilayers are shown in Figure S3, where the red arrows indicate insertion of CUR into lipid bilayer. The permeation of CUR into the lipid bilayer is favored and occurs within a time scale of hundreds of nanoseconds. The initial orientation has no impact on both insertion time and insertion terminal of CUR into model lipid bilayer (Tables S1 and S2). It is also found that DOPC and POPE/POPG bilayers are relatively easier for CUR insertion as shown in the insertion time comparison (Table S1). The number of hydrogen bonds between CUR and water, and between CUR and lipid bilayer, is monitored during the insertion of CUR (Figure S4). As CUR inserts into the bilayer, the number of hydrogen bonds between CUR and water decreases, while that between CUR and lipid bilayer increases. After insertion, CUR stays inside lipid bilayer, below the phosphate lipid head, suggesting that hydrophobic interaction also plays an important role during this process. We also calculated the time evolution of the positions of O1 and O5 (Figure 1) with respect to the center of lipid bilayer. The end (either O1 or O5) that first inserts into lipid bilayer in different trajectories is listed for each trajectory in Table S2. Not surprisingly, results show that there’s no clear preference for insertion of either end considering the symmetric structure of CUR. 3.3. Position of Curcumin Inside Model Lipid Bilayer. In this section, we characterize the binding position of CUR within lipid bilayer for the last 300 ns of 1000 ns simulation trajectory. The number density profiles of CUR, water, lipid head, glycerol, and terminal methyl groups as a function of distance to bilayer center are shown in Figure 4. CUR distribution is in the range of 0.5−2 nm to bilayer center, and is closer to glycerol than lipid head. This result is consistent with both earlier experimental and simulation results.86−89 Employing high-resolution X-ray diffraction and MD simulation, Alsop et al. recently found that CUR could be inserted into 1,2dimyristoyl-sn-glycero-3-phosphocholine (DMPC) bilayers and stay in the region of glycerol group region,89 consistent with our results. CUR also stays in one of the leaflets without moving through to the other leaflet, which implies existence of an energy barrier for penetration through the lipid bilayer. CUR distributions in POPE and POPE/POPG are found to be wider than the other three lipid bilayers, which indicates the

Figure 7. Radial distribution function g(r) of CUR with respect to different parts of solvent molecules. (a) CUR-WAT: oxygen of CUR to the oxygen of water. (b) CUR-lipid head: oxygen of CUR to the oxygen of lipid head. (c) CUR-glycerol: oxygen of CUR to the oxygen of glycerol group. (d) CUR-terminal methyl: oxygen of CUR to the carbon of terminal methyl.

insert into most of the lipid bilayers except DPPE bilayer. Simulation results show that CUR could insert into model lipid bilayer within a few hundred nanoseconds (Table S1). DPPE bilayer (transition temperature: 336.15 K) is found to be in gel phase at the simulation temperature (303.15 K), as a result, the lipid tails are not flexible to accommodate CUR. Consequently, CUR cannot be inserted into DPPE bilayer up to 200 ns simulation. For other lipid bilayers, CUR stays in the lipid tails region, close to the interface of lipid head and lipid tail, which is the glycerol region. Karewicz et al.86 observed a similar phenomenon through the fluorescence quenching experiment, which is consistent with our simulation results. It is also evident that CUR could interrupt membrane and may change some properties of the lipid bilayer, as shown in Figure 3. For example, bending of lipid heads occurs in POPE and POPC

Figure 8. (a) Number of water within 0.36 nm of CUR at different types of model lipid bilayer. (b) Interaction energy difference between parallel and perpendicular orientation of CUR in different lipid bilayer systems. Coul-CUR-MEMB and Coul-CUR-WAT refer to the Coulombic potential energy between CUR and membrane, and between CUR and water, respectively; LJ-CUR-MEMB and LJ-CUR-WAT refer to the Lennard-Jones potential energy between CUR and membrane, and between CUR and water, respectively. 2346

DOI: 10.1021/acs.jpcb.7b10566 J. Phys. Chem. B 2018, 122, 2341−2354

Article

The Journal of Physical Chemistry B

Figure 9. (a) Bilayer thickness of different types of lipid bilayer in the presence and in the absence of CUR. (b) Area per lipid (APL) of different types of lipid bilayer in the presence and in the absence of CUR. **P-value POPE/POPG > POPC > POPG > DOPC; CUR-glycerol: DOPC > POPG > POPC > POPE/ POPG > POPE) suggesting that this behavior may be attributed to competition between lipid head and glycerol. The first peak of CUR-glycerol are stronger than CUR-lipid head indicating that CUR interacts more strongly with glycerol. The RDFs of CUR-terminal methyl (Figure 7d) are also different for different lipid heads even though the structures of fatty acid chains are exactly the same (except DOPC). CUR in POPE bilayer has lowest probability followed by POPE/POPG, DOPC, POPC, and POPG, which is due to the higher order

parameter of POPE compared to other lipid bilayers as discussed below. The numbers of hydrogen bonds between CUR and water, CUR and membrane, CUR and lipid head, and CUR and glycerol group were also calculated for different model lipid bilayers (Figure S5). The results show that the number of hydrogen bonds between CUR and water (∼1.76− 2.20) is more than that between CUR and membrane (∼0.48− 0.70). CUR did not form more hydrogen bonds with PE lipids than other lipid bilayers (Figure S5a), but the number of hydrogen bonds between CUR and glycerol decreased in the order of POPE, POPE/POPG, POPC, POPG, and DOPC (Figure S5b). The results suggest that the interaction between CUR and water is more pronounced than CUR with lipids, therefore, the solvation property of CUR was further investigated. Since the first solvation shell peak appears at the distance of 0.36 nm from the distance of oxygen atom of CUR with respect to the oxygen atom of water molecules in all the lipid bilayers (Figure 7a), number of water molecules within 0.36 nm of CUR is calculated and compared for different types of lipid bilayers in Figure 8a. In POPE and POPE/POPG lipid bilayers, the number of water molecules is higher in the perpendicular orientation (3.36 and 2.94, respectively) than parallel orientation (2.69 and 2.74, respectively). In contrast, in the other three bilayers, the number of water molecules around CUR is higher in the parallel orientation than perpendicular orientation. This implies that the solvation of CUR is dependent on the structure and property of lipid bilayer. 2348

DOI: 10.1021/acs.jpcb.7b10566 J. Phys. Chem. B 2018, 122, 2341−2354

Article

The Journal of Physical Chemistry B

Figure 14. SCD of DOPC and POPE tails in pure and yeast membrane with and without the presence of CUR. (a,b) POPE in pure membrane, yeast membrane without CUR, and yeast membrane with CUR for sn-1 and sn-2, respectively. (c,d) DOPC in pure membrane, yeast membrane without CUR, and yeast membrane with CUR for sn-1 and sn-2 respectively. Note the error bars are smaller than the symbols.

0.09 nm), POPE (4.21 ± 0.12 nm), POPC (4.01 ± 0.07 nm), DOPC (3.96 ± 0.06 nm), and POPG (3.94 ± 0.05 nm). These values are in good agreement with reported simulation72,90,91 and experimental results.92,93 Although not significant, insertion of CUR causes membrane thickness to increase in POPE bilayer (4.23 ± 0.09 nm), whereas thinning of membrane occurred for all other bilayers (POPE/POPG, 4.11 ± 0.08 nm; POPC, 3.91 ± 0.10 nm; POPG, 3.67 ± 0.05 nm; and DOPC, 3.84 ± 0.09 nm). We also evaluated the lateral 2D membrane thickness and the corresponding density profile of CUR (Figure S8). It shows that CUR insertion could induce local membrane thinning where CUR is located, which is more obvious from the one-dimensional membrane thickness and corresponding CUR distribution at fixed location (Figure S9). Membrane thinning induced by CUR insertion has been reported previously. Huang et al.87 measured the thickness change of DOPC bilayer as a function of the CUR/lipid ratio. Their results showed that there is a nonlinear membrane thinning effect by CUR. Similar results of membrane thickening were reported by Ng et al. for POPE when assembled with an adenosine A2a receptor protein.94 In the absence of CUR, APL increases in the order POPE (0.5517 ± 0.0054 nm2), POPE/POPG (0.5748 ± 0.0072 nm2), POPC (0.6331 ± 0.0054 nm2), POPG (0.6625 ± 0.0024 nm2), and DOPC (0.6760 ± 0.0068 nm2) (Figure 9b). Our results are consistent with both reported experimental results95−97 and simulation results.98,99 Insertion of CUR causes APL to increase (POPE, 0.5651 ± 0.0081 nm2; POPE/POPG, 0.5848 ± 0.0077 nm2; POPC, 0.6482 ± 0.0099 nm2; POPG, 0.6825 ± 0.0120 nm2; and DOPC, 0.6818 ± 0.0134 nm2), and this increase is significant in the POPG lipid bilayer. Sun et al.100 reported the responses of individual giant unilamellar

With the presence of POPE, solvation of perpendicular orientation is higher than parallel orientation. Different components of interaction energy between CUR and membrane, and between CUR and water, are shown in Figure S6, and their differences between parallel and perpendicular orientations are given in Figure 8b. Positive value indicates a specific energy component is stronger for CUR in perpendicular orientation than in parallel orientation, while negative difference suggests an opposite effect. Interestingly, only POPE system shows positive differences in both short-range electrostatic and LJ interactions between CUR and water. This is consistent with the observation of higher water hydration number for CUR in perpendicular orientation in POPE bilayer. In contrast, parallel orientation is more favorable in DOPC bilayer, presumably due to the stronger CUR and water interactions when CUR aligns parallel to the membrane surface. In addition, LJ interaction of CUR and lipid in POPE system is negative (−4.44 kJ/mol), while this value becomes positive in other cases, particularly in DOPC bilayer. Such large positive LJ energy is likely related to the insertion depth of CUR in different systems. Indeed, CUR in perpendicular orientation inserts deeper than that in parallel in DOPC, while the distances between the center of mass and lipid center are similar in both orientations in POPE (Figure S7). 3.5. Effect of Curcumin Insertion on the Bilayer Thickness and Area Per Lipid for Model Lipid Bilayers. Effect of CUR insertion on the bilayer thickness and area per lipid (APL) for different types of model lipid bilayers are evaluated in Figure 9. Bilayer thickness is defined as the distance between two phosphate peaks. In the absence of CUR, bilayer thickness decreases in the order POPE/POPG (4.24 ± 2349

DOI: 10.1021/acs.jpcb.7b10566 J. Phys. Chem. B 2018, 122, 2341−2354

Article

The Journal of Physical Chemistry B

no preference for insertion terminal of CUR into these membranes (Table S2). After insertion, CUR stays inside the lipid tails region of lipid bilayer as shown in the snapshots (Figure 11). Density profile of CUR also indicates that CUR mostly stays in the region from 0.5 to 2 nm, whereas the peak appears below the lipid heads, close to the glycerol group region as shown in Figure 12a. The widths of E. coli lipid head (located at ∼1.97 nm) and glycerol (located at ∼1.53 nm) are larger than yeast membrane (lipid head, ∼2.17 nm; glycerol, ∼1.75 nm), indicating a more flexible membrane environment. It also shows that E. coli membrane has thinner membrane thickness than yeast membrane (Figure 12a), which results in a closer distance of CUR to bilayer center in E. coli membrane (∼1.24 nm) than yeast membrane (∼1.47 nm). The orientation distribution of CUR with respect to the membrane normal was shown in Figure 12b. The average values of the title angle are 85.76° (E. coli) and 87.52° (yeast). To further characterize the behavior of CUR in these two bilayers, orientation of CUR and hydration numbers around the oxygen of CUR are calculated and shown in Figure 13. CUR also predominantly adopts a parallel orientation in both E. coli and yeast membranes (Figure 13a), which is similar to that in model lipid bilayers described previously (section 3.3). More specifically, CUR in yeast membrane (0.35 ± 0.11) has relatively higher probability of perpendicular orientation than in E. coli membrane (0.23 ± 0.06), this probability is very close to the model lipid bilayers consisting of POPE (both POPE and POPE/POPG bilayers). The solvation behavior of CUR in E. coli and yeast bilayers are also calculated to further explore the effect of CUR orientation. The first solvation shell appeared at the distance of 0.36 nm of the oxygen of CUR as shown in the RDF of oxygen of water with respect to oxygen of CUR (Figure S11). Therefore, hydration numbers within 0.36 nm of the oxygen of CUR in both E. coli and yeast membranes are compared in Figure 13b. The results indicate CUR in both E. coli and yeast membranes has solvation behavior similar to that in POPE and POPE/POPG bilayers: the hydration number of CUR with perpendicular orientation is higher than that with parallel orientation. The existence of PE lipids in microbial cell membrane, therefore, plays an important role in influencing its behavior. SCD values for each acyl chain of PMCL2, TXCL2, PYPE, DYPE, and DPPE in E. coli membrane systems are shown in Figure S12, consistent with the work of Wu et al.49 The order parameters for all the lipid molecules are lower than 0.3 indicating that the membrane is in liquid phase. Compared to membrane only (in the absence of CUR), CUR insertion led to PYPE and DYPE being more disordered, while there was no significant effect on SCD for PMCL2, TXCL2, and DPPE. The SCD values of DOPC and POPE in the presence of CUR in both yeast and pure membrane are compared in Figure 14. The order parameters of POPE and DOPC in yeast membrane without CUR are significantly higher than those in pure membrane, thereby indicating that the lipid bilayer is more ordered in yeast membrane. Such a behavior is likely due to the presence of cholesterol, since cholesterol is well known to induce chain order for many phospholipids;112−114 this behavior is evident in our simulation as well (Figure 14). The SCD for POPE is significantly lower for membrane in the presence of CUR, while CUR has no significant effect on the SCD of DOPC membrane. For example, the SCD values for the sn-1 of POPE in the yeast membrane with CUR were more disordered in the region of C5−C10 than that without CUR,

vesicles (GUVs) to the binding of CUR from solution. Their results indicated an increase in the fractional area of DOPC in GUVs due to CUR binding, which is also consistent with our simulation results. 3.6. Order Parameter of Different Model Lipid Bilayers in the Absence of Curcumin. Comparison of SCD for different lipid bilayers are shown in Figure 10. SCD of sn-1 (chain 1) for POPE is the highest, followed by POPE/POPG, POPC, POPG, and DOPC. SCD of sn-2 (chain 2) for POPE is also highest, followed by POPE/POPG, POPC, DOPC, and POPG. CUR insertion causes an increase in the order parameter for POPE and a decrease for the other four bilayer systems. These differences are significant in POPE and POPG bilayer systems. More specifically, with the presence of CUR, the SCD values for sn-1 chain increased from C6 to C12 in POPE and decreased from C5 to C11 in POPG, the SCD values for sn-2 chain increased from C3 to C5 in POPE and decreased from C3 to C6 in POPG, all these regions being close to the glycerol region of lipid bilayer. Similar increase in order parameter was reported for DMPC bilayers. Barry et al.101 measured two-dimensional proton detected local field (PDLF) spectra which showed that CUR increased the overall order of the DMPC membrane. CUR introduced disorder in DPPC through infrared spectroscopy was also reported before,102 which is similar to our simulation in POPC and POPG bilayers. 3.7. Insertion of Curcumin into an E. coli Inner Membrane and Yeast Membrane. In nature, bacterial cell membrane is far more complicated than these model lipid bilayers. For example, E. coli is a Gram-negative bacterium, which contains both outer membrane and inner membrane. Outer membrane usually contains one layer of linked lipopolysaccharides (LPS) and one layer of phosphate lipids. Inner membrane is usually negatively charged mixed lipid bilayer. As a bacteria, E. coli could increase its osmotic stress tolerance by increase in its CL content.103 Observation of selective staining E. coli by fluorescent lipophilic dyes104,105 through fluorescence microscopy indicated the existence of CL lipid in E. coli polar and septal membrane regions. As a eukaryotic, single-celled microorganism, yeast membrane contain sterols, primarily ergosterol,48,106 whose structure is close to cholesterol. Although MD simulations have been employed to investigated the differences of the interaction of molecules with various mixed lipid bilayers (POPE/ POPG,99,107 DOPC/DOPG,108,109 and POPC/POPG110,111) previously, while these mixed bilayer were used to mimic bacterial cell membrane; it is also necessary and important to characterize the interactions between molecules with more realistic lipid bilayers. Therefore, interactions of CUR and realistic cell membrane are investigated and discussed in this section. It is to be noted that the mimics of E. coli and yeast, though realistic, do not account for detailed composition of these bacterial cell membranes but represents only the average lipid composition and therefore may not fully describe their behavior. In the absence of CUR, order parameter for different lipids in E. coli membrane (discussed below) and electron density profile for different compositions in yeast membrane (Figure S10) are consistent with reported results,48,49 indicating the membrane systems are well equilibrated in our simulations. Like other model lipid bilayers, CUR can insert into E. coli and yeast membrane within hundred nanoseconds easily (Table S1). The insertion time of CUR into E. coli and yeast is close to that into POPE/POPG and DOPC bilayers, and there is also 2350

DOI: 10.1021/acs.jpcb.7b10566 J. Phys. Chem. B 2018, 122, 2341−2354

The Journal of Physical Chemistry B



but all these two cases were higher than that for pure POPE bilayer as shown in Figure 14a. The SCD values for both sn-1 and sn-2 of DPPC were significantly lower for membranes in the presence of CUR, and no significant effect on chain order in POPA and POPS membrane (Figure S13). It is clear that the situation of a complex membrane is much more complicated than any pure membrane, all the properties may change due to intermolecular interactions, and our simulation therefore provides qualitative features of interaction of CUR with complex membrane. It is worthwhile to characterize the behavior of multiple CUR molecules in different types of realistic membranes, such as outer membrane of Gram-negative bacteria, plasma membrane of yeast, etc. It would be desirable to consider the interaction between finite CUR molecules with these realistic membranes to explain the antimicrobial activities and trends of thermodynamic properties of CUR. In addition, one can also validate these predictions by comparing with experiments.

AUTHOR INFORMATION

Corresponding Authors

*E-mail: [email protected]. *E-mail: [email protected]. ORCID

Ganesan Narsimhan: 0000-0001-8742-4129 Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS This work was supported by the Extreme Science and Engineering Discovery Environment (XSEDE) [Grant No. TG-CH#160057].



REFERENCES

(1) Cunningham, F. E.; Proctor, V. A.; Goetsch, S. J. Egg-white lysozyme as a food preservative: an overview. World's Poult. Sci. J. 1991, 47 (02), 141−163. (2) Shelef, L. A.; Seiter, J. A. Indirect antimicrobials. In Antimicrobials in Foods, 2nd ed.; Davidson, P. M., Branen, A. L., Eds.; Marcel Dekker: New York, 1993; p 539. (3) Branen, J. K.; Davidson, P. M. Enhancement of nisin, lysozyme, and monolaurin antimicrobial activities by ethylenediaminetetraacetic acid and lactoferrin. Int. J. Food Microbiol. 2004, 90 (1), 63−74. (4) Brewer, R.; Adams, M. R.; Park, S. F. Enhanced inactivation of Listeria monocytogenes by nisin in the presence of ethanol. Lett. Appl. Microbiol. 2002, 34 (1), 18−21. (5) Sobrino-Lopez, A.; Martin-Belloso, O. Enhancing inactivation of Staphylococcus aureus in skim milk by combining high-intensity pulsed electric fields and nisin. J. Food Prot. 2006, 69 (2), 345−353. (6) Gálvez, A.; Abriouel, H.; López, R. L.; Omar, N. B. Bacteriocinbased strategies for food biopreservation. Int. J. Food Microbiol. 2007, 120 (1), 51−70. (7) Mangena, T.; Muyima, N. Y. O. Comparative evaluation of the antimicrobial activities of essential oils of Artemisia afra, Pteronia incana and Rosmarinus officinalis on selected bacteria and yeast strains. Lett. Appl. Microbiol. 1999, 28 (4), 291−296. (8) Skandamis, P.; Tsigarida, E.; Nychas, G. E. The effect of oregano essential oil on survival/death of Salmonella typhimurium in meat stored at 5 C under aerobic, VP/MAP conditions. Food Microbiol. 2002, 19 (1), 97−103. (9) Gutierrez, J.; Barry-Ryan, C.; Bourke, P. Antimicrobial activity of plant essential oils using food model media: efficacy, synergistic potential and interactions with food components. Food Microbiol. 2009, 26 (2), 142−150. (10) Ricke, S. C. Perspectives on the use of organic acids and short chain fatty acids as antimicrobials. Poult. Sci. 2003, 82 (4), 632−639. (11) Theron, M. M.; Lues, J. F. R. Organic acids and food preservation; Taylor & Francis, 2011. (12) Ayala-Zavala, J. F.; Oms-Oliu, G.; Odriozola-Serrano, I.; González-Aguilar, G. A.; Á lvarez-Parrilla, E.; Martín-Belloso, O. Biopreservation of fresh-cut tomatoes using natural antimicrobials. Eur. Food Res. Technol. 2008, 226 (5), 1047−1055. (13) Simões, A. D. N.; Tudela, J. A.; Allende, A.; Puschmann, R.; Gil, M. I. Edible coatings containing chitosan and moderate modified atmospheres maintain quality and enhance phytochemicals of carrot sticks. Postharvest Biol. Technol. 2009, 51 (3), 364−370. (14) Amany, M. B.; Shereen, L. N.; Eman, A. M.; Shaker, M. A. Use of medicinal and aromatic plants for increasing quality of some bakery products. Int. Sci. Invest. J. 2012, 1 (1), 1−23. (15) Ü stündağ, Ö . G.; Erşan, S.; Ö zcan, E.; Ö zan, G.; Kayra, N.; Ekinci, F. Y. Black tea processing waste as a source of antioxidant and antimicrobial phenolic compounds. Eur. Food Res. Technol. 2016, 242 (9), 1523−1532. (16) Ouerghemmi, I.; Rebey, I. B.; Rahali, F. Z.; Bourgou, S.; Pistelli, L.; Ksouri, R.; Marzouk, B.; Tounsi, M. S. Antioxidant and

4. CONCLUSIONS CUR is a widely used natural food ingredient with known membrane activity, but the details of molecular mechanisms remain poorly understood. This manuscript investigates the molecular interactions between CUR and different types of lipid bilayers through microsecond MD simulation. The types of lipid include six model lipid bilayers (POPE, POPC, POPG, DOPC, DPPE, and POPE/POPG) and two realistic cell membrane systems (E. coli and yeast). Simulations on model lipid bilayers provide a good comparison with experimental data that characterize the behavior of CUR and membranes. Simulations on realistic membrane systems will provide detailed information on processes in specific compartments in the cell. The results indicate that CUR could easily insert into lipid bilayer in nanoseconds scale and stay inside. CUR is found to stay in the lipid tails region, close to the interface of lipid head and lipid tail, which is the glycerol region. Parallel orientation is found to be more probable than perpendicular for CUR in all bilayers as well as in E. coli and yeast bilayer systems. The orientation of CUR is related to both solvation properties and nonbonded interaction energies. Insertion of CUR results in membrane thinning with a corresponding increase in area per lipid. CUR interactions with E. coli and yeast cell membranes are quite similar to those with POPE/POPG mixed bilayer. The results from these simulations can provide insights into the possible differences in antimicrobial activity of CUR against different types of microorganisms. The interaction of multiple CUR molecules with both model lipid bilayers and other realistic membrane systems will be the direction of future research.



Article

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jpcb.7b10566. Tables S1 and S2, showing insertion time and orientation of CUR; Figures S1−S13, showing density profile, radial distribution, snapshots, time evolution of center of mass, evolution and number of hydrogen bonds, potential energy contributions, orientation of CUR, 2D profiles of membrane thickness and CUR density, electron density profiles of phospholipids, cholesterol, and water for yeast membrane simulation, and SCD comparison (PDF) 2351

DOI: 10.1021/acs.jpcb.7b10566 J. Phys. Chem. B 2018, 122, 2341−2354

Article

The Journal of Physical Chemistry B antimicrobial phenolic compounds from extracts of cultivated and wild-grown Tunisian Ruta chalepensis. J. Food Drug Anal. 2017, 25 (2), 350−359. (17) Alkan, D.; Yemenicioğlu, A. Potential application of natural phenolic antimicrobials and edible film technology against bacterial plant pathogens. Food Hydrocolloids 2016, 55, 1−10. (18) Salvia-Trujillo, L.; Rojas-Graü, A.; Soliva-Fortuny, R.; MartínBelloso, O. Physicochemical characterization and antimicrobial activity of food-grade emulsions and nanoemulsions incorporating essential oils. Food Hydrocolloids 2015, 43, 547−556. (19) Gill, A. O.; Holley, R. A. Disruption of Escherichia coli, Listeria monocytogenes and Lactobacillus sakei cellular membranes by plant oil aromatics. Int. J. Food Microbiol. 2006, 108 (1), 1−9. (20) Sirk, T. W.; Brown, E. F.; Friedman, M.; Sum, A. K. Molecular binding of catechins to biomembranes: relationship to biological activity. J. Agric. Food Chem. 2009, 57 (15), 6720−6728. (21) Lopes, J. L. S.; Nobre, T. M.; Siano, Á .; Humpola, V.; Bossolan, N. R. S.; Zaniquelli, M. E. D.; Tonarelli, G.; Beltramini, L. M. Disruption of Saccharomyces cerevisiae by Plantaricin 149 and investigation of its mechanism of action with biomembrane model systems. Biochim. Biophys. Acta, Biomembr. 2009, 1788 (10), 2252− 2258. (22) Payton, F.; Sandusky, P.; Alworth, W. L. NMR study of the solution structure of curcumin. J. Nat. Prod. 2007, 70 (2), 143−146. (23) Martins, C. V. B.; Da Silva, D. L.; Neres, A. T. M.; Magalhaes, T. F. F.; Watanabe, G. A.; Modolo, L. V.; Sabino, A. A.; De Fátima, A.; De Resende, M. A. Curcumin as a promising antifungal of clinical interest. J. Antimicrob. Chemother. 2009, 63 (2), 337−339. (24) Zandi, K.; Ramedani, E.; Mohammadi, K.; Tajbakhsh, S.; Deilami, I.; Rastian, Z.; Fouladvand, M.; Yousefi, F.; Farshadpour, F. Evaluation of antiviral activities of curcumin derivatives against HSV-1 in Vero cell line. Nat. Prod. Commun. 2010, 5 (12), 1935−1938. (25) Chattopadhyay, I.; Biswas, K.; Bandyopadhyay, U.; Banerjee, R. K. Turmeric and curcumin: Biological actions and medicinal applications. Curr. Sci. - Bangalore 2004, 87, 44−53. (26) Menon, V. P.; Sudheer, A. R. Antioxidant and anti-inflammatory properties of curcumin. The molecular targets and therapeutic uses of curcumin in health and disease; Springer, 2007; pp 105−125. (27) ToDa, S.; Miyase, T.; Arichi, H.; Tanizawa, H.; Takino, Y. Natural antioxidants. III. Antioxidative components isolated from rhizome of Curcuma longa L. Chem. Pharm. Bull. 1985, 33 (4), 1725− 1728. (28) Ak, T.; Gülçin, I.̇ Antioxidant and radical scavenging properties of curcumin. Chem.-Biol. Interact. 2008, 174 (1), 27−37. (29) Ono, K.; Hasegawa, K.; Naiki, H.; Yamada, M. Curcumin has potent anti-amyloidogenic effects for Alzheimer’s β-amyloid fibrils in vitro. J. Neurosci. Res. 2004, 75 (6), 742−750. (30) Lim, G. P.; Chu, T.; Yang, F.; Beech, W.; Frautschy, S. A.; Cole, G. M. The curry spice curcumin reduces oxidative damage and amyloid pathology in an Alzheimer transgenic mouse. J. Neurosci. 2001, 21 (21), 8370−8377. (31) Venigalla, M.; Gyengesi, E.; Münch, G. Curcumin and Apigenin−novel and promising therapeutics against chronic neuroinflammation in Alzheimer’s disease. Neural Regener. Res. 2015, 10 (8), 1181. (32) Kuttan, R.; Bhanumathy, P.; Nirmala, K.; George, M. C. Potential anticancer activity of turmeric (Curcuma longa). Cancer Lett. 1985, 29 (2), 197−202. (33) Aggarwal, B. B.; Kumar, A.; Bharti, A. C. Anticancer potential of curcumin: preclinical and clinical studies. Anticancer Res. 2003, 23, 363−398. (34) Satoskar, R. R.; Shah, S. J.; Shenoy, S. G. Evaluation of antiinflammatory property of curcumin (diferuloyl methane) in patients with postoperative inflammation. Int. J. Clin. Pharmacol. Ther. Toxicol. 1986, 24 (12), 651. (35) Srimal, R. C.; Dhawan, B. N. Pharmacology of diferuloyl methane (curcumin), a non-steroidal anti-inflammatory agent. J. Pharm. Pharmacol. 1973, 25 (6), 447−452.

(36) Tyagi, P.; Singh, M.; Kumari, H.; Kumari, A.; Mukhopadhyay, K. Bactericidal activity of curcumin I is associated with damaging of bacterial membrane. PLoS One 2015, 10 (3), e0121313. (37) Jiang, Y.; Leung, A. W.; Hua, H.; Rao, X.; Xu, C. Photodynamic action of LED-activated curcumin against Staphylococcus aureus involving intracellular ROS increase and membrane damage. Int. J. Photoenergy 2014, 2014, 637601. (38) Lee, W.; Lee, D. G. An antifungal mechanism of curcumin lies in membrane-targeted action within Candida albicans. IUBMB Life 2014, 66 (11), 780−785. (39) Wang, H.; Hao, L.; Wang, P.; Chen, M.; Jiang, S.; Jiang, S. Release kinetics and antibacterial activity of curcumin loaded zein fibers. Food Hydrocolloids 2017, 63, 437−446. (40) Zhou, L.; Narsimhan, G.; Wu, X.; Du, F. Pore formation in 1, 2dimyristoyl-sn-glycero-3-phosphocholine/cholesterol mixed bilayers by low concentrations of antimicrobial peptide melittin. Colloids Surf., B 2014, 123, 419−428. (41) Suttmann, H.; Retz, M.; Paulsen, F.; Harder, J.; Zwergel, U.; Kamradt, J.; Wullich, B.; Unteregger, G.; Stöckle, M.; Lehmann, J. Antimicrobial peptides of the Cecropin-family show potent antitumor activity against bladder cancer cells. BMC Urol. 2008, 8 (1), 5. (42) Wu, X.; Singh, A. K.; Wu, X.; Lyu, Y.; Bhunia, A. K.; Narsimhan, G. Characterization of antimicrobial activity against Listeria and cytotoxicity of native melittin and its mutant variants. Colloids Surf., B 2016, 143, 194−205. (43) Lopes, D.; Jakobtorweihen, S.; Nunes, C.; Sarmento, B.; Reis, S. Shedding light on the puzzle of drug-membrane interactions: Experimental techniques and molecular dynamics simulations. Prog. Lipid Res. 2017, 65, 24−44. (44) Cheng, J. T. J.; Hale, J. D.; Elliott, M.; Hancock, R. E. W.; Straus, S. K. The importance of bacterial membrane composition in the structure and function of aurein 2.2 and selected variants. Biochim. Biophys. Acta, Biomembr. 2011, 1808 (3), 622−633. (45) Pandit, K. R.; Klauda, J. B. Membrane models of E. coli containing cyclic moieties in the aliphatic lipid chain. Biochim. Biophys. Acta, Biomembr. 2012, 1818 (5), 1205−1210. (46) Khakbaz, P.; Klauda, J. B. Probing the importance of lipid diversity in cell membranes via molecular simulation. Chem. Phys. Lipids 2015, 192, 12−22. (47) Monje-Galvan, V.; Klauda, J. B. Modeling yeast organelle membranes and how lipid diversity influences bilayer properties. Biochemistry 2015, 54 (45), 6852−6861. (48) Jo, S.; Lim, J. B.; Klauda, J. B.; Im, W. CHARMM-GUI Membrane Builder for mixed bilayers and its application to yeast membranes. Biophys. J. 2009, 97 (1), 50−58. (49) Wu, E. L.; Cheng, X.; Jo, S.; Rui, H.; Song, K. C.; DávilaContreras, E. M.; Qi, Y.; Lee, J.; Monje-Galvan, V.; Venable, R. M.; et al. CHARMM-GUI Membrane Builder toward realistic biological membrane simulations. J. Comput. Chem. 2014, 35 (27), 1997−2004. (50) Balliano, L. C.; Milla, P.; Rocco, F.; Conzelmann, A.; Vionnet, C.; Kelly, D. E.; Kelly, S.; Schweizer, E.; Schu, H.-J.; Ller, U. H.; et al. Systematic analysis of yeast strains with possible defects in lipid metabolism. Yeast 1999, 15, 601−614. (51) Silvius, J. R. Thermotropic phase transitions of pure lipids in model membranes and their modifications by membrane proteins. In Lipid-protein interactions; Jost, P. C., Griffith, O. H., Eds.; John Wiley & Sons, Inc.: New York, 1982; Vol. 2, pp 239−281. (52) Klauda, J. B.; Venable, R. M.; Freites, J. A.; O’Connor, J. W.; Tobias, D. J.; Mondragon-Ramirez, C.; Vorobyov, I.; MacKerell, A. D., Jr; Pastor, R. W. Update of the CHARMM all-atom additive force field for lipids: validation on six lipid types. J. Phys. Chem. B 2010, 114 (23), 7830−7843. (53) Jorgensen, W. L.; Chandrasekhar, J.; Madura, J. D.; Impey, R. W.; Klein, M. L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 1983, 79 (2), 926−935. (54) Durell, S. R.; Brooks, B. R.; Ben-Naim, A. Solvent-induced forces between two hydrophilic groups. J. Phys. Chem. 1994, 98 (8), 2198−2202. 2352

DOI: 10.1021/acs.jpcb.7b10566 J. Phys. Chem. B 2018, 122, 2341−2354

Article

The Journal of Physical Chemistry B

(76) Andersen, H. C. Rattle: A “velocity” version of the shake algorithm for molecular dynamics calculations. J. Comput. Phys. 1983, 52 (1), 24−34. (77) Guixà-González, R.; Rodriguez-Espigares, I.; Ramírez-Anguita, J. M.; Carrió-Gaspar, P.; Martinez-Seara, H.; Giorgino, T.; Selent, J. MEMBPLUGIN: studying membrane complexity in VMD. Bioinformatics 2014, 30 (10), 1478−1480. (78) Barber, C. B.; Dobkin, D. P.; Huhdanpaa, H. The quickhull algorithm for convex hulls. ACM Transactions on Mathematical Software (TOMS) 1996, 22 (4), 469−483. (79) Humphrey, W.; Dalke, A.; Schulten, K. VMD: visual molecular dynamics. J. Mol. Graphics 1996, 14 (1), 33−38. (80) Ilnytskyi, J.; Patsahan, T.; Pizio, O. On the properties of the curcumin molecule in water. Exploration of the OPLS-United atom model by molecular dynamics computer simulation. J. Mol. Liq. 2016, 223, 707−715. (81) Samanta, S.; Roccatano, D. Interaction of curcumin with PEO− PPO−PEO block copolymers: a molecular dynamics study. J. Phys. Chem. B 2013, 117 (11), 3250−3257. (82) ACD/Labs. Advanced Chemistry Development Software, V11.02; Advanced Chemistry Development, Inc.: Toronto, Canada, 1994− 2012. (83) Fujisawa, S.; Ishihara, M.; Murakami, Y.; Atsumi, T.; Kadoma, Y.; Yokoe, I. Predicting the biological activities of 2-methoxyphenol antioxidants: effects of dimers. In Vivo 2007, 21 (2), 181−188. (84) Hazra, M. K.; Roy, S.; Bagchi, B. Hydrophobic hydration driven self-assembly of curcumin in water: Similarities to nucleation and growth under large metastability, and an analysis of water dynamics at heterogeneous surfaces. J. Chem. Phys. 2014, 141 (18), 18C501. (85) Bonab, M. I.; Sardroodi, J. J.; Ebrahimzadeh, A. R.; Mehrnejad, F. Molecular Interactions in the Systems Composed of Curcumin, Water and Single-Walled Carbon Nanotube: A Molecular Dynamics Simulation Study. J. Comput. Theor. Nanosci. 2015, 12 (9), 2077− 2083. (86) Karewicz, A.; Bielska, D.; Gzyl-Malcher, B.; Kepczynski, M.; Lach, R.; Nowakowska, M. Interaction of curcumin with lipid monolayers and liposomal bilayers. Colloids Surf., B 2011, 88 (1), 231−239. (87) Hung, W.-C.; Chen, F.-Y.; Lee, C.-C.; Sun, Y.; Lee, M.-T.; Huang, H. W. Membrane-thinning effect of curcumin. Biophys. J. 2008, 94 (11), 4331−4338. (88) Jalili, S.; Saeedi, M. Study of curcumin behavior in two different lipid bilayer models of liposomal curcumin using molecular dynamics simulation. J. Biomol. Struct. Dyn. 2016, 34 (2), 327−340. (89) Alsop, R. J.; Dhaliwal, A.; Rheinstadter, M. C. Curcumin Protects Membranes Through Carpet or Insertion Model Depending on Hydration. Langmuir 2017, 33, 8516−8524. (90) Venable, R. M.; Brown, F. L. H.; Pastor, R. W. Mechanical properties of lipid bilayers from molecular dynamics simulation. Chem. Phys. Lipids 2015, 192, 60−74. (91) Pluhackova, K.; Kirsch, S. A.; Han, J.; Sun, L.; Jiang, Z.; Unruh, T.; Böckmann, R. A. A critical comparison of biomembrane force fields: structure and dynamics of model DMPC, POPC, and POPE bilayers. J. Phys. Chem. B 2016, 120 (16), 3888−3903. (92) Kučerka, N.; Nieh, M.-P.; Katsaras, J. Fluid phase lipid areas and bilayer thicknesses of commonly used phosphatidylcholines as a function of temperature. Biochim. Biophys. Acta, Biomembr. 2011, 1808 (11), 2761−2771. (93) Kučerka, N.; van Oosten, B.; Pan, J.; Heberle, F. A.; Harroun, T. A.; Katsaras, J. Molecular structures of fluid phosphatidylethanolamine bilayers obtained from simulation-to-experiment comparisons and experimental scattering density profiles. J. Phys. Chem. B 2015, 119 (5), 1947−1956. (94) Ng, H. W.; Laughton, C. A.; Doughty, S. W. Molecular dynamics simulations of the adenosine A2a receptor in POPC and POPE lipid bilayers: effects of membrane on protein behavior. J. Chem. Inf. Model. 2014, 54 (2), 573−581. (95) Kučerka, N.; Nagle, J. F.; Sachs, J. N.; Feller, S. E.; Pencer, J.; Jackson, A.; Katsaras, J. Lipid bilayer structure determined by the

(55) Neria, E.; Fischer, S.; Karplus, M. Simulation of activation free energies in molecular systems. J. Chem. Phys. 1996, 105 (5), 1902− 1921. (56) Vanommeslaeghe, K.; Hatcher, E.; Acharya, C.; Kundu, S.; Zhong, S.; Shim, J.; Darian, E.; Guvench, O.; Lopes, P.; Vorobyov, I. CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields. J. Comput. Chem. 2010, 31 (4), 671−690. (57) Nosé, S. A molecular dynamics method for simulations in the canonical ensemble. Mol. Phys. 1984, 52 (2), 255−268. (58) Hoover, W. G. Canonical dynamics: equilibrium phase-space distributions. Phys. Rev. A: At., Mol., Opt. Phys. 1985, 31 (3), 1695. (59) Parrinello, M.; Rahman, A. Polymorphic transitions in single crystals: A new molecular dynamics method. J. Appl. Phys. 1981, 52 (12), 7182−7190. (60) Nosé, S.; Klein, M. L. Constant pressure molecular dynamics for molecular systems. Mol. Phys. 1983, 50 (5), 1055−1076. (61) Hess, B.; Bekker, H.; Berendsen, H. J. C.; Fraaije, J. G. E. M. LINCS: a linear constraint solver for molecular simulations. J. Comput. Chem. 1997, 18 (12), 1463−1472. (62) Kirkwood, J. G. Statistical mechanics of fluid mixtures. J. Chem. Phys. 1935, 3 (5), 300−313. (63) Garrido, N. M.; Queimada, A. J.; Jorge, M.; Macedo, E. A.; Economou, I. G. 1-Octanol/water partition coefficients of n-alkanes from molecular simulations of absolute solvation free energies. J. Chem. Theory Comput. 2009, 5 (9), 2436−2446. (64) Abraham, M.; van der Spoel, D.; Lindahl, E.; Hess, B., and the GROMACS team. GROMACS User Manual, version 5.1.1, 2015; http://www.gromacs.org/. (65) Marenich, A. V.; Cramer, C. J.; Truhlar, D. G. Universal solvation model based on solute electron density and on a continuum model of the solvent defined by the bulk dielectric constant and atomic surface tensions. J. Phys. Chem. B 2009, 113 (18), 6378−6396. (66) Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Mennucci, B.; Petersson, G. A.; et al. Gaussian 09, Revision A; Gaussian Inc.: Wallingford, CT, 2009. (67) Hehre, W. J.; Radom, L.; Schleyer, P. v. R.; Pople, J. A. Ab initio molecular orbital theory; Wiley: New York, 1986. (68) Becke, A. D. Density-functional exchange-energy approximation with correct asymptotic behavior. Phys. Rev. A: At., Mol., Opt. Phys. 1988, 38 (6), 3098. (69) Lee, C.; Yang, W.; Parr, R. G. Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density. Phys. Rev. B: Condens. Matter Mater. Phys. 1988, 37 (2), 785. (70) Abraham, M. J.; Murtola, T.; Schulz, R.; Páll, S.; Smith, J. C.; Hess, B.; Lindahl, E. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 2015, 1-2, 19−25. (71) Phillips, J. C.; Braun, R.; Wang, W.; Gumbart, J.; Tajkhorshid, E.; Villa, E.; Chipot, C.; Skeel, R. D.; Kale, L.; Schulten, K. Scalable molecular dynamics with NAMD. J. Comput. Chem. 2005, 26 (16), 1781−1802. (72) Lee, J.; Cheng, X.; Swails, J. M.; Yeom, M. S.; Eastman, P. K.; Lemkul, J. A.; Wei, S.; Buckner, J.; Jeong, J. C.; Qi, Y.; et al. CHARMM-GUI input generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM simulations using the CHARMM36 additive force field. J. Chem. Theory Comput. 2016, 12 (1), 405−413. (73) Darden, T.; York, D.; Pedersen, L. Particle mesh Ewald: An N· log (N) method for Ewald sums in large systems. J. Chem. Phys. 1993, 98 (12), 10089−10092. (74) Martyna, G. J.; Tobias, D. J.; Klein, M. L. Constant pressure molecular dynamics algorithms. J. Chem. Phys. 1994, 101 (5), 4177− 4189. (75) Feller, S. E.; Zhang, Y.; Pastor, R. W.; Brooks, B. R. Constant pressure molecular dynamics simulation: the Langevin piston method. J. Chem. Phys. 1995, 103 (11), 4613−4621. 2353

DOI: 10.1021/acs.jpcb.7b10566 J. Phys. Chem. B 2018, 122, 2341−2354

Article

The Journal of Physical Chemistry B simultaneous analysis of neutron and X-ray scattering data. Biophys. J. 2008, 95 (5), 2356−2367. (96) Kučerka, N.; Tristram-Nagle, S.; Nagle, J. F. Structure of fully hydrated fluid phase lipid bilayers with monounsaturated chains. J. Membr. Biol. 2006, 208 (3), 193−202. (97) Rappolt, M.; Hickel, A.; Bringezu, F.; Lohner, K. Mechanism of the lamellar/inverse hexagonal phase transition examined by high resolution x-ray diffraction. Biophys. J. 2003, 84 (5), 3111−3122. (98) Skjevik, Å. A.; Madej, B. D.; Dickson, C. J.; Lin, C.; Teigen, K.; Walker, R. C.; Gould, I. R. Simulation of lipid bilayer self-assembly using all-atom lipid force fields. Phys. Chem. Chem. Phys. 2016, 18 (15), 10573−10584. (99) Mukherjee, S.; Kar, R. K.; Nanga, R. P. R.; Mroue, K. H.; Ramamoorthy, A.; Bhunia, A. Accelerated molecular dynamics simulation analysis of MSI-594 in a lipid bilayer. Phys. Chem. Chem. Phys. 2017, 19 (29), 19289−19299. (100) Sun, Y.; Lee, C.-C.; Hung, W.-C.; Chen, F.-Y.; Lee, M.-T.; Huang, H. W. The bound states of amphipathic drugs in lipid bilayers: study of curcumin. Biophys. J. 2008, 95 (5), 2318−2324. (101) Barry, J.; Fritz, M.; Brender, J. R.; Smith, P. E. S.; Lee, D.-K.; Ramamoorthy, A. Determining the effects of lipophilic drugs on membrane structure by solid-state NMR spectroscopy: the case of the antioxidant curcumin. J. Am. Chem. Soc. 2009, 131 (12), 4490−4498. (102) Pérez-Lara, A.; Ausili, A.; Aranda, F. J.; de Godos, A.; Torrecillas, A.; Corbalán-García, S.; Gómez-Fernández, J. C. Curcumin Disorders 1, 2-Dipalmitoyl-sn-glycero-3-phosphocholine Membranes and Favors the Formation of Nonlamellar Structures by 1, 2Dielaidoyl-sn-glycero-3-phosphoethanolamine. J. Phys. Chem. B 2010, 114 (30), 9778−9786. (103) Romantsov, T.; Guan, Z.; Wood, J. M. Cardiolipin and the osmotic stress responses of bacteria. Biochim. Biophys. Acta, Biomembr. 2009, 1788 (10), 2092−2100. (104) Fishov, I.; Woldringh, C. L. Visualization of membrane domains in Escherichia coli. Mol. Microbiol. 1999, 32 (6), 1166−1172. (105) Mileykovskaya, E.; Dowhan, W. Visualization of phospholipid domains inEscherichia coli by using the cardiolipin-specific fluorescent dye 10-N-nonyl acridine orange. J. Bacteriol. 2000, 182 (4), 1172− 1175. (106) Daum, G.; Lees, N. D.; Bard, M.; Dickson, R. Biochemistry, cell biology and molecular biology of lipids of Saccharomyces cerevisiae. Yeast 1998, 14 (16), 1471−1510. (107) Hong, C.; Tieleman, D. P.; Wang, Y. Microsecond molecular dynamics simulations of lipid mixing. Langmuir 2014, 30 (40), 11993− 12001. (108) Lyu, Y.; Zhu, X.; Xiang, N.; Narsimhan, G. Molecular Dynamics Study of Pore Formation by Melittin in a 1, 2-Dioleoyl-snglycero-3-phosphocholine and 1, 2-Di (9 Z-octadecenoyl)-sn-glycero3-phospho-(1′-rac-glycerol) Mixed Lipid Bilayer. Ind. Eng. Chem. Res. 2015, 54 (42), 10275−10283. (109) Lyu, Y.; Xiang, N.; Zhu, X.; Narsimhan, G. Potential of mean force for insertion of antimicrobial peptide melittin into a pore in mixed DOPC/DOPG lipid bilayer by molecular dynamics simulation. J. Chem. Phys. 2017, 146 (15), 155101. (110) Xiang, N.; Lyu, Y.; Zhu, X.; Bhunia, A. K.; Narsimhan, G. Methodology for identification of pore forming antimicrobial peptides from soy protein subunits β-conglycinin and glycinin. Peptides 2016, 85, 27−40. (111) Xiang, N.; Lyu, Y.; Zhu, X.; Bhunia, A. K.; Narsimhan, G. Effect of physicochemical properties of peptides from soy protein on their antimicrobial activity. Peptides 2017, 94, 10−18. (112) Ferreira, T. M.; Coreta-Gomes, F.; Ollila, O. H. S.; Moreno, M. J.; Vaz, W. L. C.; Topgaard, D. Cholesterol and POPC segmental order parameters in lipid membranes: solid state 1 H−13 C NMR and MD simulation studies. Phys. Chem. Chem. Phys. 2013, 15 (6), 1976− 1989. (113) Sankaram, M. B.; Thompson, T. E. Modulation of phospholipid acyl chain order by cholesterol. A solid-state deuterium nuclear magnetic resonance study. Biochemistry 1990, 29 (47), 10676− 10684.

(114) Douliez, J.-P.; Leonard, A.; Dufourc, E. J. Restatement of order parameters in biomembranes: calculation of CC bond order parameters from CD quadrupolar splittings. Biophys. J. 1995, 68 (5), 1727−1739.

2354

DOI: 10.1021/acs.jpcb.7b10566 J. Phys. Chem. B 2018, 122, 2341−2354