Effect of Cholesterol and 6-Ketocholestanol on Membrane Dipole

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New Concepts at the Interface: Novel Viewpoints and Interpretations, Theory and Computations

Effect of Cholesterol and 6-Ketocholestanol on Membrane Dipole Potential and Sterol Flip-Flop Motion in Bilayer Membranes Hujun Shen, Zhenhua Wu, Kun Zhao, Hengxiu Yang, Mingsen Deng, and Shuiguo Wen Langmuir, Just Accepted Manuscript • DOI: 10.1021/acs.langmuir.9b01802 • Publication Date (Web): 02 Aug 2019 Downloaded from pubs.acs.org on August 9, 2019

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Effect of Cholesterol and 6-Ketocholestanol on Membrane Dipole Potential and Sterol Flip-Flop Motion in Bilayer Membranes

Hujun Shen1,2*, Zhenhua Wu2, Kun Zhao2, Hengxiu Yang1, Mingsen Deng1,2*， Shuiguo Wen1 1

Guizhou Provincial Key Laboratory of Computational Nano-Material Science, Guizhou Synergetic Innovation Center of Scientific Big Data for Advanced Manufacturing Technology, Guizhou Education University No.115, Gaoxin Road, Guiyang, Guizhou, 550018, P. R. China

2.

Guizhou University of Finance and Economics, School of Information, University City of Huaxi District, Guiyang, Guizhou, 550025, P. R. China

ACS Paragon Plus Environment

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ABSTRACT A variety of experimental and theoretical approaches have been employed to investigate sterol flip-flop motion in lipid bilayer membranes. However, the sterol effect on the dipole potential of lipid bilayer membranes is less well studied and the influence of dipole potential on sterol flip-flop in lipid bilayer membranes is less well understood. In our previous works, we have demonstrated the performance of our coarse-grained (CG) model in the computation of the dipole potential. In this work, five 30-μs coarsegrained (CG) simulations of dimyristoylphosphatidylcholine (DMPC) bilayers were carried out respectively at different sterol concentrations (in a range from 10% to 50% mole fraction). Then, a comparison was made between the effects of cholesterol (CHOL) and 6-ketocholestanol (6-KC) on the dipole potential of DMPC lipid bilayers as well as the sterol flip-flop motion. Our CG simulations show that membrane dipole potential is impacted more significantly by 6-KC than by CHOL. This finding is consistent with recent experimental studies. Meanwhile, our work suggests that the sterol-sterol interactions (in particular electrostatic interactions) should be critical to the formation of sterol-sterol clusters, which would hinder the sterol flip-flop motion inside lipid bilayers. This is in support of recent experimental study on the sterol transportation in lipid bilayer membranes.


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INTRODUCTION Due to the condensing effect of cholesterol and its analogues on lipid bilayer membranes, the interactions between lipids and sterols in membrane have been widely considered to be the driving force for the formation of lipid raft-like microdomains.1-4 Although the lipid raft hypothesis remains controversial,5,6 lipid rafts are generally thought to be small dynamic nanodomains,5-9 which function as essential platforms for membrane protein localization, cell signal transduction, intracellular trafficking, and so on.10,11 Abundant studies have demonstrated the functional roles of lipid rafts in various kinds of diseases, including neurological and psychiatric diseases,12 prostate cancer,13, HIV,14 Alzheimer’s disease,15 prion diseases,16 and many others. A key aspect of intracellular trafficking in lipid bilayer membranes (or lipid rafts) is transmembrane diffusion (or flip-flop motion) of sterols between leaflets. Various experimental techniques have been employed to reveal the kinetics and mechanism of sterol flip-flop in lipid bilayer membrane, including nuclear magnetic resonance (NMR),17 fluorescence resonance energy transfer (FRET),17,18 time-resolved smallangle neutron scattering (TR-SANS),19 and sum frequency generation vibrational spectroscopy (SFG-VS).20 However, these experiments reported different halftimes of sterol flip-flop (ranging from tens of milliseconds to several hours). In fact, it is very challenging for an experiment to determine the flip-flop rate due to inherent difficulties in tracking the sterol molecules in complex and dynamic lipid bilayer membranes. As a complementary tool to experiment, molecular dynamics (MD) simulation has been widely used to investigate the sterol movement between lipid bilayers. Zhang and coworkers21 calculated the free energy of cholesterol transportation between lipid bilayers using atomistic MD simulations, suggesting that cholesterol flip-flop is more rapid in unsaturated phospholipid bilayer than in saturated phospholipid bilayer. Similarly, Bennett et al.22 used the atomistic and coarse-grained (CG) simulations to calculate the free energies of cholesterol transportation in lipid bilayer membranes, revealing that the flip-flop motion of cholesterol can be hampered by increasing


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cholesterol concentration. Using the string method, Jo et al.23 constructed the twodimensional (2-D) free energy landscape for cholesterol flip-flop, revealing the cholesterol flip-flop pathways in lipid bilayer membranes. Similarly, Parisio et al.24 constructed the multi-dimensional free energy landscapes for steroid flip-flop in lipid bilayers, demonstrating the effects of molecular shape and polarity. Choubey et al.25 performed long atomistic MD simulations (the length of 15 μs), showing that rapid cholesterol flip-flop events can be directly detected (the cholesterol flip-flop rate was estimated to be 3×104 s-1). Although all-atom (AA) MD simulation can provide a reasonable interpretation of experimental results, the AA MD simulations of complex biomolecular systems would be very expensive. This motivates a coarse-grained (CG) treatment of atomistic structures in order to alleviate the computational overhead.

26-33

In particular, the

reduction of an atomistic structure and a larger integration time step would enable us to explore many phenomena or physical processes on larger time and space scales. Recently, Seo and Shinoda34 employed the SPICA CG force field to model the domain formation induced by cholesterol, reporting an observation of phase separation in lipid bilayers fully consistent with experiment. Zhang et al.35 investigated the structural organization of sterol molecules in DPPC bilayer membranes by employing the MARTINI force field,30,31 showing the sensitivity of the lateral organization of sterol molecules to sterol size. Using the MARTINI model, Bennett et al.22 calculated the free energy barrier for the flip-flop motion of cholesterol (∆Gf) in lipid bilayer membranes, showing that the CG results are comparable to that obtained from atomistic simulations. Meanwhile, the CG simulations allow us to directly observe the cholesterol flip-flop movement between leaflets. 22 Unfortunately, the MARTINI CG force field fails to reproduce the dipole potential of lipid bilayers36,37 because the electrostatic interactions between water and lipid are not well treated.38,39 In our previous works,40-42 we have demonstrated the importance of electrostatic interactions in the prediction of the dipole potential. In fact, the dipole potential can generate about 108-109 V/m of electric field, which would substantially promote or prevent the transportation of molecules into lipid bilayer membranes.43-45 However, the


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relation between the dipole potential and the sterol transportation in membranes is less well studied and understood. First, atomistic MD simulations would overestimate the dipole potential when using non-polarizable water models.40,46,47 Second, it is very expansive to use polarizable models to detect the sterol flip-flop motion in lipid membranes. Finally, some popular CG models fail to capture the sterol effect on the dipole potential owing to an inaccurate treatment of electrostatic interactions.37,41,42 In our previous work,48 we presented the CAVS (Charge Attached to Virtual Site) model for water (Figure S1 of Supporting Information). In this approach, a CG bead represents four real water molecules. Each CG bead is composed of two positively charged sites (namely CGPs), one van der Waals (vdW) interaction center (namely CGM), and one virtual site (namely CGN). In the CAVS model for phospholipids (Figure S2 of Supporting Information), electrostatic interaction sites were introduced into the ester groups of phospholipids in order to take into account the contribution of ester dipoles to the dipole potential.41 Moreover, considering the hydrophilic nature of cholesterol, electrostatic interaction sites were introduced into the CAVS model for cholesterol.42 In this work, a comparative study is made between the effects of cholesterol (CHOL)

and

6-ketocholestanol

(6-KC)

on

the

physical

properties

of

dimyristoylphosphatidylcholine (DMPC) bilayer membranes as well as its effect on the sterol flip-flop motion in DMPC bilayer membranes. The 30-μs CAVS simulations of DMPC/CHOL and DMPC/6-KC bilayers were respectively carried out at various sterol concentrations. Our CG simulation results revealed that the 6-KC effect on the dipole potential is more pronounced than the CHOL effect. Furthermore, we observed that 6KC has a greater tendency to the formation of sterol-sterol clusters as compared to CHOL. Consequently, the formation of sterol clusters would influence the flip-flop motion of sterol molecules inside lipid bilayers.


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METHODS Coarse-Grained Model for Cholesterol and 6-Ketocholestanol

Figure 1. Schematic illustration of the coarse-grained (CG) mapping for (A) cholesterol (CHOL) and (B) 6-ketocholestanol (6-KC), the van der Waals (vdW) interaction sites are indicated by black or blue filled circles and the electrostatic interaction sites by blue or red filled circles. The names for CG units are represented in blue color.

The CAVS model for CHOL was presented in our previous work.42 In this work, a similar CG mapping is adopted for 6-KC. The CG mapping for CHOL and 6-KC is illustrated respectively in Figure 1. For instance, the ring of 6-KC was represented by four CG beads (namely CI, CR1, CR2, and CR3). Considering the hydrophilic nature of 6-KC, two interaction sites CIO and OI were included into the CI bead: one (namely CIO) carries a positive charge and the other (namely OI) carries a negative charge. Please note that the CIO site represents the vdW interaction center of the CI bead. Moreover, in the 6-KC model, the C6R particle was considered as an electrostatic


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interaction site because its atomistic representation contains carbonate group (C=O). As for the CHOL model, the C6R particle was considered to be neutral due to its nonpolar nature. Since the dipole moment of 6-KC was estimated to be around 4.0 Debye by quantum mechanics (QM) calculation at the B3LYP/6-31G* level,49 the charges of three interaction sites (CIO, C6R, and OI) were respectively set as 𝑞𝐶𝐼𝑂 = 0.22, 𝑞𝐶6𝑅 = 0.12, and 𝑞𝑂𝐼 = ―0.34 . As for the CHOL model, the charges of two interaction sites (CIO and OI) were set as 𝑞𝐶𝐼𝑂 = 0.25 and 𝑞𝑂𝐼 = ―0.25 because the dipole moment of CHOL was estimated to be around 1.9 Debye.49 The particle types of three CG beads (such as CR1, CR2, and CR3) of sterol (6-KC or CHOL) were respectively assigned with C6R, C4R, and C4R. The hydrophobic tail of sterol was represented by three CG beads (namely CT1, CT2 and CT3), and their particle types were respectively assigned with C3R, C2R, and C3R. Since some earlier works50,51 emphasized the significance of two off-plane methyl groups (-CH3), each methyl group corresponds to a CG bead and the CG particle type of the methyl group (denoted by CS1 or CS2) is assigned with C1R, illustrated in Figure 1. Therefore, the 6-KC model actually adopts all CG parameters of the CHOL model except for the partial charges of CI, OI, and C6R. The parameterization of the CAVS force field for CHOL has been previously described in detail.42 Here, we briefly summarize it here: 1) The CHARMM36 simulations of lipid-CHOL bilayers were used to derive the CAVS force field parameters for the CHOL model. 2) The CAVS force field parameters for bonded interactions (such as the bond stretching term and the angle bending term) were determined by fitting to the bond and angle distributions obtained from the atomistic simulations. The dihedral angle potential is not used because the CAVS simulations can yield acceptable results without considering the dihedral angle potential. 3) The iterative inverse Boltzmann (IB) approach52 was used to determine the van der Waals (vdW) parameters (including the range parameters and well-depth) for the six particle types (such as CIO, C6R, C4R, C1R, C2R, and C3R).


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4) The vdW parameters for the CG model was optimized (in a trial-and-error manner) through the comparison to the atomistic and experimental results for physical properties of lipid bilayers (such as thickness, area per molecule, etc.). 5) Steps 3-4 were repeatedly performed until the CAVS simulations can yield acceptable results. Coarse-Grained (CG) MD Simulations All CAVS simulations were performed using the simulation package GROMACS 4.6.753 and the initial configurations of DMPC/CHOL and DMPC/6-KC bilayers were respectively generated by using the PACKMOL software.54 Each system was equilibrated for 10 ns under NPT condition and then for 5 ns under NVT condition after energy minimizations were carried out. Finally, a production run was performed for at least 6 μs under NPT condition. For each bilayer system, five NPT production runs were performed independently such that the total length of CAVS simulation was 30 μs. For each type of sterol, 512 molecules (including DMPC and sterol molecules) were used with different sterol concentrations (in a range from 10 mol% to 50 mol%). In each case, sterol molecules were randomly inserted into DMPC bilayers. For all CAVS simulations, the constant temperature of 303K was controlled by using the velocity rescaling method55 (with a time constant of 1.0 ps) while the semi-isotropic pressure of 1 bar (with a time constant of 3.0 ps) was maintained by using the ParrinelloRahman method.56 The vdW interactions were calculated by using the shift scheme (shifted from 1.2 nm to 1.6 nm) when electrostatic interactions (with a cut-off value of 1.6 nm) were computed by the PME method57. In this study, the LINCS algorithm58 was used to constrain the bonds inside a CG unit and the integration time step of 15 fs was adopted. Potential of Mean Force (PMF) Calculations An umbrella sampling technique59 has been successfully employed to determine the free energies of cholesterol transportation between the saturated and unsaturated lipid bilayers.21 To calculate the free energies of sterol transportation from the


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membrane-water surface to the bilayer center, we used the umbrella sampling method to determine the potentials of mean force (PMFs) as a function of distance between the mass center of lipid bilayer and the CI bead of CHOL or 6-KC. Then, the free energy barrier of sterol flip-flop can be computed directly through the PMF profiles. In the PMF calculations, we simulated the DMPC bilayers with two different contents (such as 10 mol% and 40 mol%). For each system, 41 windows (or configurations) were used for the PMF calculation. In the first window, one CHOL or 6-KC molecule was moved to the membrane-water interface. In subsequent windows, the CHOL or 6-KC molecule was moved towards the bilayer center along z-axis (bilayer normal) at an interval of 0.07 nm and 40 configurations were generated. For each window, 10 independent NPT simulations were respectively carried out for 50 ns. Please note that five NPT simulations were independently carried out for one leaflet and the other five simulations for the opposite leaflet. During all umbrella sampling simulations, a force constant of 1000 kJ mol-1 nm-2 was applied to restrain the distance between the bilayer center and CI bead. Finally, we employed the weighted histogram analysis method (WHAM)60 to construct the PMF profiles. For each case, the mean PMF values and their standard errors were calculated based on 10 independent NPT simulations.

RESULTS AND DISCUSSION Effect of Sterols on the Dipole Potential of DMPC Lipid Bilayer

Figure 2. The dipole potential of DMPC/CHOL (black) and DMPC/6-KC (red) lipid bilayers at various sterol concentrations, determined from (A) experiment49 and (B) CAVS


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simulations respectively.

In this work, we calculated the electrostatic potential 𝜙𝑒 along the z-axis (bilayer normal) through a double integration of local charge density ρ(z): 1 𝜙𝑒(z) = ― ε0

z

z′

∫ ∫ ρ(z )dz dz′ 0

′′

′′

(1)

0

where ε0 is the vacuum permittivity. From the CAVS simulations, the electrostatic potential profiles were constructed for the DMPC bilayers with different sterol contents, given in Figure S3 of Supporting Information. To determine the dipole potential of lipid bilayer membranes, the difference of electrostatic potential was calculated between the membrane-water interface and the membrane center. Figure 2 illustrates the variation of the dipole potential of DMPC/CHOL and DMPC/6-KC with sterol concentration. From Figure 2, it is seen that the experimental trend can be nicely captured by the CAVS model: when the sterol concentration is below 40 mol%, increasing sterol content would raise the dipole potential. Meanwhile, the experimental results show that the 6-KC effect on the dipole potential is more pronounced than that the CHOL effect, which can be successfully predicted by the CAVS model. This is also consistent with the experimental observation by Shrestha et al.61, who used the vibrational stark effect (VSE) spectroscopy to reveal the different effects of CHOL and 6-KC.

Figure 3. (A) Contribution of lipid to the dipole potential and (B) average tilt angles of the P-N vector at different concentrations of CHOL (black) and 6-KC (red).


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It is known that the dipole potential of PC lipid bilayers is correlated with the orientation of the polar groups (such as lipid head groups, lipid linkage groups, and water molecules)44-47,62 at the water- membrane interface. Specifically, lipid molecules would make a large negative contribution to the dipole potential (see Figure 3A). Moreover, Figure 3A shows that the negative contribution of lipids increases with increasing sterol content and the 6-KC effect is more noteworthy at high sterol concentrations (> 20 mol%) as compared to the CHOL effect. Since the orientation of lipid head groups (defined by the tilt angle of the vector connecting phosphate and nitrogen or P-N vector) would influence the contribution of lipid to dipole potential, we plotted the average tilt angles of the P-N vector (with respect to z-axis) at various sterol concentrations, given in Figure 3B. It is shown that increasing sterol concentration would decrease the tilt angle of P-N vector. Consequently, the P-N vectors are oriented more parallel to z-axis (bilayer normal), leading to the increased negative contribution of lipid to the dipole potential.

Figure 4. (A) Contribution of water to total dipole potential. (B) The lipid area condensation is induced by increasing the content of CHOL (black) and 6-KC (red) in DMPC lipid bilayers.

Figure 4A demonstrates that the positive contribution of water increases with increasing sterol concentration before reaching a plateau at high sterol concentrations (> 20 mol%). Interestingly, it is seen that the 6-KC effect on the contribution of water is comparable to the CHOL effect. It has been shown that the negative contribution of lipid can be overcompensated by the positive contribution of water, resulting in the


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positive dipole potential inside PC lipid bilayers.62-65 However, owing to the sterol condensing effect (Figure 4B), the water penetration into lipid bilayers can be prevented (illustrated in Figure S4 of Supporting Information) such that the effect of water on the change in the dipole potential would become insignificant at high sterol concentrations (> 30 mol%). It is shown in Figure 5A that the sterol molecules (6-KC and CHOL) make a positive contribution to the dipole potential and the contribution of sterol increases with increasing sterol content. Moreover, it is shown that the contribution of 6-KC is greater than that of CHOL. Figure 5B demonstrates that increasing sterol content would decrease the total contribution of non-sterol molecules (water and lipid molecules) at high sterol concentrations (> 20 mol%). Nevertheless, Figure 4B shows that increasing sterol content would have limited influence on the contribution of water at high sterol concentrations (> 20 mol%). Therefore, this suggests that at high sterol concentrations the increase in dipole potential (Figure 2) arises mainly from the increase in the positive contribution of sterol.

Figure 5. Contributions (A) of CHOL (black) and 6-KC (red) and (B) of non-sterol molecules (lipids and water molecules) to total dipole potential at different sterol concentrations.

It has been pointed out that the dipole potential should be correlated with the orientation of molecular dipoles (lipids and water molecules) at the membrane-water interface.66 Nevertheless, Smondyrev et al.67 suggested that the contribution of cholesterol to the dipole potential should not be ignored. Based on the CAVS


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simulations, we determined the average tilt angle 〈𝜃〉 of CHOL and 6-KC in DMPC lipid bilayers according to the following equation: 〈𝜃〉 =

∫

90

𝜃 ∙ 𝜌(𝜃)𝑑𝜃

(2)

0

where 𝜌(𝜃) corresponds to the distribution of the tilt angle 𝜃. The tilt angle 𝜃 is defined as the angle between the orientation of sterol (CHOL or 6-KC) and z-axis. The orientation of CHOL or 6-KC is defined by the tilt angle of the vector CI-CR3 (see Figure S5 of Supporting Information). According to this definition, 𝜃 = 00 denotes that the orientation is parallel to the bilayer normal (z-axis) while 𝜃 = 900 indicates that the orientation is parallel to the bilayer surface (x-y plane).

Figure 6. Variation of the average tilt angle of (A) the CR3-CI vector (shown in Figure S5A of Supporting Information) and (B) the CIO-OI vector (shown in Figure S5B of Supporting Information) with the CHOL (black) and 6-KC (red) concentrations.

Based on the calculated tilt angles of sterol molecules in DMPC bilayers (given in Figure 6A), it is seen that CHOL and 6-KC are oriented more parallel to z-axis (bilayer normal) at high sterol concentrations than at low sterol concentrations, explaining why increasing sterol content would raise the positive contribution of sterol to the dipole potential. Second, at high sterol concentrations (> 20 mol%), it is observed that CHOL is oriented less parallel to the bilayer normal than 6-KC, providing a reasonable explanation why the CHOL effect on the dipole potential is less significant than the 6KC effect. It is shown in Figure 6A that at high sterol concentrations (> 40 mol%) the sterol tilt angle is slightly influenced by increasing sterol content. However, Figure 5A


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shows that increasing sterol content has a substantial influence on the contribution of sterol to the dipole potential. To interpret the bewildering result, we calculated the tilt angles of the CIO-OI vector at different sterol concentrations (shown in Figure 6B) because a large positive charge is placed at the CIO site and a large negative charge is placed at the OI site in the CI bead. One can see from Figure 6B that the orientation of the CIO-OI vector linearly depends on sterol concentration, suggesting the correlation between the contribution of sterol to the dipole potential and the orientation of sterol dipole moment. This is in support of the experimental study of Starke-Peterkovic et al.49, revealing that the dipole potential is correlated with the z-component of the dipole moment of sterol molecules. Effect of Sterols on the Structural Properties of DMPC Lipid Bilayer

Figure 7. Number density profiles of PO4 in the (A) DMPC/CHOL and (B) DMPC/6-KC bilayers at the concentrations of 0 mol% (black), 30 mol% (red) and 50 mol% (blue), obtained from the CAVS simulations.

In this work, the number density profiles of the head group (PO4) were constructed from the CAVS simulations at three representative sterol concentrations, given in Figure 7. Based on the number density profiles, it is straightforward to compute the peak-to-peak distance (Db) between the PO4 beads, which is regarded as the bilayer thickness in this work. Figure 8A shows the variation of DMPC bilayer thickness with sterol concentration. In our previous work,42 a comparison was made between the CAVS and atomistic simulations of lipid bilayers with different CHOL contents,


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showing that the CAVS simulations can qualitatively reproduce the CHOL effect on the DMPC bilayer thickness as compared to the atomistic simulations and experiments. In this work, we compare the effects of 6-KC and CHOL on the DMPC bilayer thickness. From Figure 8A, one can see that the influence of 6-KC on the DMPC bilayer thickness is similar to that of CHOL. Meanwhile, the DMPC bilayer thickness can also be computed by using a grid-based method (GridMAT-MD),68,69 and the calculated results are given in Figure 8B. One can see that these two computational methods yield similar results.

Figure 8. The effect of sterols on the bilayer thickness of DMPC/CHOL (black) DMPC/6KC (red) at different sterol concentrations, calculated by using (A) number density profiles (NDP) and (B) the grid-based method.68,69

Figure 9. The lipid area condensation is induced by increasing the content of CHOL (black) and 6-KC (red) in DMPC lipid bilayers: (A) area per molecule (APM) and (B) area per lipid (APL).


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The area per molecule (APM) A𝑚 can be calculated as follows: A𝑚 =

2 𝐿𝑥 𝐿𝑦 𝑁𝐿

(3)

where 𝑁𝐿 represents the total number of molecules (including sterols and lipids), 𝐿𝑥 corresponds to the length of x-axis, and 𝐿𝑦 is the length of y-axis. In our previous work,42 we have demonstrated that the CHARMM and CAVS models can nicely capture the lipid area condensation induced by CHOL as compared to experiment. In this work, we calculated the lipid area condensation induced by 6-KC and CHOL at different sterol concentrations, presented in Figure 9A. It is seen in Figure 9A that the effects of 6-KC and CHOL on APM are slightly different. Meanwhile, the area per lipid (APL) can also be calculated using the GridMAT-MD method (250×250 grid points were used for the calculations),68,69 given in Figure 9B. It is shown that 6-KC and CHOL have a similar condensing effect on APL.

Figure 10. Sterol-sterol radial distribution functions (RDFs) for (A) head-head and (B) tailtail pairs calculated from the CAVS simulations of DMPC/CHOL (black) and DMPC/6-KC (red) bilayers at the sterol concentration of 40 mol%.

Previously, the MARTINI CG simulations showed that the sterol organization and sterol-lipid interactions are strongly influenced by the sterol size.35 In this work, we examined the influence of the molecular dipole moment on the lateral organization of CHOL and 6-KC in DMPC lipid bilayers. The sterol-sterol radial distribution functions (RDF) were calculated for the head-head and tail-tail pairs at high sterol concentration (40 mol%) respectively, given in Figure 10. In the head-head correlation function, it is


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shown in Figure 10A that the first sharp peak is found at about 0.6 nm and the wide second peak at about 1.0 nm. Interestingly, the first peak height of 6-KC is higher than that of CHOL while the second peak height of 6-KC is lower than that of CHOL. This suggests that the head-head packing of 6-KC is stronger than that of CHOL. Similarly, as for the tail-tail correlation function (shown in Figure 10B), one can see that the first peak height of 6-KC is higher than that of CHOL, indicating that the tail-tail packing of 6-KC is denser than that of CHOL. This is consistent with the atomistic study of Shrestha et al,61 showing that 6-KC tends to strengthen the short-range sterol clusters as compare to CHOL. Consequently, 6-KC is oriented more parallel to the bilayer normal than CHOL (shown in Figure 6), explaining why the contribution of 6-KC to the dipole potential would be more significant than that of CHOL (see Figure 7). Flip-Flop Motion of Sterols in DMPC Lipid Bilayer The flip-flop motion of sterol molecules in lipid bilayers has been investigated by various experimental methods, showing different halftimes of sterol flip-flop in the range of from tens of milliseconds to a few hours.17-19,70,71 Considering that different fluorescence or spin labels used in experiments would influence the sterol flip-flop motion, Ye and Luo20 employed the sum frequency generation vibrational spectroscopy (SFG-VS) (a label-free method) to probe the transport of 6-KC in membranes in situ, suggesting that the formation of strong 6-KC clusters would hamper the flip-flop motion. In this work, we compare the effects of CHOL and 6-KC on the sterol flip-flop motion in DMPC lipid bilayer membranes using the CAVS simulations. The normalized number density profiles for the CI particle of sterols (CHOL and 6-KC) were constructed based on the 30-μs CAVS simulations at two different sterol concentrations (10 mol% and 40 mol%), given in Figure 11. At the low sterol concentration (10 mol%), a wide peak is located at the bilayer center and two sharp peaks are identified at the equilibrium positions (about 1.9 nm from the bilayer center). However, a sharp peak appears at the bilayer center when increasing sterol content (shown in Figure 11B). This suggests the presence of sterol molecules at the bilayer midplane, in consistence with the observation by Weiner and Feigenson,72 who used


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CG simulations to demonstrate the presence of midplane cholesterol in lipid bilayer membranes. However, we discovered that dwell time of sterols is very short (in the order of nanoseconds), explaining why the existence of midplane sterols cannot be easily detected by experiment. Thus, these midplane sterols might exist as the intermediate states during the sterol flip-flop motion. It is shown in Figure 11A that at the low sterol concentration, the population of CHOL at equilibrium positions (or “surface CHOL”) is comparable to that of surface 6-KC. Nevertheless, at the high sterol concentration, surface 6-KC molecules are more populated than surface CHOL molecules (see Figure 11B), in an agreement with the observation in Figure 10.

Figure 11. Normalized number density profiles for the CI particle (head group) of CHOL (black) and 6-KC (red), constructed based on the CAVS simulations of DMPC bilayers at two sterol concentrations of (A) 10 mol% and (B) 40 mol%.

The CAVS simulations allow us to directly observe the flip-flop events of sterol molecules in DMPC lipid bilayers. Figure S6 of Supporting information shows the snapshots obtained from the CAVS simulation of DMPC bilayer at the concentration of 10 mol% CHOL. From this figure, we can see that one CHOL flip-flop event can occur within 50 ns. Based on the 30-μs CAVS simulations, we calculated the observed flip-flop rate of CHOL and 6-KC at two different concentrations (10 mol% and 40 mol%) respectively. To calculate the flip-flop rate of sterols, we monitored the motions of all sterol molecules inside DMPC lipid bilayers. In this work, the motion of a sterol molecule is considered as a complete flip-flop when the following two conditions are satisfied: 1) the head group (CI particle) of sterol located at an equilibrium position


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(about 1.9 nm away from the bilayer center) moves to the bilayer center; (2) the CI particle moves from the bilayer center to opposite equilibrium position (1.9 nm from the bilayer center). For each type of sterol, we counted total flip-flop events 𝐹𝑡𝑜𝑡𝑎𝑙. However, we found that flip-flop events only involved a few sterol molecules, and then we calculated the flip-flop frequency 𝑓𝑠 per molecule by the following equation: 𝑓𝑠 =

𝐹𝑡𝑜𝑡𝑎𝑙 𝑡∗𝑁

(4)

where 𝑡 is the total simulation time (such as 𝑡 = 30 μs) and N represents the total number of sterol molecules, and the final results are summarized in Table 1. From this table, one can see: 1) at the low sterol concentration (10 mol%), the flip-flop rate of 6KC is comparable to that of CHOL; 2) increasing the sterol concentration would decrease the sterol flip-flop rate, in consistence with the atomistic simulation results provided by Bennett et al.;22 3) at the high sterol concentration (40 mol%), the flip-flop motion of 6-KC is much less favorable than that of CHOL. In addition, mean square displacement (MSD) in the y-z plane was computed for the mass center of CHOL or 6KC at two different sterol concentrations (10 mol% and 40 mol%), showing a similar observation given in Table 1 (see Figure S7 of Supporting Information). Table 1. Observed flip-flop frequency (s-1) per molecule calculated from the 30-μs CAVS simulations of DMPC/CHOL and DMPC/6-KC bilayers at two different concentrations of 10 mol% and 40 mol%.

Sterol Concentration 10% 40%

Observed flip-flop rate (s-1) CHOL 6-KC 5 3.69×10 3.34×105 4.08×103 6.52×102

In our previous work,42 we applied the CAVS simulations to calculate the PMFs of cholesterol transportation in lipid bilayer membranes, showing similar results to the ones obtained by the atomistic MD simulations.22 Similarly, we employed the CAVS simulations to determine the PMFs for transferring CHOL and 6-KC from the membrane-water interface to the DMPC bilayer center, given in Figure 12. The CAVS results show the dependence of the sterol flip-flop motion on the sterol concentration


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and the sterol type: 1) at the low sterol concentration (10 mol%), the free energy barrier for moving 6-KC (∆Gff = 28 kJ/mol) is slightly higher than that for moving CHOL (∆Gff = 26 kJ/mol); 2) at the high sterol concentration (40 mol%), the free energy barrier for 6-KC flip-flop (∆Gff = 53 kJ/mol) is much higher than that for CHOL flip-flop (∆Gff = 41 kJ/mol). Therefore, it is clear that increasing sterol concentration would prevent the sterol flip-flop between lipid bilayers and the flip-flop motion of 6-KC would be impeded more strongly than that of CHOL, in support of our direct observation of sterol flip-flop given in Table 1.

Figure 12. PMFs for the CHOL (black) and 6-KC (red) transfer between the membrane surface and membrane center at two sterol concentrations (A )10 mol% and (B) 40 mol%. The standard errors were estimated based on 10 independent PMF calculations (five for each leaflet).

The sterol-lipid radial distribution functions (RDF) were calculated for the headhead and tail-tail pairs at high sterol concentration (40 mol%) respectively, given in Figure 13. In the head-head correlation function, it is shown in Figure 13A that the first sharp peaks are found at about 0.5 nm and the first peak height of 6-KC is higher than that of CHOL (Figure 13A). This suggests that the head-head packing between 6-KC and lipid should be weaker than that between CHOL and lipid. Similarly, the tail-tail correlation function shows that the tail-tail packing between 6-KC and lipid is slightly looser than that between CHOL and lipid (Figure 13B). Therefore, this indicates that at high sterol concentration, the interaction of lipid with 6-KC is weaker that with CHOL. On the other hand, it is seen in Figure 10 that 6-KC molecules have a stronger tendency


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to the formation of sterol-sterol clusters than CHOL molecules at high sterol concentration. This suggests that 6-KC molecules have slower flip-flop motion than CHOL molecules owing to stronger sterol-sterol interactions (including electrostatic and vdW interactions). In particular, the electrostatic interactions should play a critical role in the different effects between CHOL and 6-KC. This is consistent with the atomistic work by Rog et al.73, showing that sterol flip-flop motion would be significantly facilitated by decreasing the hydrophilicity of cholesterol.

Figure 13. Sterol-lipid radial distribution functions (RDFs) for (A) head-head and (B) tailtail pairs calculated from the CAVS simulations of DMPC/CHOL (black) and DMPC/6-KC (red) bilayers at high sterol concentration (40 mol%).

CONCLUSIONS Using the CAVS model, we carried out five 30-μs CG simulations of DMPC bilayer membranes with different sterol concentrations (in a range from 10 mol% to 50 mol%) respectively. First, the CAVS simulations successfully capture the different effects of 6-KC and CHOL on the dipole potential of DMPC bilayers when comparing to experiment, showing that the effect of 6-KC is more prominent than that of CHOL. Our work showed that the different effects arise mainly from different positive contributions of sterol. Second, we discovered that 6-KC and CHOL have similar impact on the structural properties (thickness and area per lipid) of DMPC bilayers. Owing to the condensing effect of sterol, the water penetration is prevented into DMPC lipid bilayers as the sterol concentration increases. As a result, the influence of water


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on the change in membrane dipole potential would be insignificant at high sterol concentrations. Finally, it is observed that the sterol flip-flop motion would be impeded by increasing sterol concentration (or enhancing the sterol-sterol interactions). Our work revealed that the strength of sterol-sterol clusters would influence the sterol flipflop motion, in support of recent SFG-VS study.

AUTHOR INFORMATION Corresponding Authors *E-mail: [email protected] [email protected]

NOTES The authors declare no competing financial interest.

ACKNOWLEDGEMENTS This work is supported by the National Natural Science Foundation of China (No. 21863002), the Natural Science Foundation of Guizhou Province (No. QKHJC[2016]1109), the start-up fund from the Guizhou Education University, the construction project for Guizhou Provincial Key Disciplines (No. ZDXK[2015]10). The Shanghai Supercomputer Center (SSC) is gratefully acknowledged for providing the computational resources in the PMF calculations.

SUPPORTING INFORMATION Supporting Information contains the CAVS model for water and phospholipids, electrostatic potential profiles for DMPC bilayer membranes, number density profiles for water, the orientation of CHOL or 6-KC defined by different vectors, the snapshots for the flip-flop motion of cholesterol, and mean square displacement (MSD) results for the diffusion of CHOL and 6-KC in DMPC bilayers. This information is available


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free of charge via the Internet at http://pubs.acs.org.

REFERENCES 1. London, E. Insights into Lipid Raft Structure and Formation from Experiments in Model Membranes. Curr. Opin. Struct. Biol. 2002, 12, 480-486. 2. Marrink, S. J.; de Vries, A. H.; Harroun, T. A.; Katsaras, J.; Wassall, S. R. Cholesterol Shows Preference for the Interior of Polyunsaturated Lipid Membranes. J. Am. Chem. Soc. 2008, 130, 10-11. 3. Wang, C.; Krause, M. R.; Regen, S. L. Push and Pull Forces in Lipid Raft Formation: The Push Can Be as Important as the Pull. J. Am. Chem. Soc. 2015, 137, 664-666. 4. Bennett, W. F. D.; Shea, J.-E.; Tieleman, D. P. Phospholipid Chain Interactions with Cholesterol Drive Domain Formation in Lipid Membranes. Biophys. J. 2018, 114, 2595-2605. 5. Hancock, J. F. Lipid Rafts: Contentious only from Simplistic Standpoints. Nat. Rev. Mol. Cell Biol. 2006, 7, 456-462. 6. Shaw, A. S. Lipid Rafts: Now You See Them, Now You Don't. Nat. Immunol. 2006, 7, 1139–1142. 7. Edidin, M. The State of Lipid Rafts: From Model Membranes to Cells. Annu. Rev. Biophys. Biomol. Struct. 2003, 32, 257–283. 8. Simons, K.; Vaz, W. L. Model Systems, Lipid Rafts, and Cell Membranes. Annu. Rev. Biophys. Biomol. Struct. 2004, 33, 269-295. 9. Lingwood, D.; Simons, K. Lipid Rafts As a Membrane-Organizing Principle. Science 2009, 327, 46-50. 10. Simons, K.; Ikonen, E. Functional Rafts in Cell Membranes. Nature 1997, 387, 569572. 11. Simons, K.; Toomre, D. Lipid Rafts and Signal Transduction. Nat. Rev. Mol. Cell Biol. 2000, 1, 31-39. 12. Allen, J. A.; Halverson-Tamboli, R. A.; Rasenick, M. M. Lipid Raft Microdomains and Neurotransmitter Signalling. Nat. Rev. Neurosci. 2007, 8, 128-140. 13. Zhuang, L.; Kim, J.; Adam, R. M.; Solomon, K. R.; Freeman, M. R. Cholesterol Targeting Alters Lipid Raft Composition and Cell Survival in Prostate Cancer Cells and Xenografts. J. Clin. Investig. 2005, 115, 959-968. 14. Yang, S.; Kiessling, V.; Simmons, J. A.; White, J. M.; Tamm, L. K. HIV Gp41– Mediated Membrane Fusion Occurs at Edges of Cholesterol-Rich Lipid Domains. Nat. Chem. Biol. 2015, 11, 424-431. 15. Cheng, H.; Vetrivel, K. S.; Gong, P.; Meckler, X.; Parent, A.; Thinakaran, G. Mechanisms of Disease: New Therapeutic Strategies for Alzheimer's Disease—Targeting APP Processing in Lipid Rafts. Nat. Rev. Neurol. 2007, 3 374-382. 16. Walmsley, A. R.; Zeng, F.; Hooper, N. M. The N-terminal Region of the Prion Protein Ectodomain Contains a Lipid Raft Targeting Determinant. J. Biol. Chem. 2003, 278, 37241–37248. 17. Bruckner, R. J.; Mansy, S. S.; Ricardo, A.; Mahadevan, L.; Szostak, J. W. FlipFlop-Induced Relaxation of Bending Energy: Implications for Membrane


Langmuir 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Remodeling. Biophys. J. 2009, 97, 3113-3122. 18. John, K.; Kubelt, J.; Müller, P.; Wüstner, D.; Herrmann, A. Rapid Transbilayer Movement of the Fluorescent Sterol Dehydroergosterol in Lipid Membranes. Biophys. J. 2002, 83, 1525-1534. 19. Garg, S.; Porcar, L.; Woodka, A. C.; Butler, P. D.; Perez-Salas, U. Noninvasive Neutron Scattering Measurements Reveal Slower Cholesterol Transport in Model Lipid Membranes. Biophys. J. 2011, 101, 370-377. 20. Ma, S.; Li, H.; Tian, K.; Ye, S.; Luo, Y. In Situ and Real-Time SFG Measurements Revealing Organization and Transport of Cholesterol Analogue 6-Ketocholestanol in a Cell Membrane. J. Phys. Chem. Lett. 2014, 5, 419-424. 21. Zhang, Z.; Lu, L.; Berkowitz, M. Energetics of Cholesterol Transfer between Lipid Bilayers. J. Phys. Chem. B 2008, 112, 3807-3811. 22. Bennett, W. F. D.; MacCallum, J. L.; Hinner, M. J.; Marrink, S. J.; Tieleman, D. P. Molecular View of Cholesterol Flip-Flop and Chemical Potential in Different Membrane Environments. J. Am. Chem. Soc. 2009, 131, 12714–12720. 23. Jo, S.; Rui, H.; Joseph, B. L.; Klauda, J. B.; Im, W. Cholesterol Flip-Flop: Insights from Free Energy Simulation Studies J. Phys. Chem. B 2010, 114, 13342–13348. 24. Parisio, G.; Sperotto, M. M.; Ferrarini, A. Flip-Flop of Steroids in Phospholipid Bilayers: Effects of the Chemical Structure on Transbilayer Diffusion. J. Am. Chem. Soc. 2012, 134, 12198–12208. 25. Choubey, A.; Kalia, R. K.; Malmstadt, N.; Nakano, A.; Vashishta, P. Cholesterol Translocation in a Phospholipid Membrane. Biophys. J. 2013, 104, 2429-2436. 26. Shen, H.; Li, Y.; Ren, P.; Zhang, D.; Li, G. Anisotropic Coarse-Grained Model for Proteins Based On Gay-Berne and Electric Multipole Potentials. J. Chem. Theory Comput. 2014, 10, 731–750. 27. Shen, H.; Li, Y.; Xu, P.; Li, X.; Chu, H.; Zhang, D.; Li, G. An Anisotropic CoarseGrained Model Based on Gay–Berne and Electric Multipole Potentials and its Application to Simulate a DMPC Bilayer in an Implicit Solvent Model. J. Comput. Chem. 2015, 36, 1103-1113. 28. Li, G.; Shen, H.; Zhang, D.; Li, Y.; Wang, H. Coarse-Grained Modeling of Nucleic Acids Using Anisotropic Gay-Berne and Electric Multipole Potentials. J. Chem. Theory Comput., 2016, 12, 676–693. 29. Shen, H.; Xia, Z.; Li, G.; Ren, P. A Review of Physics-Based Coarse-grained Potentials for the Simulations of Protein Structure and Dynamics. Annu. Rep. Comput. Chem. 2012, 8, 129-148. 30. Marrink, S. J.; de Vries, A. H.; Mark, A. E. Coarse Grained Model for Semiquantitative Lipid Simulations. J. Phys. Chem. B 2004, 108, 750-760. 31. Marrink, S. J.; Risselada, H. J.; Yefimov, S.; Tieleman, D. P.; de Vries, A. H. The MARTINI Force Field: Coarse Grained Model for Biomolecular Simulations. J. Phys. Chem. B 2007, 111, 7812-7824. 32. Melo, M. N.; Ingólfsson, H. I.; Marrink, S. J. Parameters for MARTINI Sterols and Hopanoids based on a Virtual-Site Description. J. Chem. Phys. 2015, 143, 243152. 33. Orsi, M.; Essex, J. W. The ELBA Force Field for Coarse-Grained Modeling of Lipid Membranes. PLoS ONE 2011, 6, e28637.


Page 24 of 27

Page 25 of 27 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Langmuir

34. Seo, S.; Shinoda, W. SPICA Force Field for Lipid Membranes: Domain Formation Induced by Cholesterol. J. Chem. Theory Comput. 2019, 15, 762–774. 35. Zhang, Y.; Carter, J. W.; Lervik, A.; Brooks, N. J.; Seddon, J. M.; Bresme, F. Structural Organization of sterol molecules in DPPC Bilayers: a Coarse-Grained Molecular Dynamics Investigation. Soft Matt. 2016, 12, 2108-2117. 36. Yesylevskyy, S. O.; Schafer, L. V.; Sengupta, D.; Marrink, S. J. Polarizable Water Model for the Coarse-Grained MARTINI Force Field. PLoS Comput. Biol. 2010, 6, e1000810. 37. Wu, Z.; Cui, Q.; Yethiraj, A. A New Coarse-Grained Model for Water: The Importance of Electrostatic Interactions. J. Phys. Chem. B 2010, 114, 10524-10529. 38. Daily, M. D.; Olsen, B. N.; Schlesinger, P. H.; Ory, D. S.; Baker, N. A. Improved Coarse-Grained Modeling of Cholesterol-Containing Lipid Bilayers. J. Chem. Theory Comput. 2014, 10, 2137-2150. 39. Melo, M. N.; Ingólfsson, H. I.; Marrink, S. J. Parameters for MARTINI Sterols and Hopanoids based on a Virtual-Site Description. J. Chem. Phys. 2015, 143, 243152. 40. Shen, H.; Wu, Z.; Deng, M.; Wen, S.; Gao, C.; Li, S.; Wu, X. Molecular Dynamics Simulations of Ether- and Ester-linked Phospholipid Bilayers: A Comparative Study of Water Models. J. Phys. Chem. B 2018, 122, 9399-9408. 41. Shen, H.; Deng, M.; Zhang, Y. Extension of CAVS Coarse-Grained Model to Phospholipid Membranes: The Importance of Electrostatics. J. Comput. Chem. 2017, 38, 971-980. 42. Shen, H.; Deng, M.; Wu, Z.; Zhang, J.; Zhang, Y.; Gao, C.; Cen, C. Effect of Cholesterol on Membrane Dipole Potential: Atomistic and Coarse-Grained Molecular Dynamics Simulations. J. Chem. Theory Comput. 2018, 14, 37803795. 43. Andersen, O. S.; M. Fuchs, M. Potential Energy Barriers to Ion Transport within Lipid Bilayers. Studies with Tetraphnylborate. Biophys. J. 1975, 15, 795–830. 44. Brockman, H. Dipole Potential of Lipid Membranes. Chem. Phys. Lipids 1994. 73, 57-79. 45. Wang, L. Measurements and Implications of the Membrane Dipole Potential. Annu. Rev. Biochem. 2012, 81, 615–635. 46. Harder, E.; MacKerell Jr, A. D.; Roux, B. Many-Body Polarization Effects and the Membrane Dipole Potential. J. Am. Chem. Soc. 2009, 121, 2760-2751. 47. Li, H.; Chowdhary, J.; Huang, L.; He, X.; MacKerell Jr, A. D.; Roux, B. Drude Polarizable Force Field for Molecular Dynamcis Simulations of Saturated and Unsaturated Zwitteronic Lipids. J. Chem. Theory Comput. 2017, 13, 4535-4552. 48. Deng, M.; Shen, H. Coarse-Grained Model for Water Involving a Virtual Site. J. Phys. Chem. B 2016, 120, 733-739. 49. Starke-Peterkovic, T.; Turner, N.; Vitha, M. F.; Waller, M. P.; Hibbs, D. E.; Clarke, R. J. Cholesterol Effect on the Dipole Potential of Lipid Membranes. Biophys. J. 2006, 90, 4060-4070. 50. Poyry, S.; Rog, T.; Karttunen, M.; Vattulainen, I. Significance of Cholesterol Methyl Groups. J. Phys. Chem. B 2008, 112, 2922.


Langmuir 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

51. Martinez-Seara, H.; Rog, T.; Karttunen, M.; Vattulainen, I.; Reigada, R. Cholesterol Induces Specific Spatial and Orientational Order in Cholesterol/Phospholipid Membranes. PLoS One 2010, 5, e11162. 52. Reith, D.; Pütz, M.; Müller-Plathe, F. Deriving Effective Mesoscale Potentials from Atomistic Simulations. J. Comput. Chem. 2003, 24, 1624-1636. 53. Hess, B.; Kutzner, C.; van der Spoel, D.; Lindahl, E. GROMAS4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation. J. Chem. Theory Comput. 2008, 4, 435-447. 54. Martínez, L.; Andrade, R.; Birgin, E. G.; Martínez, J. M. PACKMOL: a Package for Building Initial Configurations for Molecular Dynamics Simulations. J. Comput. Chem. 2009, 30, 2157-2164. 55. Bussi, G.; Donadio, D.; Parrinello, M. Canonical Sampling through Velocity Rescaling. J. Chem. Phys. 2007, 126, 014101 56. Parrinello, M.; Rahman, A. Polymorphic Transitions in Single Crystals: A New Molecular Dynamics Method. J. Appl. Phys. 1981, 52,7182–7190. 57. Darden, T.; York, D.; Pedersen, L. Particule Mesh Ewald: An N·log(N) Method for Ewald Sums in Large Systems. J. Chem. Phys. 1993, 98, 10089-10092. 58. Hess, B. P-LINCS: A Parallel Linear Constraint Solver for Molecular Simulation. J. Chem. Theory Comput. 2008, 4, 116–122. 59. Torrie, G. M.; Valleau, J. P. Non-physical Sampling Distributions in MonteCarlo Free-Energy Estimation-Umbrella Sampling. J. Comp. Phys. 1977, 23, 187-199. 60. Kumar, S.; Bouzida, D.; Swendsen, R. H.; Kollman, P. A. ; Rosenberg, J. M. The Weighted Histogram Analysis Method for Free-Energy Calculations on Biomolecules. I. The method. J. Comput. Chem. 1992, 13, 1011–1021. 61. Shrestha, R.; Anderson, C. M.; Cardenas, A. E.; Elber, R.; Webb, L. J. Direct Measurement of the Effect of Cholesterol and 6-Ketocholestanol on the Membrane Dipole Electric Field Using Vibrational Stark Effect Spectroscopy Coupled with Molecular Dynamics Simulations. J. Phys. Chem. B 2017, 121, 3424-3436. 62. Bohinc, K.; Giner-Casares, J. J.; May, S. Analytic Model for the Dipole Potential of a Lipid Layer. J. Phys. Chem. B 2014, 118, 7568-7576. 63. Wang, L.; Bose, P. S.; Sigworth, F. J. Using Cryo-EM to Measure the Dipole Potential of a Lipid Membrane. Proc. Natl. Acad. Sci. USA. 2006, 103, 18528– 18533. 64. Zhou, F.; Schulten, K. Molecular-Dynamics Study of a Membrane Water Interface. J. Phys. Chem. 1995, 99, 2194-2207. 65. Smondyrev, A.; Berkowitz, M. United Atom Force Field for Phospholipid Membranes: Constant Pressure Molecular Dynamics Simulation of Dipalmitoylphosphatidicholine/Water System. J. Comput. Chem. 1999, 20, 531545. 66. Szabo, G. Dual Mechanism for the Action of Cholesterol on Membrane Permeability. Nature, 1974, 252, 47-49. 67. Smondyrev, A. M.; Berkovitz, M. L. Structure of Dipalmitoylphosphatidylcholine/


Page 26 of 27

Page 27 of 27 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Langmuir

Cholesterol Bilayer at Low and High Cholesterol Concentrations: Molecular Dynamics Simulation. Biophys. J. 1999, 77, 2075-2089. 68. Allen, W. J.; Lemkul, J. A.; Bevan, D. R. GridMAT-MD: A Grid-based Membrane Analysis Tool for Use With Molecular Dynamics. J. Comput. Chem. 2009, 30, 1952-1958. 69. Kapla, J.; Stevensson, B.; Dahlberg, M.; Maliniak, A. Molecular Dynamics Simulations of Membranes Composed of Glycolipids and Phospholipids. J. Phys. Chem. B 2008, 116, 244-252. 70. Steck, T. L.; Ye, J.; Lange, Y. Probing Red Cell Membrane Cholesterol Movement with Cyclodextrin. Biophys. J. 2002, 83, 2118-2125. 71. Hamilton, J. A. Fast Flip-Flop of Cholesterol and Fatty Acids in Membranes: Implications for Membrane Transport Proteins. Curr. Opin. Lipidol. 2002, 14, 263271. 72. Weiner, M. D; Feigenson, G. W. Presence and Role of Midplane Cholesterol in Lipid Bilayers Containing Registered or Antiregistered Phase Domains. J. Phys. Chem. B 2018, 122, 8193-8200. 73. Rog, T.; Stimson, L. M.; Pasenkiewicz-Gierula, M.; Vattulainen, I.; Karttunen, M. Replacing the Cholesterol Hydroxyl Group with the Ketone Group Facilitates Sterol Flip-Flop and Promotes Membrane Fluidity. J. Phys. Chem. B 2008, 112, 19461952.

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Effect of Cholesterol and 6-Ketocholestanol on Membrane Dipole

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