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1 tim 2685 \chapter{\label{chapt:lipid}LIPID MODELING}
2    
3     \section{\label{lipidSection:introduction}Introduction}
4    
5 tim 2731 Under biologically relevant conditions, phospholipids are solvated
6     in aqueous solutions at a roughly 25:1 ratio. Solvation can have a
7     tremendous impact on transport phenomena in biological membranes
8     since it can affect the dynamics of ions and molecules that are
9     transferred across membranes. Studies suggest that because of the
10     directional hydrogen bonding ability of the lipid headgroups, a
11     small number of water molecules are strongly held around the
12     different parts of the headgroup and are oriented by them with
13     residence times for the first hydration shell being around 0.5 - 1
14 tim 2786 ns\cite{Ho1992}. In the second solvation shell, some water molecules
15     are weakly bound, but are still essential for determining the
16     properties of the system. Transport of various molecular species
17     into living cells is one of the major functions of membranes. A
18     thorough understanding of the underlying molecular mechanism for
19     solute diffusion is crucial to the further studies of other related
20     biological processes. All transport across cell membranes takes
21     place by one of two fundamental processes: Passive transport is
22     driven by bulk or inter-diffusion of the molecules being transported
23     or by membrane pores which facilitate crossing. Active transport
24     depends upon the expenditure of cellular energy in the form of ATP
25     hydrolysis. As the central processes of membrane assembly,
26     translocation of phospholipids across membrane bilayers requires the
27     hydrophilic head of the phospholipid to pass through the highly
28     hydrophobic interior of the membrane, and for the hydrophobic tails
29     to be exposed to the aqueous environment\cite{Sasaki2004}. A number
30     of studies indicate that the flipping of phospholipids occurs
31 tim 2881 rapidly in the eukaryotic endoplasmic reticulum and the bacterial
32     cytoplasmic membrane via a bi-directional, facilitated diffusion
33     process requiring no metabolic energy input. Another system of
34     interest is the distribution of sites occupied by inhaled
35     anesthetics in membrane. Although the physiological effects of
36     anesthetics have been extensively studied, the controversy over
37     their effects on lipid bilayers still continues. Recent deuterium
38     NMR measurements on halothane on POPC lipid bilayers suggest the
39     anesthetics are primarily located at the hydrocarbon chain
40     region\cite{Baber1995}. However, infrared spectroscopy experiments
41     suggest that halothane in DMPC lipid bilayers lives near the
42     membrane/water interface\cite{Lieb1982}.
43 tim 2731
44 tim 2776 Molecular dynamics simulations have proven to be a powerful tool for
45     studying the functions of biological systems, providing structural,
46     thermodynamic and dynamical information. Unfortunately, much of
47     biological interest happens on time and length scales well beyond
48 tim 2844 the range of current simulation technologies. Several schemes are
49 tim 2909 introduced in this chapter to overcome these difficulties.
50 tim 2731
51 tim 2844 \section{\label{lipidSection:model}Model and Methodology}
52 tim 2685
53 tim 2776 \subsection{\label{lipidSection:SSD}The Soft Sticky Dipole Water Model}
54 tim 2685
55 tim 2776 In a typical bilayer simulation, the dominant portion of the
56     computation time will be spent calculating water-water interactions.
57     As an efficient solvent model, the Soft Sticky Dipole (SSD) water
58 tim 2807 model\cite{Chandra1999,Fennell2004} is used as the explicit solvent
59 tim 2786 in this project. Unlike other water models which have partial
60     charges distributed throughout the whole molecule, the SSD water
61     model consists of a single site which is a Lennard-Jones interaction
62     site, as well as a point dipole. A tetrahedral potential is added to
63     correct for hydrogen bonding. The following equation describes the
64     interaction between two water molecules:
65 tim 2885 \begin{equation}
66 tim 2776 V_{SSD} = V_{LJ} (r_{ij} ) + V_{dp} (r_{ij} ,\Omega _i ,\Omega _j )
67     + V_{sticky} (r_{ij} ,\Omega _i ,\Omega _j )
68 tim 2885 \label{lipidSection:ssdEquation}
69     \end{equation}
70 tim 2909 where $r_{ij}$ is the vector between molecule $i$ and molecule $j$,
71 tim 2776 $\Omega _i$ and $\Omega _j$ are the orientational degrees of freedom
72 tim 2885 for molecule $i$ and molecule $j$ respectively. The potential terms
73     in Eq.~\ref{lipidSection:ssdEquation} are given by :
74     \begin{eqnarray}
75 tim 2884 V_{LJ} (r_{ij} ) &= &4\varepsilon _{ij} \left[ {\left(
76     {\frac{{\sigma _{ij} }}{{r_{ij} }}} \right)^{12} - \left(
77     {\frac{{\sigma _{ij}
78     }}{{r_{ij} }}} \right)^6 } \right], \\
79     V_{dp} (r_{ij} ,\Omega _i ,\Omega _j ) &= &
80     \frac{|\mu_i||\mu_j|}{4\pi\epsilon_{0}r_{ij}^{3}} \biggl[
81     \hat{u}_{i} \cdot \hat{u}_{j} - 3(\hat{u}_i \cdot \hat{\mathbf{r}}_{ij}) %
82     (\hat{u}_j \cdot \hat{\mathbf{r}}_{ij}) \biggr],\\
83     V_{sticky} (r_{ij} ,\Omega _i ,\Omega _j ) &=& v_0 [s(r_{ij}
84     )w(r_{ij} ,\Omega _i ,\Omega _j ) + s'(r_{ij} )w'(r_{ij} ,\Omega _i
85 tim 2885 ,\Omega _j )]
86     \end{eqnarray}
87 tim 2776 where $v_0$ is a strength parameter, $s$ and $s'$ are cubic
88 tim 2909 switching functions and $w$ and $w'$ are responsible for the
89 tim 2776 tetrahedral potential and the short-range correction to the dipolar
90 tim 2885 interaction respectively:
91     \begin{eqnarray}
92     w(r_{ij} ,\Omega _i ,\Omega _j )& = &\sin \theta _{ij} \sin 2\theta _{ij} \cos 2\phi _{ij}, \\
93     w'(r_{ij} ,\Omega _i ,\Omega _j )& = &(\cos \theta _{ij} - 0.6)^2 (\cos \theta _{ij} + 0.8)^2 -
94     w_0.
95     \end{eqnarray}
96     Here $\theta _{ij}$ and $\phi _{ij}$ are the spherical polar angles
97 tim 2909 representing relative orientations of molecule $j$ in the body-fixed
98     frame of molecule $i$. Although the dipole-dipole and sticky
99     interactions are more mathematically complicated than Coulomb
100     interactions, the number of pair interactions is reduced
101     dramatically both because the model only contains a single-point and
102     because of the "short range" nature of the more expensive
103     interaction.
104 tim 2776
105     \subsection{\label{lipidSection:coarseGrained}The Coarse-Grained Phospholipid Model}
106    
107 tim 2781 Fig.~\ref{lipidFigure:coarseGrained} shows a schematic for our
108     coarse-grained phospholipid model. The lipid head group is modeled
109     by a linear rigid body which consists of three Lennard-Jones spheres
110     and a centrally located point-dipole. The backbone atoms in the
111     glycerol motif are modeled by Lennard-Jones spheres with dipoles.
112     Alkyl groups in hydrocarbon chains are replaced with unified
113     $\text{{\sc CH}}_2$ or $\text{{\sc CH}}_3$ atoms.
114     \begin{figure}
115     \centering
116 tim 2806 \includegraphics[width=3in]{coarse_grained.eps}
117 tim 2844 \caption[A representation of coarse-grained phospholipid model]{A
118     representation of coarse-grained phospholipid model. The lipid
119     headgroup consists of $\text{{\sc PO}}_4$ group (yellow),
120 tim 2882 $\text{{\sc NC}}_4$ group (blue) and a united C atom (gray) with a
121     dipole, while the glycerol backbone includes dipolar $\text{{\sc
122     CE}}$ (red) and $\text{{\sc CK}}$ (pink) groups. Alkyl groups in
123     hydrocarbon chains are simply represented by gray united atoms.}
124     \label{lipidFigure:coarseGrained}
125 tim 2781 \end{figure}
126    
127 tim 2776 Accurate and efficient computation of electrostatics is one of the
128     most difficult tasks in molecular modeling. Traditionally, the
129     electrostatic interaction between two molecular species is
130     calculated as a sum of interactions between pairs of point charges,
131     using Coulomb's law:
132     \[
133     V = \sum\limits_{i = 1}^{N_A } {\sum\limits_{j = 1}^{N_B }
134     {\frac{{q_i q_j }}{{4\pi \varepsilon _0 r_{ij} }}} }
135     \]
136     where $N_A$ and $N_B$ are the number of point charges in the two
137     molecular species. Originally developed to study ionic crystals, the
138 tim 2881 Ewald sum method mathematically transforms this straightforward but
139     conditionally convergent summation into two more complicated but
140     rapidly convergent sums. One summation is carried out in reciprocal
141     space while the other is carried out in real space. An alternative
142     approach is the multipole expansion, which is based on electrostatic
143     moments, such as charge (monopole), dipole, quadrupole etc.
144 tim 2776
145     Here we consider a linear molecule which consists of two point
146     charges $\pm q$ located at $ ( \pm \frac{d}{2},0)$. The
147     electrostatic potential at point $P$ is given by:
148     \[
149     \frac{1}{{4\pi \varepsilon _0 }}\left( {\frac{{ - q}}{{r_ - }} +
150     \frac{{ + q}}{{r_ + }}} \right) = \frac{1}{{4\pi \varepsilon _0
151     }}\left( {\frac{{ - q}}{{\sqrt {r^2 + \frac{{d^2 }}{4} + rd\cos
152     \theta } }} + \frac{q}{{\sqrt {r^2 + \frac{{d^2 }}{4} - rd\cos
153     \theta } }}} \right)
154     \]
155 tim 2781 \begin{figure}
156     \centering
157 tim 2806 \includegraphics[width=3in]{charge_dipole.eps}
158 tim 2844 \caption[An illustration of split-dipole
159     approximation]{Electrostatic potential due to a linear molecule
160     comprising two point charges with opposite charges. }
161     \label{lipidFigure:chargeDipole}
162 tim 2781 \end{figure}
163 tim 2776 The basic assumption of the multipole expansion is $r \gg d$ , thus,
164     $\frac{{d^2 }}{4}$ inside the square root of the denominator is
165     neglected. This is a reasonable approximation in most cases.
166     Unfortunately, in our headgroup model, the distance of charge
167 tim 2883 separation $d$ (4.63 \AA in PC headgroup) may be comparable to $r$.
168     Nevertheless, we could still assume $ \cos \theta \approx 0$ in
169     the central region of the headgroup. Using Taylor expansion and
170 tim 2776 associating appropriate terms with electric moments will result in a
171     "split-dipole" approximation:
172     \[
173     V(r) = \frac{1}{{4\pi \varepsilon _0 }}\frac{{r\mu \cos \theta
174     }}{{R^3 }}
175     \]
176     where$R = \sqrt {r^2 + \frac{{d^2 }}{4}}$ Placing a dipole at point
177     $P$ and applying the same strategy, the interaction between two
178     split-dipoles is then given by:
179     \[
180     V_{sd} (r_{ij} ,\Omega _i ,\Omega _j ) = \frac{1}{{4\pi \varepsilon
181     _0 }}\left[ {\frac{{\mu _i \cdot \mu _j }}{{R_{ij}^3 }} -
182     \frac{{3\left( {\mu _i \cdot r_{ij} } \right)\left( {\mu _i \cdot
183     r_{ij} } \right)}}{{R_{ij}^5 }}} \right]
184     \]
185     where $\mu _i$ and $\mu _j$ are the dipole moment of molecule $i$
186     and molecule $j$ respectively, $r_{ij}$ is vector between molecule
187 tim 2800 $i$ and molecule $j$, and $R_{ij}$ is given by,
188 tim 2776 \[
189     R_{ij} = \sqrt {r_{ij}^2 + \frac{{d_i^2 }}{4} + \frac{{d_j^2
190     }}{4}}
191     \]
192     where $d_i$ and $d_j$ are the charge separation distance of dipole
193     and respectively. This approximation to the multipole expansion
194     maintains the fast fall-off of the multipole potentials but lacks
195     the normal divergences when two polar groups get close to one
196 tim 2844 another. The comparision between different electrostatic
197     approximation is shown in \ref{lipidFigure:splitDipole}. Due to the
198     divergence at the central region of the headgroup introduced by
199 tim 2909 dipole-dipole approximation, we have discovered that water molecules
200     are locked into the central region in the simulation. This artifact
201     can be corrected using split-dipole approximation or other accurate
202 tim 2844 methods.
203 tim 2776 \begin{figure}
204     \centering
205 tim 2859 \includegraphics[width=\linewidth]{split_dipole.eps}
206 tim 2844 \caption[Comparison between electrostatic
207     approximation]{Electrostatic potential map for two pairs of charges
208     with different alignments: (a) illustration of different alignments;
209     (b) charge-charge interaction; (c) dipole-dipole approximation; (d)
210     split-dipole approximation.} \label{lipidFigure:splitDipole}
211 tim 2776 \end{figure}
212    
213 tim 2685 \section{\label{lipidSection:resultDiscussion}Results and Discussion}
214 tim 2776
215     \subsection{One Lipid in Sea of Water Molecules}
216    
217 tim 2881 To tune our parameters without the inter-headgroup interactions,
218     atomistic models of one lipid (DMPC or DLPE) in sea of water
219     molecules (TIP3P) were built and studied using atomistic molecular
220     dynamics. The simulation was analyzed using a set of radial
221     distribution functions, which give the probability of finding a pair
222     of molecular species a distance apart, relative to the probability
223     expected for a completely random distribution function at the same
224 tim 2905 density
225     \begin{eqnarray}
226     g_{AB} (r) & = & \frac{1}{{\rho _B }}\frac{1}{{N_A }} <
227     \sum\limits_{i
228     \in A} {\sum\limits_{j \in B} {\delta (r - r_{ij} )} } >, \\
229     g_{AB} (r,\cos \theta ) & = & \frac{1}{{\rho _B }}\frac{1}{{N_A }} <
230 tim 2776 \sum\limits_{i \in A} {\sum\limits_{j \in B} {\delta (r - r_{ij} )}
231 tim 2905 } \delta (\cos \theta _{ij} - \cos \theta ) >.
232     \end{eqnarray}
233 tim 2844 From Fig.~\ref{lipidFigure:PCFAtom}, we can identify the first
234 tim 2883 solvation shell (3.5 \AA) and the second solvation shell (5.0 \AA)
235     from both plots. However, the corresponding orientations are
236 tim 2844 different. In DLPE, water molecules prefer to sit around $\text{{\sc
237     NH}}_3$ group due to the hydrogen bonding. In contrast, because of
238     the hydrophobic effect of the $ {\rm{N(CH}}_{\rm{3}}
239     {\rm{)}}_{\rm{3}} $ group, the preferred position of water molecules
240     in DMPC is around the $\text{{\sc PO}}_4$ Group. When the water
241     molecules are far from the headgroup, the distribution of the two
242     angles should be uniform. The correlation close to center of the
243 tim 2881 headgroup dipole in both plots tells us that in the closely-bound
244 tim 2844 region, the dipoles of the water molecules are preferentially
245     anti-aligned with the dipole of headgroup. When the water molecules
246     are far from the headgroup, the distribution of the two angles
247     should be uniform. The correlation close to center of the headgroup
248     dipole in both plots tell us that in the closely-bound region, the
249     dipoles of the water molecules are preferentially aligned with the
250     dipole of headgroup.
251 tim 2776 \begin{figure}
252     \centering
253     \includegraphics[width=\linewidth]{g_atom.eps}
254 tim 2844 \caption[The pair correlation functions for atomistic models]{The
255     pair correlation functions for atomistic models: (a)$g(r,\cos \theta
256     )$ for DMPC; (b) $g(r,\cos \theta )$ for DLPE; (c)$g(r,\cos \omega
257     )$ for DMPC; (d)$g(r,\cos \omega )$ for DLPE; (e)$g(\cos \theta,\cos
258     \omega)$ for DMPC; (f)$g(\cos \theta,\cos \omega)$ for DMLPE.}
259 tim 2776 \label{lipidFigure:PCFAtom}
260     \end{figure}
261    
262     The initial configurations of coarse-grained systems are constructed
263     from the previous atomistic ones. The parameters for the
264     coarse-grained model in Table~\ref{lipidTable:parameter} are
265     estimated and tuned using isothermal-isobaric molecular dynamics.
266     Pair distribution functions calculated from coarse-grained models
267     preserve the basic characteristics of the atomistic simulations. The
268     water density, measured in a head-group-fixed reference frame,
269     surrounding two phospholipid headgroups is shown in
270     Fig.~\ref{lipidFigure:PCFCoarse}. It is clear that the phosphate end
271     in DMPC and the amine end in DMPE are the two most heavily solvated
272     atoms.
273     \begin{figure}
274     \centering
275     \includegraphics[width=\linewidth]{g_coarse.eps}
276 tim 2844 \caption[The pair correlation functions for coarse-grained
277     models]{The pair correlation functions for coarse-grained models:
278     (a)$g(r,\cos \theta )$ for DMPC; (b) $g(r,\cos \theta )$ for DLPE.}
279 tim 2776 \label{lipidFigure:PCFCoarse}
280     \end{figure}
281     \begin{figure}
282     \centering
283     \includegraphics[width=\linewidth]{EWD_coarse.eps}
284 tim 2847 \caption[Excess water density of coarse-grained
285     phospholipids]{Excess water density of coarse-grained
286     phospholipids.} \label{lipidFigure:EWDCoarse}
287 tim 2776 \end{figure}
288    
289     \begin{table}
290 tim 2889 \caption{THE PARAMETERS FOR COARSE-GRAINED PHOSPHOLIPIDS}
291 tim 2776 \label{lipidTable:parameter}
292     \begin{center}
293 tim 2905 \begin{tabular}{lccccc}
294 tim 2776 \hline
295     % after \\: \hline or \cline{col1-col2} \cline{col3-col4} ...
296     Atom type & Mass & $\sigma$ & $\epsilon$ & charge & Dipole \\
297 tim 2905 \hline
298 tim 2776 $\text{{\sc CH}}_2$ & 14.03 & 3.95 & 0.0914 & 0 & 0 \\
299     $\text{{\sc CH}}_3$ & 15.04 & 3.75 & 0.195 & 0 & 0 \\
300 tim 2781 $\text{{\sc CE}}$ & 28.01 & 3.427& 0.294 & 0 & 1.693 \\
301 tim 2776 $\text{{\sc CK}}$ & 28.01 & 3.592& 0.311 & 0 & 2.478 \\
302     $\text{{\sc PO}}_4$ & 108.995& 3.9 & 1.88 & -1& 0 \\
303     $\text{{\sc HDP}}$ & 14.03 & 4.0 & 0.13 & 0 & 0 \\
304     $\text{{\sc NC}}_4$ & 73.137 & 4.9 & 0.88 & +1& 0 \\
305     $\text{{\sc NH}}_3$ & 17.03 & 3.25 & 0.17 & +1& 0\\
306     \hline
307     \end{tabular}
308     \end{center}
309     \end{table}
310    
311     \subsection{Bilayer Simulations Using Coarse-grained Model}
312    
313     A bilayer system consisting of 128 DMPC lipids and 3655 water
314 tim 2844 molecules has been constructed from an atomistic coordinate file.
315     The MD simulation is performed at constant temperature, T = 300K,
316     and constant pressure, p = 1 atm, and consisted of an equilibration
317     period of 2 ns. During the equilibration period, the system was
318     initially simulated at constant volume for 1 ns. Once the system was
319     equilibrated at constant volume, the cell dimensions of the system
320 tim 2881 was relaxed by performing under NPT conditions using Nos\'{e}-Hoover
321 tim 2844 extended system isothermal-isobaric dynamics. After equilibration,
322     different properties were evaluated over a production run of 5 ns.
323 tim 2776 \begin{figure}
324     \centering
325     \includegraphics[width=\linewidth]{bilayer.eps}
326     \caption[Image of a coarse-grained bilayer system]{A coarse-grained
327     bilayer system consisting of 128 DMPC lipids and 3655 SSD water
328     molecules.}
329     \label{lipidFigure:bilayer}
330     \end{figure}
331    
332 tim 2819 \subsubsection{\textbf{Electron Density Profile (EDP)}}
333 tim 2776
334     Assuming a gaussian distribution of electrons on each atomic center
335     with a variance estimated from the size of the van der Waals radius,
336     the EDPs which are proportional to the density profiles measured
337     along the bilayer normal obtained by x-ray scattering experiment,
338 tim 2786 can be expressed by\cite{Tu1995}
339 tim 2776 \begin{equation}
340     \rho _{x - ray} (z)dz \propto \sum\limits_{i = 1}^N {\frac{{n_i
341 tim 2909 }}{V}\frac{1}{{\sqrt {2\pi \sigma _i ^2 } }}e^{ - (z - z_i )^2
342     /2\sigma _i ^2 } dz},
343 tim 2776 \end{equation}
344 tim 2909 where $\sigma _i$ is the variance equal to the van der Waals radius,
345 tim 2776 $n_i$ is the atomic number of site $i$ and $V$ is the volume of the
346     slab between $z$ and $z+dz$ . The highest density of total EDP
347     appears at the position of lipid-water interface corresponding to
348     headgroup, glycerol, and carbonyl groups of the lipids and the
349     distribution of water locked near the head groups, while the lowest
350     electron density is in the hydrocarbon region. As a good
351     approximation to the thickness of the bilayer, the headgroup spacing
352     , is defined as the distance between two peaks in the electron
353 tim 2883 density profile, calculated from our simulations to be 34.1 \AA.
354 tim 2776 This value is close to the x-ray diffraction experimental value 34.4
355 tim 2883 \AA\cite{Petrache1998}.
356 tim 2776
357     \begin{figure}
358     \centering
359     \includegraphics[width=\linewidth]{electron_density.eps}
360     \caption[The density profile of the lipid bilayers]{Electron density
361     profile along the bilayer normal. The water density is shown in red,
362     the density due to the headgroups in green, the glycerol backbone in
363     brown, $\text{{\sc CH}}_2$ in yellow, $\text{{\sc CH}}_3$ in cyan,
364     and total density due to DMPC in blue.}
365     \label{lipidFigure:electronDensity}
366     \end{figure}
367    
368 tim 2819 \subsubsection{\textbf{$\text{S}_{\text{{\sc cd}}}$ Order Parameter}}
369 tim 2776
370     Measuring deuterium order parameters by NMR is a useful technique to
371     study the orientation of hydrocarbon chains in phospholipids. The
372     order parameter tensor $S$ is defined by:
373     \begin{equation}
374     S_{ij} = \frac{1}{2} < 3\cos \theta _i \cos \theta _j - \delta
375     _{ij} >
376     \end{equation}
377 tim 2909 where $\theta _i$ is the angle between the $i$th molecular axis and
378 tim 2776 the bilayer normal ($z$ axis). The brackets denote an average over
379 tim 2909 time and lipid molecules. The molecular axes are defined:
380 tim 2776 \begin{itemize}
381     \item $\mathbf{\hat{z}}$ is the vector from $C_{n-1}$ to $C_{n+1}$.
382     \item $\mathbf{\hat{y}}$ is the vector that is perpendicular to $z$ and
383     in the plane through $C_{n-1}$, $C_{n}$, and $C_{n+1}$.
384     \item $\mathbf{\hat{x}}$ is the vector perpendicular to
385     $\mathbf{\hat{y}}$ and $\mathbf{\hat{z}}$.
386     \end{itemize}
387 tim 2909 In our coarse-grained model, although there are no explicit
388     hydrogens, the order parameter can still be written in terms of
389     carbon ordering at each point of the chain\cite{Egberts1988}
390 tim 2776 \begin{equation}
391     S_{ij} = \frac{1}{2} < 3\cos \theta _i \cos \theta _j - \delta
392     _{ij} >.
393     \end{equation}
394    
395     Fig.~\ref{lipidFigure:Scd} shows the order parameter profile
396     calculated for our coarse-grained DMPC bilayer system at 300K. Also
397 tim 2786 shown are the experimental data of Tu\cite{Tu1995}. The fact that
398 tim 2776 $\text{S}_{\text{{\sc cd}}}$ order parameters calculated from
399     simulation are higher than the experimental ones is ascribed to the
400     assumption of the locations of implicit hydrogen atoms which are
401     fixed in coarse-grained models at positions relative to the CC
402     vector.
403    
404     \begin{figure}
405     \centering
406     \includegraphics[width=\linewidth]{scd.eps}
407     \caption[$\text{S}_{\text{{\sc cd}}}$ order parameter]{A comparison
408     of $|\text{S}_{\text{{\sc cd}}}|$ between coarse-grained model
409 tim 2845 (blue) and DMPC\cite{Petrache2000} (black) near 300~K.}
410 tim 2776 \label{lipidFigure:Scd}
411     \end{figure}
412 tim 2781
413     %\subsection{Bilayer Simulations Using Gay-Berne Ellipsoid Model}
414 tim 2844
415     \section{\label{lipidSection:Conclusion}Conclusion}
416    
417 tim 2881 Atomistic simulations have been used in this study to determine the
418 tim 2844 preferred orientation and location of water molecules relative to
419     the location and orientation of the PC and PE lipid headgroups.
420 tim 2881 Based on the results from our all-atom simulations, we developed a
421     simple coarse-grained model which captures the essential features of
422     the headgroup solvation which is crucial to transport process in
423     membrane system. In addition, the model has been explored in a
424     bilayer system was shown to have reasonable electron density
425     profiles, $\text{S}_{\text{{\sc cd}}}$ order parameter and other
426     structural properties. The accuracy of this model is achieved by
427     matching atomistic result. It is also easy to represent different
428     phospholipids by changing a few parameters of the model. Another
429 tim 2844 important characteristic of this model distinguishing itself from
430     other models\cite{Goetz1998,Marrink2004} is the computational speed
431 tim 2881 gained by introducing a short range electrostatic approximation.
432 tim 2844 Further studies of this system using z-constraint method could
433     extend the time length of the simulations to study transport
434     phenomena in large-scale membrane systems.