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4  
5   \section{\label{lipidSec:Intro}Introduction}
6  
7 < In the past 10 years, computer speeds have allowed for the atomistic
8 < simulation of phospholipid bilayers.  These simulations have ranged
9 < from simulation of the gel phase ($L_{\beta}$) of
10 < dipalmitoylphosphatidylcholine (DPPC), \cite{Lindahl:2000} to the
7 > In the past 10 years, increasing computer speeds have allowed for the
8 > atomistic simulation of phospholipid bilayers for increasingly
9 > relevant lenghths of time.  These simulations have ranged from
10 > simulation of the gel phase ($L_{\beta}$) of
11 > dipalmitoylphosphatidylcholine (DPPC),\cite{lindahl00} to the
12   spontaneous aggregation of DPPC molecules into fluid phase
13 < ($L_{\alpha}$ bilayers. \cite{Marrinck:2001} With the exception of a
14 < few ambitious
15 < simulations,\cite{Marrinch:2001b,Marrinck:2002,Lindahl:2000} most
16 < investigations are limited to 64 to 256
17 < phospholipids.\cite{Lindal:2000,Sum:2003,Venable:2000,Gomez:2003,Smondyrev:1999,Marrinck:2001a}
18 < This is due to the expense of the computer calculations involved when
19 < performing these simulations.  To properly hydrate a bilayer, one
13 > ($L_{\alpha}$) bilayers.\cite{marrink01} With the exception of a few
14 > ambitious
15 > simulations,\cite{marrink01:undulation,marrink:2002,lindahl00} most
16 > investigations are limited to a range of 64 to 256
17 > phospholipids.\cite{lindahl00,sum:2003,venable00,gomez:2003,smondyrev:1999,marrink01}
18 > The expense of the force calculations involved when performing these
19 > simulations limits the system size. To properly hydrate a bilayer, one
20   typically needs 25 water molecules for every lipid, bringing the total
21   number of atoms simulated to roughly 8,000 for a system of 64 DPPC
22 < molecules. Added to the difficluty is the electrostatic nature of the
23 < phospholipid head groups and water, requiring the computationally
24 < expensive Ewald sum or its slightly faster derivative particle mesh
25 < Ewald sum.\cite{Nina:2002,Norberg:2000,Patra:2003} These factors all
26 < limit the potential size and time lenghts of bilayer simulations.
22 > molecules. Added to the difficulty is the electrostatic nature of the
23 > phospholipid head groups and water, requiring either the
24 > computationally expensive Ewald sum or the faster, particle mesh Ewald
25 > sum.\cite{nina:2002,norberg:2000,patra:2003} These factors all limit
26 > the system size and time scales of bilayer simulations.
27  
28   Unfortunately, much of biological interest happens on time and length
29 < scales unfeasible with current simulation. One such example is the
30 < observance of a ripple phase ($P_{\beta'}$) between the $L_{\beta}$
31 < and $L_{\alpha}$ phases of certain phospholipid
32 < bilayers.\cite{Katsaras:2000,Sengupta:2000} These ripples are shown to
33 < have periodicity on the order of 100-200~$\mbox{\AA}$. A simulation on
34 < this length scale would have approximately 1,300 lipid molecules with
35 < an additional 25 water molecules per lipid to fully solvate the
36 < bilayer. A simulation of this size is impractical with current
37 < atomistic models.
29 > scales well beyond the range of current simulation technology. One
30 > such example is the observance of a ripple phase
31 > ($P_{\beta^{\prime}}$) between the $L_{\beta}$ and $L_{\alpha}$ phases
32 > of certain phospholipid bilayers.\cite{katsaras00,sengupta00} These
33 > ripples are shown to have periodicity on the order of
34 > 100-200~$\mbox{\AA}$. A simulation on this length scale would have
35 > approximately 1,300 lipid molecules with an additional 25 water
36 > molecules per lipid to fully solvate the bilayer. A simulation of this
37 > size is impractical with current atomistic models.
38  
39 < Another class of simulations to consider, are those dealing with the
40 < diffusion of molecules through a bilayer.  Due to the fluid-like
41 < properties of a lipid membrane, not all diffusion across the membrane
42 < happens at pores.  Some molecules of interest may incorporate
43 < themselves directly into the membrane.  Once here, they may possess an
44 < appreciable waiting time (on the order of 10's to 100's of
45 < nanoseconds) within the bilayer.  Such long simulation times are
46 < difficulty to obtain when integrating the system with atomistic
46 < detail.
39 > The time and length scale limitations are most striking in transport
40 > phenomena.  Due to the fluid-like properties of a lipid membrane, not
41 > all diffusion across the membrane happens at pores.  Some molecules of
42 > interest may incorporate themselves directly into the membrane.  Once
43 > here, they may possess an appreciable waiting time (on the order of
44 > 10's to 100's of nanoseconds) within the bilayer. Such long simulation
45 > times are nearly impossible to obtain when integrating the system with
46 > atomistic detail.
47  
48 < Addressing these issues, several schemes have been proposed.  One
49 < approach by Goetz and Liposky\cite{Goetz:1998} is to model the entire
48 > To address these issues, several schemes have been proposed.  One
49 > approach by Goetz and Liposky\cite{goetz98} is to model the entire
50   system as Lennard-Jones spheres. Phospholipids are represented by
51   chains of beads with the top most beads identified as the head
52   atoms. Polar and non-polar interactions are mimicked through
53   attractive and soft-repulsive potentials respectively.  A similar
54 < model proposed by Marrinck \emph{et. al.}\cite{Marrinck:2004}~ uses a
54 > model proposed by Marrinck \emph{et. al}.\cite{marrink04}~uses a
55   similar technique for modeling polar and non-polar interactions with
56   Lennard-Jones spheres. However, they also include charges on the head
57   group spheres to mimic the electrostatic interactions of the
# Line 63 | Line 63 | Lennard-Jones spheres for the head and tail groups of
63   interactions than the previous two models, while still balancing the
64   need for simplifications over atomistic detail.  The model uses
65   Lennard-Jones spheres for the head and tail groups of the
66 < phopholipids, allowing for the ability to scale the parameters to
66 > phospholipids, allowing for the ability to scale the parameters to
67   reflect various sized chain configurations while keeping the number of
68   interactions small.  What sets this model apart, however, is the use
69 < of dipoles to represent the electrosttaic nature of the
69 > of dipoles to represent the electrostatic nature of the
70   phospholipids. The dipole electrostatic interaction is shorter range
71 < than coulombic ($\frac{1}{r^3}$ versus $\frac{1}{r}$), eliminating the
72 < need for a costly Ewald sum.  
71 > than Coulombic ($\frac{1}{r^3}$ versus $\frac{1}{r}$), and eliminates
72 > the need for a costly Ewald sum.
73  
74   Another key feature of this model, is the use of a dipolar water model
75 < to represent the solvent. The soft sticky dipole ({\scssd})
76 < water \cite{Liu:1996a} relies on the dipole for long range
77 < electrostatic effects, butalso contains a short range correction for
78 < hydrogen bonding. In this way the systems in this research mimic the
79 < entropic contribution to the hydrophobic effect due to hydrogen-bond
80 < network deformation around a non-polar entity, \emph{i.e.}~ the
81 < phospholipid.
75 > to represent the solvent. The soft sticky dipole ({\sc ssd}) water
76 > \cite{liu96:new_model} relies on the dipole for long range electrostatic
77 > effects, but also contains a short range correction for hydrogen
78 > bonding. In this way the systems in this research mimic the entropic
79 > contribution to the hydrophobic effect due to hydrogen-bond network
80 > deformation around a non-polar entity, \emph{i.e.}~the phospholipid
81 > molecules.
82  
83   The following is an outline of this chapter.
84 < Sec.~\ref{lipoidSec:Methods} is an introduction to the lipid model
85 < used in these simulations.  As well as clarification about the water
86 < model and integration techniques.  The various simulation setups
87 < explored in this research are outlined in
88 < Sec.~\ref{lipidSec:ExpSetup}. Sec.~\ref{lipidSec:Results} and
89 < Sec.~\ref{lipidSec:Discussion} give a summary of the results and
90 < interpretation of those results respectively.  Finally, the
91 < conclusions of this chapter are presented in
92 < Sec.~\ref{lipidSec:Conclusion}.
84 > Sec.~\ref{lipidSec:Methods} is an introduction to the lipid model used
85 > in these simulations, as well as clarification about the water model
86 > and integration techniques. The various simulations explored in this
87 > research are outlined in
88 > Sec.~\ref{lipidSec:ExpSetup}. Sec.~\ref{lipidSec:resultsDis} gives a
89 > summary and interpretation of the results.  Finally, the conclusions
90 > of this chapter are presented in Sec.~\ref{lipidSec:Conclusion}.
91  
92   \section{\label{lipidSec:Methods}Methods}
93  
96
97
94   \subsection{\label{lipidSec:lipidModel}The Lipid Model}
95  
96   \begin{figure}
97 <
98 < \caption{Schematic diagram of the single chain phospholipid model}
99 <
97 > \centering
98 > \includegraphics[width=\linewidth]{twoChainFig.eps}
99 > \caption[The two chained lipid model]{Schematic diagram of the double chain phospholipid model. The head group (in red) has a point dipole, $\boldsymbol{\mu}$, located at its center of mass. The two chains are eight methylene groups in length.}
100   \label{lipidFig:lipidModel}
105
101   \end{figure}
102  
103   The phospholipid model used in these simulations is based on the
104   design illustrated in Fig.~\ref{lipidFig:lipidModel}.  The head group
105   of the phospholipid is replaced by a single Lennard-Jones sphere of
106 < diameter $fix$, with $fix$ scaling the well depth of its van der Walls
107 < interaction.  This sphere also contains a single dipole of magnitude
108 < $fix$, where $fix$ can be varied to mimic the charge separation of a
106 > diameter $\sigma_{\text{head}}$, with $\epsilon_{\text{head}}$ scaling
107 > the well depth of its van der Walls interaction.  This sphere also
108 > contains a single dipole of magnitude $|\boldsymbol{\mu}|$, where
109 > $|\boldsymbol{\mu}|$ can be varied to mimic the charge separation of a
110   given phospholipid head group.  The atoms of the tail region are
111 < modeled by unified atom beads.  They are free of partial charges or
112 < dipoles, containing only Lennard-Jones interaction sites at their
113 < centers of mass.  As with the head groups, their potentials can be
114 < scaled by $fix$ and $fix$.
111 > modeled by beads representing multiple methyl groups.  They are free
112 > of partial charges or dipoles, and contain only Lennard-Jones
113 > interaction sites at their centers of mass.  As with the head groups,
114 > their potentials can be scaled by $\sigma_{\text{tail}}$ and
115 > $\epsilon_{\text{tail}}$.
116  
117   The long range interactions between lipids are given by the following:
118   \begin{equation}
119 < EQ Here
119 > V_{\text{LJ}}(r_{ij}) =
120 >        4\epsilon_{ij} \biggl[
121 >        \biggl(\frac{\sigma_{ij}}{r_{ij}}\biggr)^{12}
122 >        - \biggl(\frac{\sigma_{ij}}{r_{ij}}\biggr)^{6}
123 >        \biggr]
124   \label{lipidEq:LJpot}
125   \end{equation}
126   and
127   \begin{equation}
128 < EQ Here
128 > V_{\text{dipole}}(\mathbf{r}_{ij},\boldsymbol{\Omega}_{i},
129 >        \boldsymbol{\Omega}_{j}) = \frac{|\mu_i||\mu_j|}{4\pi\epsilon_{0}r_{ij}^{3}} \biggl[
130 >        \boldsymbol{\hat{u}}_{i} \cdot \boldsymbol{\hat{u}}_{j}
131 >        -
132 >        3(\boldsymbol{\hat{u}}_i \cdot \mathbf{\hat{r}}_{ij}) %
133 >                (\boldsymbol{\hat{u}}_j \cdot \mathbf{\hat{r}}_{ij} \biggr]
134   \label{lipidEq:dipolePot}
135   \end{equation}
136   Where $V_{\text{LJ}}$ is the Lennard-Jones potential and
# Line 133 | Line 139 | In $V_{\text{dipole}}$, $\mathbf{r}_{ij}$ is the vecto
139   parameters which scale the length and depth of the interaction
140   respectively, and $r_{ij}$ is the distance between beads $i$ and $j$.
141   In $V_{\text{dipole}}$, $\mathbf{r}_{ij}$ is the vector starting at
142 < bead$i$ and pointing towards bead $j$.  Vectors $\mathbf{\Omega}_i$
142 > bead $i$ and pointing towards bead $j$.  Vectors $\mathbf{\Omega}_i$
143   and $\mathbf{\Omega}_j$ are the orientational degrees of freedom for
144   beads $i$ and $j$.  $|\mu_i|$ is the magnitude of the dipole moment of
145   $i$, and $\boldsymbol{\hat{u}}_i$ is the standard unit orientation
146 < vector of $\boldsymbol{\Omega}_i$.
146 > vector rotated with euler angles: $\boldsymbol{\Omega}_i$.
147  
148 < The model also allows for the bonded interactions of bonds, bends, and
149 < torsions.  The bonds between two beads on a chain are of fixed length,
150 < and are maintained according to the {\sc rattle} algorithm. \cite{fix}
148 > The model also allows for the bonded interactions bends, and torsions.
149 > The bond between two beads on a chain is of fixed length, and is
150 > maintained according to the {\sc rattle} algorithm.\cite{andersen83}
151   The bends are subject to a harmonic potential:
152   \begin{equation}
153 < eq here
153 > V_{\text{bend}}(\theta) = k_{\theta}( \theta - \theta_0 )^2
154   \label{lipidEq:bendPot}
155   \end{equation}
156 < where $fix$ scales the strength of the harmonic well, and $fix$ is the
157 < angle between bond vectors $fix$ and $fix$.  The torsion potential is
158 < given by:
156 > where $k_{\theta}$ scales the strength of the harmonic well, and
157 > $\theta$ is the angle between bond vectors
158 > (Fig.~\ref{lipidFig:lipidModel}). In addition, we have placed a
159 > ``ghost'' bend on the phospholipid head. The ghost bend adds a
160 > potential to keep the dipole pointed along the bilayer surface, where
161 > $\theta$ is now the angle the dipole makes with respect to the {\sc
162 > head}-$\text{{\sc ch}}_2$ bond vector
163 > (Fig.~\ref{lipidFig:ghostBend}). The torsion potential is given by:
164   \begin{equation}
165 < eq here
165 > V_{\text{torsion}}(\phi) =  
166 >        k_3 \cos^3 \phi + k_2 \cos^2 \phi + k_1 \cos \phi + k_0
167   \label{lipidEq:torsionPot}
168   \end{equation}
169   Here, the parameters $k_0$, $k_1$, $k_2$, and $k_3$ fit the cosine
170   power series to the desired torsion potential surface, and $\phi$ is
171 < the angle between bondvectors $fix$ and $fix$ along the vector $fix$
172 < (see Fig.:\ref{lipidFig:lipidModel}).  Long range interactions such as
173 < the Lennard-Jones potential are excluded for bead pairs involved in
174 < the same bond, bend, or torsion.  However, internal interactions not
171 > the angle the two end atoms have rotated about the middle bond
172 > (Fig.:\ref{lipidFig:lipidModel}).  Long range interactions such as the
173 > Lennard-Jones potential are excluded for atom pairs involved in the
174 > same bond, bend, or torsion.  However, internal interactions not
175   directly involved in a bonded pair are calculated.
176  
177 + \begin{figure}
178 + \centering
179 + \includegraphics[width=\linewidth]{ghostBendFig.eps}
180 + \caption[Depiction of the ``ghost'' bend]{The ``ghost'' bend is a bend potential added to constrain the motion of the dipole on the {\sc head} group. The potential follows Eq.~\ref{lipidEq:bendPot} where $\theta$ is now the angle that the dipole makes with the {\sc head}-$\text{{\sc ch}}_2$ bond vector.}
181 + \label{lipidFig:ghostBend}
182 + \end{figure}
183 +
184   All simulations presented here use a two chained lipid as pictured in
185 < Fig.~\ref{lipidFig:twochain}.  The chains are both eight beads long,
185 > Fig.~\ref{lipidFig:lipidModel}.  The chains are both eight beads long,
186   and their mass and Lennard Jones parameters are summarized in
187   Table~\ref{lipidTable:tcLJParams}. The magnitude of the dipole moment
188   for the head bead is 10.6~Debye, and the bend and torsion parameters
189 < are summarized in Table~\ref{lipidTable:teBTParams}.
189 > are summarized in Table~\ref{lipidTable:tcBendParams} and
190 > \ref{lipidTable:tcTorsionParams}.
191  
192 < \section{label{lipidSec:furtherMethod}Further Methodology}
192 > \begin{table}
193 > \caption{The Lennard Jones Parameters for the two chain phospholipids.}
194 > \label{lipidTable:tcLJParams}
195 > \begin{center}
196 > \begin{tabular}{|l|c|c|c|}
197 > \hline
198 >     & mass (amu) & $\sigma$($\mbox{\AA}$)  & $\epsilon$ (kcal/mol) \\ \hline
199 > {\sc head} & 72  & 4.0 & 0.185 \\ \hline
200 > {\sc ch}\cite{Siepmann1998} & 13.02 & 4.0 & 0.0189 \\ \hline
201 > $\text{{\sc ch}}_2$\cite{Siepmann1998} & 14.03 & 3.95 & 0.18 \\ \hline
202 > $\text{{\sc ch}}_3$\cite{Siepmann1998} & 15.04 & 3.75 & 0.25 \\ \hline
203 > {\sc ssd}\cite{liu96:new_model} & 18.03 & 3.051 & 0.152 \\ \hline
204 > \end{tabular}
205 > \end{center}
206 > \end{table}
207  
208 + \begin{table}
209 + \caption[Bend Parameters for the two chain phospholipids]{Bend Parameters for the two chain phospholipids. All alkane parameters are based off of those from TraPPE.\cite{Siepmann1998}}
210 + \label{lipidTable:tcBendParams}
211 + \begin{center}
212 + \begin{tabular}{|l|c|c|}
213 + \hline
214 +   & $k_{\theta}$ ( kcal/($\text{mol deg}^2$) ) & $\theta_0$ ( deg ) \\ \hline
215 + {\sc ghost}-{\sc head}-$\text{{\sc ch}}_2$ & 0.00177 & 129.78 \\ \hline
216 + $x$-{\sc ch}-$y$ & 58.84 & 112.0 \\ \hline
217 + $x$-$\text{{\sc ch}}_2$-$y$ & 58.84 & 114.0 \\ \hline
218 + \end{tabular}
219 + \end{center}
220 + \end{table}
221 +
222 + \begin{table}
223 + \caption[Torsion Parameters for the two chain phospholipids]{Torsion Parameters for the two chain phospholipids. Alkane parameters based on TraPPE.\cite{Siepmann1998}}
224 + \label{lipidTable:tcTorsionParams}
225 + \begin{center}
226 + \begin{tabular}{|l|c|c|c|c|}
227 + \hline
228 + All are in kcal/mol $\rightarrow$ & $k_3$ & $k_2$ & $k_1$ & $k_0$ \\ \hline
229 + $x$-{\sc ch}-$y$-$z$ & 3.3254 & -0.4215 & -1.686 & 1.1661 \\ \hline
230 + $x$-$\text{{\sc ch}}_2$-$\text{{\sc ch}}_2$-$y$ & 5.9602 & -0.568 & -3.802 & 2.1586 \\ \hline
231 + \end{tabular}
232 + \end{center}
233 + \end{table}
234 +
235 +
236 + \section{\label{lipidSec:furtherMethod}Further Methodology}
237 +
238   As mentioned previously, the water model used throughout these
239 < simulations was the {\scssd} model of
240 < Ichiye.\cite{liu:1996a,Liu:1996b,Chandra:1999} A discussion of the
241 < model can be found in Sec.~\ref{oopseSec:SSD}. As for the integration
242 < of the equations of motion, all simulations were performed in an
243 < orthorhombic periodic box with a thermostat on velocities, and an
244 < independent barostat on each cartesian axis $x$, $y$, and $z$.  This
245 < is the $\text{NPT}_{xyz}$. ensemble described in Sec.~\ref{oopseSec:Ensembles}.
239 > simulations was the {\sc ssd} model of
240 > Ichiye.\cite{liu96:new_model,liu96:monte_carlo,chandra99:ssd_md} A
241 > discussion of the model can be found in Sec.~\ref{oopseSec:SSD}. As
242 > for the integration of the equations of motion, all simulations were
243 > performed in an orthorhombic periodic box with a thermostat on
244 > velocities, and an independent barostat on each Cartesian axis $x$,
245 > $y$, and $z$.  This is the $\text{NPT}_{xyz}$. ensemble described in
246 > Sec.~\ref{oopseSec:Ensembles}.
247  
248  
249   \subsection{\label{lipidSec:ExpSetup}Experimental Setup}
# Line 200 | Line 265 | included the number of waters each lipid would displac
265   estimate for the number of waters each lipid would displace in a
266   simulation box. A target number of waters was then defined which
267   included the number of waters each lipid would displace, the number of
268 < waters desired to solvate each lipid, and a fudge factor to pad the
269 < initialization.
268 > waters desired to solvate each lipid, and a factor to pad the
269 > initial box with a few extra water molecules.
270  
271   Next, a cubic simulation box was created that contained at least the
272   target number of waters in an FCC lattice (the lattice was for ease of
273   placement).  What followed was a RSA simulation similar to those of
274   Chapt.~\ref{chapt:RSA}. The lipids were sequentially given a random
275   position and orientation within the box.  If a lipid's position caused
276 < atomic overlap with any previously adsorbed lipid, its position and
277 < orientation were rejected, and a new random adsorption site was
276 > atomic overlap with any previously placed lipid, its position and
277 > orientation were rejected, and a new random placement site was
278   attempted. The RSA simulation proceeded until all phospholipids had
279 < been adsorbed.  After adsorption, all water molecules with locations
280 < that overlapped with the atomic coordinates of the lipids were
281 < removed.
279 > been adsorbed.  After placement of all lipid molecules, water
280 > molecules with locations that overlapped with the atomic coordinates
281 > of the lipids were removed.
282  
283 < Finally, water molecules were removed one by one at random until the
284 < desired number of waters per lipid was reached.  The typical low final
285 < density for these initial configurations was not a problem, as the box
286 < would shrink to an appropriate size within the first 50~ps of a
287 < simulation in the $\text{NPT}_{xyz}$ ensemble.
283 > Finally, water molecules were removed at random until the desired
284 > number of waters per lipid was reached.  The typical low final density
285 > for these initial configurations was not a problem, as the box shrinks
286 > to an appropriate size within the first 50~ps of a simulation in the
287 > $\text{NPT}_{xyz}$ ensemble.
288  
289 < \subsection{\label{lipidSec:Configs}The simulation configurations}
289 > \subsection{\label{lipidSec:Configs}Configurations}
290  
291 < Table ~\ref{lipidTable:simNames} summarizes the names and important
292 < details of the simulations.  The B set of simulations were all started
293 < in an ordered bilayer and observed over a period of 10~ns. Simulution
294 < RL was integrated for approximately 20~ns starting from a random
295 < configuration as an example of spontaneous bilayer aggregation.
296 < Lastly, simulation RH was also started from a random configuration,
297 < but with a lesser water content and higher temperature to show the
298 < spontaneous aggregation of an inverted hexagonal lamellar phase.
291 > The first class of simulations were started from ordered
292 > bilayers. They were all configurations consisting of 60 lipid
293 > molecules with 30 lipids on each leaf, and were hydrated with 1620
294 > {\sc ssd} molecules. The original configuration was assembled
295 > according to Sec.~\ref{lipidSec:ExpSetup} and simulated for a length
296 > of 10~ns at 300~K. The other temperature runs were started from a
297 > frame 7~ns into the 300~K simulation. Their temperatures were reset
298 > with the thermostating algorithm in the $\text{NPT}_{xyz}$
299 > integrator. All of the temperature variants were also run for 10~ns,
300 > with only the last 5~ns being used for accumulation of statistics.
301 >
302 > The second class of simulations were two configurations started from
303 > randomly dispersed lipids in a ``gas'' of water. The first
304 > ($\text{R}_{\text{I}}$) was a simulation containing 72 lipids with
305 > 1800 {\sc ssd} molecules simulated at 300~K. The second
306 > ($\text{R}_{\text{II}}$) was 90 lipids with 1350 {\sc ssd} molecules
307 > simulated at 350~K. Both simulations were integrated for more than
308 > 20~ns, and illustrate the spontaneous aggregation of the lipid model
309 > into phospholipid macrostructures: $\text{R}_{\text{I}}$ into a
310 > bilayer, and $\text{R}_{\text{II}}$ into a inverted rod.
311 >
312 > \section{\label{lipidSec:resultsDis}Results and Discussion}
313 >
314 > \subsection{\label{lipidSec:scd}$\text{S}_{\text{{\sc cd}}}$ order parameters}
315 >
316 > The $\text{S}_{\text{{\sc cd}}}$ order parameter is often reported in
317 > the experimental charecterizations of phospholipids. It is obtained
318 > through deuterium NMR, and measures the ordering of the carbon
319 > deuterium bond in relation to the bilayer normal at various points
320 > along the chains. In our model, there are no explicit hydrogens, but
321 > the order parameter can be written in terms of the carbon ordering at
322 > each point in the chain:\cite{egberts88}
323 > \begin{equation}
324 > S_{\text{{\sc cd}}}  = \frac{2}{3}S_{xx} + \frac{1}{3}S_{yy}
325 > \label{lipidEq:scd1}
326 > \end{equation}
327 > Where $S_{ij}$ is given by:
328 > \begin{equation}
329 > S_{ij} = \frac{1}{2}\Bigl<(3\cos\Theta_i\cos\Theta_j - \delta_{ij})\Bigr>
330 > \label{lipidEq:scd2}
331 > \end{equation}
332 > Here, $\Theta_i$ is the angle the $i$th carbon atom frame axis makes
333 > with the bilayer normal. The brackets denote an average over time and
334 > molecules. The carbon atom axes are defined:
335 > $\mathbf{\hat{z}}\rightarrow$ vector from $C_{n-1}$ to $C_{n+1}$;
336 > $\mathbf{\hat{y}}\rightarrow$ vector that is perpindicular to $z$ and
337 > in the plane through $C_{n-1}$, $C_{n}$, and $C_{n+1}$;
338 > $\mathbf{\hat{x}}\rightarrow$ vector perpindicular to
339 > $\mathbf{\hat{y}}$ and $\mathbf{\hat{z}}$.
340 >
341 > The order parameter has a range of $[1,-\frac{1}{2}]$. A value of 1
342 > implies full order aligned to the bilayer axis, 0 implies full
343 > disorder, and $-\frac{1}{2}$ implies full order perpindicular to the
344 > bilayer axis. The {\sc cd} bond vector for carbons near the head group
345 > are usually ordered perpindicular to the bilayer normal, with tails
346 > farther away tending toward disorder. This makes the order paramter
347 > negative for most carbons, and as such $|S_{\text{{\sc cd}}}|$ is more
348 > commonly reported than $S_{\text{{\sc cd}}}$.
349 >
350 >
351 >
352 >
353 > \begin{figure}
354 > \centering
355 > \includegraphics[width=\linewidth]{scdFig.eps}
356 > \caption[$\text{S}_{\text{{\sc cd}}}$ order parameter for our model]{A comparison of $|\text{S}_{\text{{\sc cd}}}|$ between our model (blue) and DMPC\cite{petrache00} (black) near 300~K.}
357 > \label{lipidFig:scdFig}
358 > \end{figure}
359 >
360 >
361 > \begin{figure}
362 > \centering
363 > \includegraphics[width=\linewidth]{densityProfile.eps}
364 > \caption[The density profile of the lipid bilayers]{The density profile of the lipid bilayers along the bilayer normal. The black lines are the {\sc head} atoms, red lines are the {\sc ch} atoms, green lines are the $\text{{\sc ch}}_2$ atoms, blue lines are the $\text{{\sc ch}}_3$ atoms, and the magenta lines are the {\sc ssd} atoms.}
365 > \label{lipidFig:densityProfile}
366 > \end{figure}
367 >
368 >
369 >
370 > \begin{figure}
371 > \centering
372 > \includegraphics[width=\linewidth]{diffusionFig.eps}
373 > \caption[The lateral difusion constants versus temperature]{The lateral diffusion constants for the bilayers as a function of temperature.}
374 > \label{lipidFig:diffusionFig}
375 > \end{figure}
376 >
377 > \begin{table}
378 > \caption[Structural properties of the bilayers]{Bilayer Structural properties as a function of temperature.}
379 > \begin{center}
380 > \begin{tabular}{|c|c|c|c|c|}
381 > \hline
382 > Temperature (K) & $<L_{\perp}>$ ($\mbox{\AA}$) & %
383 >        $<A_{\parallel}>$ ($\mbox{\AA}^2$) & $<P_2>_{\text{Lipid}}$ & %
384 >        $<P_2>_{\text{{\sc head}}}$ \\ \hline
385 > 270 & 18.1 & 58.1 & 0.253 & 0.494 \\ \hline
386 > 275 & 17.2 & 56.7 & 0.295 & 0.514 \\ \hline
387 > 277 & 16.9 & 58.0 & 0.301 & 0.541 \\ \hline
388 > 280 & 17.4 & 58.0 & 0.274 & 0.488 \\ \hline
389 > 285 & 16.9 & 57.6 & 0.270 & 0.616 \\ \hline
390 > 290 & 17.0 & 57.6 & 0.263 & 0.534 \\ \hline
391 > 293 & 17.5 & 58.0 & 0.227 & 0.643 \\ \hline
392 > 300 & 16.9 & 57.6 & 0.315 & 0.536 \\ \hline
393 > \end{tabular}
394 > \end{center}
395 > \end{table}

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