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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
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{marrink01} With the exception of a few
14   ambitious
15   simulations,\cite{marrink01:undulation,marrink:2002,lindahl00} most
16 < investigations are limited to 64 to 256
16 > investigations are limited to a range of 64 to 256
17   phospholipids.\cite{lindahl00,sum:2003,venable00,gomez:2003,smondyrev:1999,marrink01}
18 < This is due to the expense of the computer calculations involved when
19 < performing these simulations.  To properly hydrate a bilayer, one
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 difficulty 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 lengths of bilayer simulations.
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 infeasible with current simulation. One such example is the
30 < observance of a ripple phase ($P_{\beta^{\prime}}$) between the
31 < $L_{\beta}$ and $L_{\alpha}$ phases of certain phospholipid
32 < bilayers.\cite{katsaras00,sengupta00} 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
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
# Line 68 | Line 68 | phospholipids. The dipole electrostatic interaction is
68   interactions small.  What sets this model apart, however, is the use
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 ({\sc ssd}) water
# Line 77 | Line 77 | contribution to the hydrophobic effect due to hydrogen
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.
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{lipidSec: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
90 < conclusions of this chapter are presented in
91 < 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  
# Line 109 | Line 108 | given phospholipid head group.  The atoms of the tail
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 $\sigma_{\text{tail}}$ and $\epsilon_{\text{tail}}$.
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}
# Line 129 | Line 129 | V_{\text{dipole}}(\mathbf{r}_{ij},\boldsymbol{\Omega}_
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 <        \frac{3(\boldsymbol{\hat{u}}_i \cdot \mathbf{r}_{ij}) %
133 <                (\boldsymbol{\hat{u}}_j \cdot \mathbf{r}_{ij}) }
134 <                {r^{2}_{ij}} \biggr]
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 140 | 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 bends, and torsions.
149   The bond between two beads on a chain is of fixed length, and is
# Line 159 | Line 158 | potential to keep the dipole pointed along the bilayer
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. The torsion potential is given
163 < by:
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   V_{\text{torsion}}(\phi) =  
166          k_3 \cos^3 \phi + k_2 \cos^2 \phi + k_1 \cos \phi + k_0
# Line 175 | Line 174 | directly involved in a bonded pair are calculated.
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:lipidModel}.  The chains are both eight beads long,
186   and their mass and Lennard Jones parameters are summarized in
# Line 259 | 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. Simulation
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:diffusion}Lateral Diffusion Constants}
315 >
316 > The lateral diffusion constant, $D_L$, is the constant charecterizing
317 > the diffusive motion of the lipid within the plane of the bilayer. It
318 > is given by the following Einstein relation valid at long
319 > times:\cite{allen87:csl}
320 > \begin{equation}
321 > 2tD_L = \frac{1}{2}\langle |\mathbf{r}(t) - \mathbf{r}(0)|^2\rangle
322 > \end{equation}
323 > Where $\mathbf{r}(t)$ is the position of the lipid at time $t$, and is
324 > constrained to lie within a plane. For the bilayer simulations the
325 > plane of constrained motion was that perpindicular to the bilayer
326 > normal, namely the $xy$-plane.
327 >
328 > Fig.~\ref{lipidFig:diffusionFig} shows the lateral diffusion constants
329 > as a function of temperature. There is a definite increase in the
330 > lateral diffusion with higher temperatures, which is exactly what one
331 > would expect with greater fluidity of the chains. However, the
332 > diffusion constants are all two orders of magnitude smaller than those
333 > typical of DPPC.\cite{Cevc87} This is counter-intuitive as the DPPC
334 > molecule is sterically larger and heavier than our model. This could
335 > be an indication that our model's chains are too interwoven and hinder
336 > the motion of the lipid, or that a simplification in the model's
337 > forces has led to a slowing of diffusive behaviour within the
338 > bilayer. In contrast, the diffusion constant of the {\sc ssd} water,
339 > $9.84\times 10^{-6}\,\text{cm}^2/\text{s}$, compares favorably with
340 > that of bulk water.
341 >
342 > \begin{figure}
343 > \centering
344 > \includegraphics[width=\linewidth]{diffusionFig.eps}
345 > \caption[The lateral difusion constants versus temperature]{The lateral diffusion constants for the bilayers as a function of temperature.}
346 > \label{lipidFig:diffusionFig}
347 > \end{figure}
348 >
349 > \subsection{\label{lipidSec:densProf}Density Profile}
350 >
351 > Fig.~\ref{lipidFig:densityProfile} illustrates the densities of the
352 > atoms in the bilayer systems normailzed by the bulk density as a
353 > function of distance from the center of the box. The profile is taken
354 > along the bilayer normal, in this case the $z$ axis. The profile at
355 > 270~K shows several structural features that are largerly smoothed out
356 > by 300~K. The left peak for the {\sc head} atoms is split at 270~K,
357 > implying that some freezing of the structure might already be occuring
358 > at this temperature. From the dynamics, the tails at this temperature
359 > are very much fluid, but the profile could indicate that a phase
360 > transition may simply be beyond the length scale of the current
361 > simulation. In all profiles, the water penetrates almost
362 > 5~$\mbox{\AA}$ into the bilayer, completely solvating the {\sc head}
363 > atoms. The $\text{{\sc ch}}_3$ atoms although mainly centered at the
364 > middle of the bilayer, show appreciable penetration into the head
365 > group region. This indicates that the chains have enough mobility to
366 > bend back upward to allow the ends to explore areas around the {\sc
367 > head} atoms. It is unlikely that this is penetration from a lipid of
368 > the opposite face, as the lipids are only 12~$\mbox{\AA}$ in length,
369 > and the typical leaf spacing as measured from the {\sc head-head}
370 > spacing in the profile is 17.5~$\mbox{\AA}$.
371 >
372 > \begin{figure}
373 > \centering
374 > \includegraphics[width=\linewidth]{densityProfile.eps}
375 > \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.}
376 > \label{lipidFig:densityProfile}
377 > \end{figure}
378 >
379 >
380 > \subsection{\label{lipidSec:scd}$\text{S}_{\text{{\sc cd}}}$ Order Parameters}
381 >
382 > The $\text{S}_{\text{{\sc cd}}}$ order parameter is often reported in
383 > the experimental charecterizations of phospholipids. It is obtained
384 > through deuterium NMR, and measures the ordering of the carbon
385 > deuterium bond in relation to the bilayer normal at various points
386 > along the chains. In our model, there are no explicit hydrogens, but
387 > the order parameter can be written in terms of the carbon ordering at
388 > each point in the chain:\cite{egberts88}
389 > \begin{equation}
390 > S_{\text{{\sc cd}}}  = \frac{2}{3}S_{xx} + \frac{1}{3}S_{yy}
391 > \label{lipidEq:scd1}
392 > \end{equation}
393 > Where $S_{ij}$ is given by:
394 > \begin{equation}
395 > S_{ij} = \frac{1}{2}\Bigl\langle(3\cos\Theta_i\cos\Theta_j
396 >        - \delta_{ij})\Bigr\rangle
397 > \label{lipidEq:scd2}
398 > \end{equation}
399 > Here, $\Theta_i$ is the angle the $i$th axis in the reference frame of
400 > the carbon atom makes with the bilayer normal. The brackets denote an
401 > average over time and molecules. The carbon atom axes are defined:
402 > $\mathbf{\hat{z}}\rightarrow$ vector from $C_{n-1}$ to $C_{n+1}$;
403 > $\mathbf{\hat{y}}\rightarrow$ vector that is perpindicular to $z$ and
404 > in the plane through $C_{n-1}$, $C_{n}$, and $C_{n+1}$;
405 > $\mathbf{\hat{x}}\rightarrow$ vector perpindicular to
406 > $\mathbf{\hat{y}}$ and $\mathbf{\hat{z}}$.
407 >
408 > The order parameter has a range of $[1,-\frac{1}{2}]$. A value of 1
409 > implies full order aligned to the bilayer axis, 0 implies full
410 > disorder, and $-\frac{1}{2}$ implies full order perpindicular to the
411 > bilayer axis. The {\sc cd} bond vector for carbons near the head group
412 > are usually ordered perpindicular to the bilayer normal, with tails
413 > farther away tending toward disorder. This makes the order paramter
414 > negative for most carbons, and as such $|S_{\text{{\sc cd}}}|$ is more
415 > commonly reported than $S_{\text{{\sc cd}}}$.
416 >
417 > Fig.~\ref{lipidFig:scdFig} shows the $S_{\text{{\sc cd}}}$ order
418 > parameters for the bilayer system at 300~K. There is no appreciable
419 > difference in the plots for the various temperatures, however, there
420 > is a larger difference between our models ordering, and that of
421 > DMPC. As our values are closer to $-\frac{1}{2}$, this implies more
422 > ordering perpindicular to the normal than in a real system. This is
423 > due to the model having only one carbon group separating the chains
424 > from the top of the lipid. In DMPC, with the flexibility inherent in a
425 > multiple atom head group, as well as a glycerol linkage between the
426 > head group and the acyl chains, there is more loss of ordering by the
427 > point when the chains start.
428 >
429 > \begin{figure}
430 > \centering
431 > \includegraphics[width=\linewidth]{scdFig.eps}
432 > \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.}
433 > \label{lipidFig:scdFig}
434 > \end{figure}
435 >
436 >
437 >
438 >
439 >
440 > \begin{table}
441 > \caption[Structural properties of the bilayers]{Bilayer Structural properties as a function of temperature.}
442 > \begin{center}
443 > \begin{tabular}{|c|c|c|c|c|}
444 > \hline
445 > Temperature (K) & $\langle L_{\perp}\rangle$ ($\mbox{\AA}$) & %
446 >        $\langle A_{\parallel}\rangle$ ($\mbox{\AA}^2$) & %
447 >        $\langle P_2\rangle_{\text{Lipid}}$ & %
448 >        $\langle P_2\rangle_{\text{{\sc head}}}$ \\ \hline
449 > 270 & 18.1 & 58.1 & 0.253 & 0.494 \\ \hline
450 > 275 & 17.2 & 56.7 & 0.295 & 0.514 \\ \hline
451 > 277 & 16.9 & 58.0 & 0.301 & 0.541 \\ \hline
452 > 280 & 17.4 & 58.0 & 0.274 & 0.488 \\ \hline
453 > 285 & 16.9 & 57.6 & 0.270 & 0.616 \\ \hline
454 > 290 & 17.0 & 57.6 & 0.263 & 0.534 \\ \hline
455 > 293 & 17.5 & 58.0 & 0.227 & 0.643 \\ \hline
456 > 300 & 16.9 & 57.6 & 0.315 & 0.536 \\ \hline
457 > \end{tabular}
458 > \end{center}
459 > \end{table}

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