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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     rapidly in the eukaryotic ER and the bacterial cytoplasmic membrane
32     via a bi-directional, facilitated diffusion process requiring no
33     metabolic energy input. Another system of interest would be the
34     distribution of sites occupied by inhaled anesthetics in membrane.
35     Although the physiological effects of anesthetics have been
36     extensively studied, the controversy over their effects on lipid
37     bilayers still continues. Recent deuterium NMR measurements on
38     halothane in POPC lipid bilayers suggest the anesthetics are
39     primarily located at the hydrocarbon chain region\cite{Baber1995}.
40 tim 2776 Infrared spectroscopy experiments suggest that halothane in DMPC
41 tim 2786 lipid bilayers lives near the membrane/water
42     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 2786 the range of current simulation technologies.
49     %review of coarse-grained modeling
50     Several schemes are proposed in this chapter to overcome these
51     difficulties.
52 tim 2731
53 tim 2685 \section{\label{lipidSection:model}Model}
54    
55 tim 2776 \subsection{\label{lipidSection:SSD}The Soft Sticky Dipole Water Model}
56 tim 2685
57 tim 2776 In a typical bilayer simulation, the dominant portion of the
58     computation time will be spent calculating water-water interactions.
59     As an efficient solvent model, the Soft Sticky Dipole (SSD) water
60 tim 2786 model\cite{Chandra1999,Fennel2004} is used as the explicit solvent
61     in this project. Unlike other water models which have partial
62     charges distributed throughout the whole molecule, the SSD water
63     model consists of a single site which is a Lennard-Jones interaction
64     site, as well as a point dipole. A tetrahedral potential is added to
65     correct for hydrogen bonding. The following equation describes the
66     interaction between two water molecules:
67 tim 2776 \[
68     V_{SSD} = V_{LJ} (r_{ij} ) + V_{dp} (r_{ij} ,\Omega _i ,\Omega _j )
69     + V_{sticky} (r_{ij} ,\Omega _i ,\Omega _j )
70     \]
71     where $r_{ij}$ is the vector between molecule $i$ and molecule $j$,
72     $\Omega _i$ and $\Omega _j$ are the orientational degrees of freedom
73     for molecule $i$ and molecule $j$ respectively.
74     \[
75     V_{LJ} (r_{ij} ) = 4\varepsilon _{ij} \left[ {\left( {\frac{{\sigma
76     _{ij} }}{{r_{ij} }}} \right)^{12} - \left( {\frac{{\sigma _{ij}
77     }}{{r_{ij} }}} \right)^6 } \right]
78     \]
79     \[
80     V_{dp} (r_{ij} ,\Omega _i ,\Omega _j ) = \frac{1}{{4\pi \varepsilon
81     _0 }}\left[ {\frac{{\mu _i \cdot \mu _j }}{{r_{ij}^3 }} -
82     \frac{{3\left( {\mu _i \cdot r_{ij} } \right)\left( {\mu _i \cdot
83     r_{ij} } \right)}}{{r_{ij}^5 }}} \right]
84     \]
85     \[
86     V_{sticky} (r_{ij} ,\Omega _i ,\Omega _j ) = v_0 [s(r_{ij} )w(r_{ij}
87     ,\Omega _i ,\Omega _j ) + s'(r_{ij} )w'(r_{ij} ,\Omega _i ,\Omega _j
88     )]
89     \]
90     where $v_0$ is a strength parameter, $s$ and $s'$ are cubic
91     switching functions, while $w$ and $w'$ are responsible for the
92     tetrahedral potential and the short-range correction to the dipolar
93     interaction respectively.
94     \[
95     \begin{array}{l}
96     w(r_{ij} ,\Omega _i ,\Omega _j ) = \sin \theta _{ij} \sin 2\theta _{ij} \cos 2\phi _{ij} \\
97     w'(r_{ij} ,\Omega _i ,\Omega _j ) = (\cos \theta _{ij} - 0.6)^2 (\cos \theta _{ij} + 0.8)^2 - w_0 \\
98     \end{array}
99     \]
100     Although dipole-dipole and sticky interactions are more
101     mathematically complicated than Coulomb interactions, the number of
102     pair interactions is reduced dramatically both because the model
103     only contains a single-point as well as "short range" nature of the
104     higher order interaction.
105    
106     \subsection{\label{lipidSection:coarseGrained}The Coarse-Grained Phospholipid Model}
107    
108 tim 2781 Fig.~\ref{lipidFigure:coarseGrained} shows a schematic for our
109     coarse-grained phospholipid model. The lipid head group is modeled
110     by a linear rigid body which consists of three Lennard-Jones spheres
111     and a centrally located point-dipole. The backbone atoms in the
112     glycerol motif are modeled by Lennard-Jones spheres with dipoles.
113     Alkyl groups in hydrocarbon chains are replaced with unified
114     $\text{{\sc CH}}_2$ or $\text{{\sc CH}}_3$ atoms.
115 tim 2776
116 tim 2781 \begin{figure}
117     \centering
118 tim 2806 \includegraphics[width=3in]{coarse_grained.eps}
119 tim 2781 \caption[A representation of coarse-grained phospholipid model]{}
120     \label{lipidFigure:coarseGrained}
121     \end{figure}
122    
123 tim 2776 Accurate and efficient computation of electrostatics is one of the
124     most difficult tasks in molecular modeling. Traditionally, the
125     electrostatic interaction between two molecular species is
126     calculated as a sum of interactions between pairs of point charges,
127     using Coulomb's law:
128     \[
129     V = \sum\limits_{i = 1}^{N_A } {\sum\limits_{j = 1}^{N_B }
130     {\frac{{q_i q_j }}{{4\pi \varepsilon _0 r_{ij} }}} }
131     \]
132     where $N_A$ and $N_B$ are the number of point charges in the two
133     molecular species. Originally developed to study ionic crystals, the
134     Ewald summation method mathematically transforms this
135     straightforward but conditionally convergent summation into two more
136     complicated but rapidly convergent sums. One summation is carried
137     out in reciprocal space while the other is carried out in real
138     space. An alternative approach is a multipole expansion, which is
139     based on electrostatic moments, such as charge (monopole), dipole,
140     quadruple etc.
141    
142     Here we consider a linear molecule which consists of two point
143     charges $\pm q$ located at $ ( \pm \frac{d}{2},0)$. The
144     electrostatic potential at point $P$ is given by:
145     \[
146     \frac{1}{{4\pi \varepsilon _0 }}\left( {\frac{{ - q}}{{r_ - }} +
147     \frac{{ + q}}{{r_ + }}} \right) = \frac{1}{{4\pi \varepsilon _0
148     }}\left( {\frac{{ - q}}{{\sqrt {r^2 + \frac{{d^2 }}{4} + rd\cos
149     \theta } }} + \frac{q}{{\sqrt {r^2 + \frac{{d^2 }}{4} - rd\cos
150     \theta } }}} \right)
151     \]
152    
153 tim 2781 \begin{figure}
154     \centering
155 tim 2806 \includegraphics[width=3in]{charge_dipole.eps}
156 tim 2781 \caption[Electrostatic potential due to a linear molecule comprising
157     two point charges]{Electrostatic potential due to a linear molecule
158     comprising two point charges} \label{lipidFigure:chargeDipole}
159     \end{figure}
160    
161 tim 2776 The basic assumption of the multipole expansion is $r \gg d$ , thus,
162     $\frac{{d^2 }}{4}$ inside the square root of the denominator is
163     neglected. This is a reasonable approximation in most cases.
164     Unfortunately, in our headgroup model, the distance of charge
165     separation $d$ (4.63 $\AA$ in PC headgroup) may be comparable to
166     $r$. Nevertheless, we could still assume $ \cos \theta \approx 0$
167     in the central region of the headgroup. Using Taylor expansion and
168     associating appropriate terms with electric moments will result in a
169     "split-dipole" approximation:
170     \[
171     V(r) = \frac{1}{{4\pi \varepsilon _0 }}\frac{{r\mu \cos \theta
172     }}{{R^3 }}
173     \]
174     where$R = \sqrt {r^2 + \frac{{d^2 }}{4}}$ Placing a dipole at point
175     $P$ and applying the same strategy, the interaction between two
176     split-dipoles is then given by:
177     \[
178     V_{sd} (r_{ij} ,\Omega _i ,\Omega _j ) = \frac{1}{{4\pi \varepsilon
179     _0 }}\left[ {\frac{{\mu _i \cdot \mu _j }}{{R_{ij}^3 }} -
180     \frac{{3\left( {\mu _i \cdot r_{ij} } \right)\left( {\mu _i \cdot
181     r_{ij} } \right)}}{{R_{ij}^5 }}} \right]
182     \]
183     where $\mu _i$ and $\mu _j$ are the dipole moment of molecule $i$
184     and molecule $j$ respectively, $r_{ij}$ is vector between molecule
185 tim 2800 $i$ and molecule $j$, and $R_{ij}$ is given by,
186 tim 2776 \[
187     R_{ij} = \sqrt {r_{ij}^2 + \frac{{d_i^2 }}{4} + \frac{{d_j^2
188     }}{4}}
189     \]
190     where $d_i$ and $d_j$ are the charge separation distance of dipole
191     and respectively. This approximation to the multipole expansion
192     maintains the fast fall-off of the multipole potentials but lacks
193     the normal divergences when two polar groups get close to one
194     another.
195 tim 2786 %description of the comparsion
196 tim 2776 \begin{figure}
197     \centering
198     \includegraphics[width=\linewidth]{split_dipole.eps}
199     \caption[Comparison between electrostatic approximation]{Electron
200     density profile along the bilayer normal.}
201     \label{lipidFigure:splitDipole}
202     \end{figure}
203    
204     %\section{\label{lipidSection:methods}Methods}
205    
206 tim 2685 \section{\label{lipidSection:resultDiscussion}Results and Discussion}
207 tim 2776
208     \subsection{One Lipid in Sea of Water Molecules}
209    
210     To exclude the inter-headgroup interaction, atomistic models of one
211     lipid (DMPC or DLPE) in sea of water molecules (TIP3P) were built
212     and studied using atomistic molecular dynamics. The simulation was
213     analyzed using a set of radial distribution functions, which give
214     the probability of finding a pair of molecular species a distance
215     apart, relative to the probability expected for a completely random
216     distribution function at the same density.
217    
218     \begin{equation}
219     g_{AB} (r) = \frac{1}{{\rho _B }}\frac{1}{{N_A }} < \sum\limits_{i
220     \in A} {\sum\limits_{j \in B} {\delta (r - r_{ij} )} } >
221     \end{equation}
222     \begin{equation}
223     g_{AB} (r,\cos \theta ) = \frac{1}{{\rho _B }}\frac{1}{{N_A }} <
224     \sum\limits_{i \in A} {\sum\limits_{j \in B} {\delta (r - r_{ij} )}
225     } \delta (\cos \theta _{ij} - \cos \theta ) >
226     \end{equation}
227    
228     From figure 4(a), we can identify the first solvation shell (3.5
229     $\AA$) and the second solvation shell (5.0 $\AA$) from both plots.
230     However, the corresponding orientations are different. In DLPE,
231     water molecules prefer to sit around -NH3 group due to the hydrogen
232     bonding. In contrast, because of the hydrophobic effect of the
233     -N(CH3)3 group, the preferred position of water molecules in DMPC is
234     around the -PO4 Group. When the water molecules are far from the
235     headgroup, the distribution of the two angles should be uniform. The
236     correlation close to center of the headgroup dipole (< 5 $\AA$) in
237     both plots tell us that in the closely-bound region, the dipoles of
238     the water molecules are preferentially anti-aligned with the dipole
239     of headgroup.
240    
241     \begin{figure}
242     \centering
243     \includegraphics[width=\linewidth]{g_atom.eps}
244     \caption[The pair correlation functions for atomistic models]{}
245     \label{lipidFigure:PCFAtom}
246     \end{figure}
247    
248     The initial configurations of coarse-grained systems are constructed
249     from the previous atomistic ones. The parameters for the
250     coarse-grained model in Table~\ref{lipidTable:parameter} are
251     estimated and tuned using isothermal-isobaric molecular dynamics.
252     Pair distribution functions calculated from coarse-grained models
253     preserve the basic characteristics of the atomistic simulations. The
254     water density, measured in a head-group-fixed reference frame,
255     surrounding two phospholipid headgroups is shown in
256     Fig.~\ref{lipidFigure:PCFCoarse}. It is clear that the phosphate end
257     in DMPC and the amine end in DMPE are the two most heavily solvated
258     atoms.
259    
260     \begin{figure}
261     \centering
262     \includegraphics[width=\linewidth]{g_coarse.eps}
263     \caption[The pair correlation functions for coarse-grained models]{}
264     \label{lipidFigure:PCFCoarse}
265     \end{figure}
266    
267     \begin{figure}
268     \centering
269     \includegraphics[width=\linewidth]{EWD_coarse.eps}
270     \caption[Excess water density of coarse-grained phospholipids]{ }
271     \label{lipidFigure:EWDCoarse}
272     \end{figure}
273    
274     \begin{table}
275     \caption{The Parameters For Coarse-grained Phospholipids}
276     \label{lipidTable:parameter}
277     \begin{center}
278     \begin{tabular}{|l|c|c|c|c|c|}
279     \hline
280     % after \\: \hline or \cline{col1-col2} \cline{col3-col4} ...
281     Atom type & Mass & $\sigma$ & $\epsilon$ & charge & Dipole \\
282     $\text{{\sc CH}}_2$ & 14.03 & 3.95 & 0.0914 & 0 & 0 \\
283     $\text{{\sc CH}}_3$ & 15.04 & 3.75 & 0.195 & 0 & 0 \\
284 tim 2781 $\text{{\sc CE}}$ & 28.01 & 3.427& 0.294 & 0 & 1.693 \\
285 tim 2776 $\text{{\sc CK}}$ & 28.01 & 3.592& 0.311 & 0 & 2.478 \\
286     $\text{{\sc PO}}_4$ & 108.995& 3.9 & 1.88 & -1& 0 \\
287     $\text{{\sc HDP}}$ & 14.03 & 4.0 & 0.13 & 0 & 0 \\
288     $\text{{\sc NC}}_4$ & 73.137 & 4.9 & 0.88 & +1& 0 \\
289     $\text{{\sc NH}}_3$ & 17.03 & 3.25 & 0.17 & +1& 0\\
290     \hline
291     \end{tabular}
292     \end{center}
293     \end{table}
294    
295     \subsection{Bilayer Simulations Using Coarse-grained Model}
296    
297     A bilayer system consisting of 128 DMPC lipids and 3655 water
298     molecules has been constructed from an atomistic coordinate
299     file.[15] The MD simulation is performed at constant temperature, T
300     = 300K, and constant pressure, p = 1 atm, and consisted of an
301     equilibration period of 2 ns. During the equilibration period, the
302     system was initially simulated at constant volume for 1ns. Once the
303     system was equilibrated at constant volume, the cell dimensions of
304     the system was relaxed by performing under NPT conditions using
305     Nos¨¦-Hoover extended system isothermal-isobaric dynamics. After
306     equilibration, different properties were evaluated over a production
307     run of 5 ns.
308    
309     \begin{figure}
310     \centering
311     \includegraphics[width=\linewidth]{bilayer.eps}
312     \caption[Image of a coarse-grained bilayer system]{A coarse-grained
313     bilayer system consisting of 128 DMPC lipids and 3655 SSD water
314     molecules.}
315     \label{lipidFigure:bilayer}
316     \end{figure}
317    
318     \subsubsection{Electron Density Profile (EDP)}
319    
320     Assuming a gaussian distribution of electrons on each atomic center
321     with a variance estimated from the size of the van der Waals radius,
322     the EDPs which are proportional to the density profiles measured
323     along the bilayer normal obtained by x-ray scattering experiment,
324 tim 2786 can be expressed by\cite{Tu1995}
325 tim 2776 \begin{equation}
326     \rho _{x - ray} (z)dz \propto \sum\limits_{i = 1}^N {\frac{{n_i
327     }}{V}\frac{1}{{\sqrt {2\pi \sigma ^2 } }}e^{ - (z - z_i )^2 /2\sigma
328     ^2 } dz},
329     \end{equation}
330     where $\sigma$ is the variance equal to the van der Waals radius,
331     $n_i$ is the atomic number of site $i$ and $V$ is the volume of the
332     slab between $z$ and $z+dz$ . The highest density of total EDP
333     appears at the position of lipid-water interface corresponding to
334     headgroup, glycerol, and carbonyl groups of the lipids and the
335     distribution of water locked near the head groups, while the lowest
336     electron density is in the hydrocarbon region. As a good
337     approximation to the thickness of the bilayer, the headgroup spacing
338     , is defined as the distance between two peaks in the electron
339     density profile, calculated from our simulations to be 34.1 $\AA$.
340     This value is close to the x-ray diffraction experimental value 34.4
341 tim 2786 $\AA$\cite{Petrache1998}.
342 tim 2776
343     \begin{figure}
344     \centering
345     \includegraphics[width=\linewidth]{electron_density.eps}
346     \caption[The density profile of the lipid bilayers]{Electron density
347     profile along the bilayer normal. The water density is shown in red,
348     the density due to the headgroups in green, the glycerol backbone in
349     brown, $\text{{\sc CH}}_2$ in yellow, $\text{{\sc CH}}_3$ in cyan,
350     and total density due to DMPC in blue.}
351     \label{lipidFigure:electronDensity}
352     \end{figure}
353    
354     \subsubsection{$\text{S}_{\text{{\sc cd}}}$ Order Parameter}
355    
356     Measuring deuterium order parameters by NMR is a useful technique to
357     study the orientation of hydrocarbon chains in phospholipids. The
358     order parameter tensor $S$ is defined by:
359     \begin{equation}
360     S_{ij} = \frac{1}{2} < 3\cos \theta _i \cos \theta _j - \delta
361     _{ij} >
362     \end{equation}
363     where $\theta$ is the angle between the $i$th molecular axis and
364     the bilayer normal ($z$ axis). The brackets denote an average over
365     time and molecules. The molecular axes are defined:
366     \begin{itemize}
367     \item $\mathbf{\hat{z}}$ is the vector from $C_{n-1}$ to $C_{n+1}$.
368     \item $\mathbf{\hat{y}}$ is the vector that is perpendicular to $z$ and
369     in the plane through $C_{n-1}$, $C_{n}$, and $C_{n+1}$.
370     \item $\mathbf{\hat{x}}$ is the vector perpendicular to
371     $\mathbf{\hat{y}}$ and $\mathbf{\hat{z}}$.
372     \end{itemize}
373     In coarse-grained model, although there are no explicit hydrogens,
374     the order parameter can still be written in terms of carbon ordering
375 tim 2786 at each point of the chain\cite{Egberts1988}
376 tim 2776 \begin{equation}
377     S_{ij} = \frac{1}{2} < 3\cos \theta _i \cos \theta _j - \delta
378     _{ij} >.
379     \end{equation}
380    
381     Fig.~\ref{lipidFigure:Scd} shows the order parameter profile
382     calculated for our coarse-grained DMPC bilayer system at 300K. Also
383 tim 2786 shown are the experimental data of Tu\cite{Tu1995}. The fact that
384 tim 2776 $\text{S}_{\text{{\sc cd}}}$ order parameters calculated from
385     simulation are higher than the experimental ones is ascribed to the
386     assumption of the locations of implicit hydrogen atoms which are
387     fixed in coarse-grained models at positions relative to the CC
388     vector.
389    
390     \begin{figure}
391     \centering
392     \includegraphics[width=\linewidth]{scd.eps}
393     \caption[$\text{S}_{\text{{\sc cd}}}$ order parameter]{A comparison
394     of $|\text{S}_{\text{{\sc cd}}}|$ between coarse-grained model
395     (blue) and DMPC\cite{petrache00} (black) near 300~K.}
396     \label{lipidFigure:Scd}
397     \end{figure}
398 tim 2781
399     %\subsection{Bilayer Simulations Using Gay-Berne Ellipsoid Model}