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55 \author{Don Armstrong}
56 \title{OOL Kinetic Formalisms}
62 <<results=hide,echo=FALSE>>=
66 to.kcal <- function(k,temp=300) {
68 return(-gasconst*temp*log(k)/1000)
72 \section{State Equation}
73 % double check this with the bits in the paper
75 Given a base forward kinetic parameter for the $i$th specie $k_{fi}$
76 (which is dependent on lipid type, that is PC, PE, PS, etc.), an
77 adjustment parameter $k_{fi\mathrm{adj}}$ based on the vesicle and the
78 specific specie (length, unsaturation, etc.) (see~\fref{eq:kf_adj}),
79 the molar concentration of monomer of the $i$th specie
80 $\left[C_{i_\mathrm{monomer}}\right]$, the surface area of the vesicle
81 $S_\mathrm{ves}$, the base backwards kinetic parameter for the $i$th
82 specie $k_{bi}$ which is also dependent on lipid type, its adjustment
83 parameter $k_{bi\mathrm{adj}}$ (see~\fref{eq:kb_adj}), and the molar
84 concentration of the $i$th specie in the vesicle $C_{i_\mathrm{ves}}$,
85 the change in concentration of the $i$th specie in the vesicle per
86 change in time $\frac{d C_{i_\mathrm{ves}}}{dt}$ can be calculated:
89 \frac{d C_{i_\mathrm{ves}}}{dt} = k_{fi}k_{fi\mathrm{adj}}\left[C_{i_\mathrm{monomer}}\right]S_\mathrm{ves} -
90 k_{bi}k_{bi\mathrm{adj}}C_{i_\mathrm{ves}}
94 For $k_{fi}k_{fi\mathrm{adj}}\left[C_{i_\mathrm{monomer}}\right]$,
95 $k_{fi}$ has units of $\frac{\mathrm{m}}{\mathrm{s}}$,
96 $k_{fi\mathrm{adj}}$ and $k_{bi\mathrm{adj}}$ are unitless,
97 concentration is in units of $\frac{\mathrm{n}}{\mathrm{L}}$, surface
98 area is in units of $\mathrm{m}^2$, $k_{bi}$ has units of
99 $\frac{1}{\mathrm{s}}$ and $C_{i_\mathrm{ves}}$ has units of
100 $\mathrm{n}$, Thus, we have
103 \frac{\mathrm{n}}{\mathrm{s}} = \frac{\mathrm{m}}{\mathrm{s}} \frac{\mathrm{n}}{\mathrm{L}} \mathrm{m}^2 \frac{1000\mathrm{L}}{\mathrm{m}^3} -
104 \frac{1}{\mathrm{s}} \mathrm{n}
106 \frac{\mathrm{m^3}}{\mathrm{s}} \frac{\mathrm{n}}{\mathrm{L}} \frac{1000\mathrm{L}}{\mathrm{m}^3} - \frac{\mathrm{n}}{\mathrm{s}}=
107 \frac{\mathrm{n}}{\mathrm{s}} = 1000 \frac{\mathrm{n}}{\mathrm{s}} - \frac{\mathrm{n}}{\mathrm{s}}
108 \label{eq:state_units}
111 The 1000 isn't in \fref{eq:state} above, because it is unit-dependent.
113 \subsection{Forward adjustments ($k_{fi\mathrm{adj}}$)}
115 The forward rate constant adjustment, $k_{fi\mathrm{adj}}$ takes into
116 account unsaturation ($un_f$), charge ($ch_f$), curvature ($cu_f$),
117 length ($l_f$), and complex formation ($CF1_f$), each of which are
118 modified depending on the specific specie and the vesicle into which
119 the specie is entering.
122 k_{fi\mathrm{adj}} = un_f \cdot ch_f \cdot cu_f \cdot l_f \cdot CF1_f
127 \subsubsection{Unsaturation Forward}
129 In order for a lipid to be inserted into a membrane, a void has to be
130 formed for it to fill. Voids can be generated by the combination of
131 unsaturated and saturated lipids forming herterogeneous domains. Void
132 formation is increased when the unsaturation of lipids in the vesicle
133 is widely distributed; in other words, the insertion of lipids into
134 the membrane is greater when the standard deviation of the
135 unsaturation is larger. Assuming that an increase in width of the
136 distribution linearly decreases the free energy of activation, the
137 $un_f$ parameter must follow
138 $a^{\mathrm{stdev}\left(un_\mathrm{ves}\right)}$ where $a > 1$, so a
139 convenient starting base for $a$ is $2$:
142 un_f = 2^{\mathrm{stdev}\left(un_\mathrm{ves}\right)}
143 \label{eq:unsaturation_forward}
146 The most common $\mathrm{stdev}\left(un_\mathrm{ves}\right)$ is around
147 $1.5$, which leads to a $\Delta \Delta G^\ddagger$ of
148 $\Sexpr{format(digits=3,to.kcal(2^1.5))}
149 \frac{\mathrm{kcal}}{\mathrm{mol}}$.
151 It is not clear that the unsaturation of the inserted monomer will
152 affect the rate of the insertion positively or negatively, so we do
153 not include a term for it in this formalism.
156 \setkeys{Gin}{width=3.2in}
157 <<fig=TRUE,echo=FALSE,results=hide,width=5,height=5>>=
158 curve(2^x,from=0,to=sd(c(0,4)),
159 main="Unsaturation Forward",
160 xlab="Standard Deviation of Unsaturation of Vesicle",
161 ylab="Unsaturation Forward Adjustment")
163 <<fig=TRUE,echo=FALSE,results=hide,width=5,height=5>>=
164 curve(to.kcal(2^x),from=0,to=sd(c(0,4)),
165 main="Unsaturation forward",
166 xlab="Standard Deviation of Unsaturation of Vesicle",
167 ylab="Unsaturation Forward (kcal/mol)")
172 \subsubsection{Charge Forward}
174 A charged lipid such as PS approaching a vesicle with an average
175 charge of the same sign will experience repulsion, whereas those with
176 different signs will experience attraction, the degree of which is
177 dependent upon the charge of the monomer and the average charge of the
178 vesicle. If either the vesicle or the monomer has no charge, there
179 should be no effect of charge upon the rate. This leads us to the
180 following equation, $a^{-\left<ch_v\right> ch_m}$, where
181 $\left<ch_v\right>$ is the average charge of the vesicle, and $ch_m$
182 is the charge of the monomer. If either $\left<ch_v\right>$ or $ch_m$
183 is 0, the adjustment parameter is 1 (no change), whereas it decreases
184 if both are positive or negative, as the product of two real numbers
185 with the same sign is always positive. A convenient base for $a$ is
186 60, resulting in the following equation:
190 ch_f = 60^{-\left<{ch}_v\right> {ch}_m}
191 \label{eq:charge_forward}
194 The most common $\left<{ch}_v\right>$ is around $-0.165$, which leads to
195 a range of $\Delta \Delta G^\ddagger$ from
196 $\Sexpr{format(digits=3,to.kcal(60^(-.165*-1)))}
197 \frac{\mathrm{kcal}}{\mathrm{mol}}$ to $0\frac{\mathrm{kcal}}{\mathrm{mol}}$.
199 <<fig=TRUE,echo=FALSE,results=hide,width=7,height=7>>=
200 x <- seq(-1,0,length.out=20)
201 y <- seq(-1,0,length.out=20)
202 grid <- expand.grid(x=x,y=y)
203 grid$z <- as.vector(60^(-outer(x,y)))
204 print(wireframe(z~x*y,grid,cuts=50,
206 scales=list(arrows=FALSE),
207 main="Charge Forward",
208 xlab=list("Average Vesicle Charge",rot=30),
209 ylab=list("Component Charge",rot=-35),
210 zlab=list("Charge Forward",rot=93)))
213 <<fig=TRUE,echo=FALSE,results=hide,width=7,height=7>>=
214 x <- seq(-1,0,length.out=20)
215 y <- seq(-1,0,length.out=20)
216 grid <- expand.grid(x=x,y=y)
217 grid$z <- as.vector(to.kcal(60^(-outer(x,y))))
218 print(wireframe(z~x*y,grid,cuts=50,
220 scales=list(arrows=FALSE),
221 main="Charge Forward (kcal/mol)",
222 xlab=list("Average Vesicle Charge",rot=30),
223 ylab=list("Component Charge",rot=-35),
224 zlab=list("Charge Forward (kcal/mol)",rot=93)))
230 \subsubsection{Curvature Forward}
232 Curvature is a measure of the intrinsic propensity of specific lipids
233 to form micelles (positive curvature), inverted micelles (negative
234 curvature), or planar sheets (zero curvature). In this formalism,
235 curvature is measured as the ratio of the size of the head to that of
236 the base, so negative curvature is bounded by $(0,1)$, zero curvature
237 is 1, and positive curvature is bounded by $(1,\infty)$. The curvature
238 can be transformed into the typical postive/negative mapping using
239 $\log$, which has the additional property of making the range of
240 positive and negative curvature equal, and distributed about 0.
242 As in the case of unsaturation, void formation is increased by the
243 presence of lipids with mismatched curvature. Thus, a larger
244 distribution of curvature in the vesicle increases the rate of lipid
245 insertion into the vesicle. However, a species with curvature $e^{-1}$
246 will cancel out a species with curvature $e$, so we have to log
247 transform (turning these into -1 and 1), then take the absolute value
248 (1 and 1), and finally measure the width of the distribution. Thus, by
249 using the log transform to make the range of the lipid curvature equal
250 between positive and negative, and taking the average to cancel out
251 exactly mismatched curvatures, we come to an equation with the shape
252 $a^{\left<\log cu_\mathrm{vesicle}\right>}$. A convenient base for $a$
257 % cu_f = 10^{\mathrm{stdev}\left|\log cu_\mathrm{vesicle}\right|}
258 cu_f = 10^{\left|\left<\log cu_\mathrm{vesicle} \right>\right|\mathrm{stdev} \left|\log cu_\mathrm{vesicle}\right|}
259 \label{eq:curvature_forward}
262 The most common $\left|\left<\log {cu}_v\right>\right|$ is around
263 $0.013$, which with the most common $\mathrm{stdev} \log
264 cu_\mathrm{vesicle}$ of $0.213$ leads to a $\Delta \Delta G^\ddagger$
265 of $\Sexpr{format(digits=3,to.kcal(10^(0.13*0.213)))}
266 \frac{\mathrm{kcal}}{\mathrm{mol}}$. This is a consequence of the
267 relatively matched curvatures in our environment.
269 % 1.5 to 0.75 3 to 0.33
270 <<fig=TRUE,echo=FALSE,results=hide,width=7,height=7>>=
271 grid <- expand.grid(x=seq(0,max(c(sd(abs(log(c(1,3)))),
272 sd(abs(log(c(1,0.33)))),sd(abs(log(c(0.33,3)))))),length.out=20),
273 y=seq(0,max(c(mean(log(c(1,3)),
274 mean(log(c(1,0.33))),
275 mean(log(c(0.33,3)))))),length.out=20))
276 grid$z <- 10^(grid$x*grid$y)
277 print(wireframe(z~x*y,grid,cuts=50,
279 scales=list(arrows=FALSE),
280 xlab=list("Vesicle stdev log curvature",rot=30),
281 ylab=list("Vesicle average log curvature",rot=-35),
282 zlab=list("Vesicle Curvature Forward",rot=93)))
285 <<fig=TRUE,echo=FALSE,results=hide,width=7,height=7>>=
286 grid <- expand.grid(x=seq(0,max(c(sd(abs(log(c(1,3)))),
287 sd(abs(log(c(1,0.33)))),sd(abs(log(c(0.33,3)))))),length.out=20),
288 y=seq(0,max(c(mean(log(c(1,3)),
289 mean(log(c(1,0.33))),
290 mean(log(c(0.33,3)))))),length.out=20))
291 grid$z <- to.kcal(10^(grid$x*grid$y))
292 print(wireframe(z~x*y,grid,cuts=50,
294 scales=list(arrows=FALSE),
295 xlab=list("Vesicle stdev log curvature",rot=30),
296 ylab=list("Vesicle average log curvature",rot=-35),
297 zlab=list("Vesicle Curvature Forward (kcal/mol)",rot=93)))
302 \subsubsection{Length Forward}
304 As in the case of unsaturation, void formation is easier when vesicles
305 are made up of components of widely different lengths. Thus, when the
306 width of the distribution of lengths is larger, the forward rate
307 should be greater as well, leading us to an equation of the form
308 $x^{\mathrm{stdev} l_\mathrm{ves}}$, where $\mathrm{stdev}
309 l_\mathrm{ves}$ is the standard deviation of the length of the
310 components of the vesicle, which has a maximum possible value of 8 and
311 a minimum of 0 in this set of experiments. A convenient base for $x$
315 l_f = 2^{\mathrm{stdev} l_\mathrm{ves}}
316 \label{eq:length_forward}
319 The most common $\mathrm{stdev} l_\mathrm{ves}$ is around $3.4$, which leads to
320 a range of $\Delta \Delta G^\ddagger$ of
321 $\Sexpr{format(digits=3,to.kcal(2^(3.4)))}
322 \frac{\mathrm{kcal}}{\mathrm{mol}}$.
324 While it could be argued that increased length of the monomer could
325 affect the rate of insertion into the membrane, it's not clear whether
326 it would increase (by decreasing the number of available hydrogen
327 bonds, for example) or decrease (by increasing the time taken to fully
328 insert the acyl chain, for example) the rate of insertion or to what
329 degree, so we do not take it into account in this formalism.
332 <<fig=TRUE,echo=FALSE,results=hide,width=7,height=5>>=
333 curve(2^x,from=0,to=sd(c(12,24)),
334 main="Length forward",
335 xlab="Standard Deviation of Length of Vesicle",
336 ylab="Length Forward Adjustment")
338 <<fig=TRUE,echo=FALSE,results=hide,width=7,height=5>>=
339 curve(to.kcal(2^x),from=0,to=sd(c(12,24)),
340 main="Length forward",
341 xlab="Standard Deviation of Length of Vesicle",
342 ylab="Length Forward Adjustment (kcal/mol)")
346 \subsubsection{Complex Formation}
347 There is no contribution of complex formation to the forward reaction
348 rate in the current formalism.
352 \label{eq:complex_formation_forward}
355 \subsection{Backward adjustments ($k_{bi\mathrm{adj}}$)}
357 Just as the forward rate constant adjustment $k_{fi\mathrm{adj}}$
358 does, the backwards rate constant adjustment $k_{bi\mathrm{adj}}$
359 takes into account unsaturation ($un_b$), charge ($ch_b$), curvature
360 ($cu_b$), length ($l_b$), and complex formation ($CF1_b$), each of
361 which are modified depending on the specific specie and the vesicle
362 into which the specie is entering:
366 k_{bi\mathrm{adj}} = un_b \cdot ch_b \cdot cu_b \cdot l_b \cdot CF1_b
370 \subsubsection{Unsaturation Backward}
372 Unsaturation also influences the ability of a lipid molecule to leave
373 a membrane. If a molecule has an unsaturation level which is different
374 from the surrounding membrane, it will be more likely to leave the
375 membrane. The more different the unsaturation level is, the greater
376 the propensity for the lipid molecule to leave. However, a vesicle
377 with some unsaturation is more favorable for lipids with more
378 unsaturation than the equivalent amount of less unsatuturation, so the
379 difference in energy between unsaturation is not linear. Therefore, an
380 equation with the shape
381 $x^{\left| y^{-\left< un_\mathrm{ves}\right> }-y^{-un_\mathrm{monomer}} \right| }$
382 where $\left<un_\mathrm{ves}\right>$ is the average unsaturation of
383 the vesicle, and $un_\mathrm{monomer}$ is the average unsaturation. In
384 this equation, as the average unsaturation of the vesicle is larger,
387 un_b = 7^{1-\left(20\left(2^{-\left<un_\mathrm{vesicle} \right>} - 2^{-un_\mathrm{monomer}} \right)^2+1\right)^{-1}}
388 \label{eq:unsaturation_backward}
391 The most common $\left<un_\mathrm{ves}\right>$ is around $1.7$, which leads to
392 a range of $\Delta \Delta G^\ddagger$ from
393 $\Sexpr{format(digits=3,to.kcal(7^(1-1/(5*(2^-1.7-2^-0)^2+1))))}
394 \frac{\mathrm{kcal}}{\mathrm{mol}}$ for monomers with 0 unsaturation
396 $\Sexpr{format(digits=3,to.kcal(7^(1-1/(5*(2^-1.7-2^-4)^2+1))))}\frac{\mathrm{kcal}}{\mathrm{mol}}$
397 for monomers with 4 unsaturations.
400 <<fig=TRUE,echo=FALSE,results=hide,width=7,height=7>>=
401 grid <- expand.grid(x=seq(0,4,length.out=20),
402 y=seq(0,4,length.out=20))
403 grid$z <- (7^(1-1/(5*(2^-grid$x-2^-grid$y)^2+1)))
404 print(wireframe(z~x*y,grid,cuts=50,
406 scales=list(arrows=FALSE),
407 xlab=list("Average Vesicle Unsaturation",rot=30),
408 ylab=list("Monomer Unsaturation",rot=-35),
409 zlab=list("Unsaturation Backward",rot=93)))
412 <<fig=TRUE,echo=FALSE,results=hide,width=7,height=7>>=
413 grid <- expand.grid(x=seq(0,4,length.out=20),
414 y=seq(0,4,length.out=20))
415 grid$z <- to.kcal((7^(1-1/(5*(2^-grid$x-2^-grid$y)^2+1))))
416 print(wireframe(z~x*y,grid,cuts=50,
418 scales=list(arrows=FALSE),
419 xlab=list("Average Vesicle Unsaturation",rot=30),
420 ylab=list("Monomer Unsaturation",rot=-35),
421 zlab=list("Unsaturation Backward (kcal/mol)",rot=93)))
428 \subsubsection{Charge Backwards}
429 As in the case of monomers entering a vesicle, monomers leaving a
430 vesicle leave faster if their charge has the same sign as the average
431 charge vesicle. An equation of the form $ch_b = a^{\left<ch_v\right>
432 ch_m}$ is then appropriate, and using a base of $a=20$ yields:
435 ch_b = 20^{\left<{ch}_v\right> {ch}_m}
436 \label{eq:charge_backwards}
439 The most common $\left<ch_v\right>$ is around $-0.164$, which leads to
440 a range of $\Delta \Delta G^\ddagger$ from
441 $\Sexpr{format(digits=3,to.kcal(20^(-.164*-1)))}
442 \frac{\mathrm{kcal}}{\mathrm{mol}}$ for monomers with charge $-1$ to
443 $0\frac{\mathrm{kcal}}{\mathrm{mol}}$
444 for monomers with charge $0$.
447 <<fig=TRUE,echo=FALSE,results=hide,width=7,height=7>>=
448 x <- seq(-1,0,length.out=20)
449 y <- seq(-1,0,length.out=20)
450 grid <- expand.grid(x=x,y=y)
451 grid$z <- as.vector(20^(outer(x,y)))
452 print(wireframe(z~x*y,grid,cuts=50,
454 scales=list(arrows=FALSE),
455 xlab=list("Average Vesicle Charge",rot=30),
456 ylab=list("Component Charge",rot=-35),
457 zlab=list("Charge Backwards",rot=93)))
460 <<fig=TRUE,echo=FALSE,results=hide,width=7,height=7>>=
461 x <- seq(-1,0,length.out=20)
462 y <- seq(-1,0,length.out=20)
463 grid <- expand.grid(x=x,y=y)
464 grid$z <- to.kcal(as.vector(20^(outer(x,y))))
465 print(wireframe(z~x*y,grid,cuts=50,
467 scales=list(arrows=FALSE),
468 xlab=list("Average Vesicle Charge",rot=30),
469 ylab=list("Component Charge",rot=-35),
470 zlab=list("Charge Backwards (kcal/mol)",rot=93)))
475 \subsubsection{Curvature Backwards}
477 The less a monomer's intrinsic curvature matches the average curvature
478 of the vesicle in which it is in, the greater its rate of efflux. If
479 the difference is 0, $cu_f$ needs to be one. To map negative and
480 positive curvature to the same range, we also need take the logarithm.
481 Increasing mismatches in curvature increase the rate of efflux, but
482 asymptotically. An equation which satisfies this critera has the
483 form $cu_f = a^{1-\left(b\left( \left< \log cu_\mathrm{vesicle} \right>
484 -\log cu_\mathrm{monomer}\right)^2+1\right)^{-1}}$. An
485 alternative form would use the aboslute value of the difference,
486 however, this yields a cusp and sharp increase about the curvature
487 equilibrium, which is decidedly non-elegant. We have chosen bases of
491 cu_b = 7^{1-\left(20\left(\left< \log cu_\mathrm{vesicle} \right> -\log cu_\mathrm{monomer} \right)^2+1\right)^{-1}}
492 \label{eq:curvature_backwards}
495 The most common $\left<\log cu_\mathrm{ves}\right>$ is around $-0.013$, which leads to
496 a range of $\Delta \Delta G^\ddagger$ from
497 $\Sexpr{format(digits=3,to.kcal(7^(1-1/(20*(-0.013-log(0.8))^2+1))))}
498 \frac{\mathrm{kcal}}{\mathrm{mol}}$ for monomers with curvature 0.8
500 $\Sexpr{format(digits=3,to.kcal(7^(1-1/(20*(-0.013-log(1.3))^2+1))))}\frac{\mathrm{kcal}}{\mathrm{mol}}$
501 for monomers with curvature 1.3 to $0\frac{\mathrm{kcal}}{\mathrm{mol}}$ for monomers with curvature near 1.
504 <<fig=TRUE,echo=FALSE,results=hide,width=7,height=7>>=
505 grid <- expand.grid(x=seq(0.8,1.33,length.out=20),
506 y=seq(0.8,1.33,length.out=20))
507 grid$z <- 7^(1-1/(20*(log(grid$x)-log(grid$y))^2+1))
508 print(wireframe(z~x*y,grid,cuts=50,
510 scales=list(arrows=FALSE),
511 xlab=list("Vesicle Curvature",rot=30),
512 ylab=list("Monomer Curvature",rot=-35),
513 zlab=list("Curvature Backward",rot=93)))
516 <<fig=TRUE,echo=FALSE,results=hide,width=7,height=7>>=
517 grid <- expand.grid(x=seq(0.8,1.33,length.out=20),
518 y=seq(0.8,1.33,length.out=20))
519 grid$z <- to.kcal(7^(1-1/(20*(log(grid$x)-log(grid$y))^2+1)))
520 print(wireframe(z~x*y,grid,cuts=50,
522 scales=list(arrows=FALSE),
523 xlab=list("Vesicle Curvature",rot=30),
524 ylab=list("Monomer Curvature",rot=-35),
525 zlab=list("Curvature Backward (kcal/mol)",rot=93)))
530 \subsubsection{Length Backwards}
532 In a model membrane, the dissociation constant increases by a factor
533 of approximately 3.2 per carbon decrease in acyl chain length (Nichols
534 1985). Unfortunatly, the experimental data known to us only measures
535 chain length less than or equal to the bulk lipid, and does not exceed
536 it, and is only known for one bulk lipid species (DOPC). We assume
537 then, that the increase is in relationship to the average vesicle, and
538 that lipids with larger acyl chain length will also show an increase
539 in their dissociation constant.
542 l_b = 3.2^{\left|\left<l_\mathrm{ves}\right>-l_\mathrm{monomer}\right|}
543 \label{eq:length_backward}
546 The most common $\left<\log l_\mathrm{ves}\right>$ is around $17.75$, which leads to
547 a range of $\Delta \Delta G^\ddagger$ from
548 $\Sexpr{format(digits=3,to.kcal(3.2^abs(12-17.75)))}
549 \frac{\mathrm{kcal}}{\mathrm{mol}}$ for monomers with length 12
551 $\Sexpr{format(digits=3,to.kcal(3.2^abs(24-17.75)))}\frac{\mathrm{kcal}}{\mathrm{mol}}$
552 for monomers with length 24 to $0\frac{\mathrm{kcal}}{\mathrm{mol}}$ for monomers with curvature near 18.
555 <<fig=TRUE,echo=FALSE,results=hide,width=7,height=7>>=
556 grid <- expand.grid(x=seq(12,24,length.out=20),
557 y=seq(12,24,length.out=20))
558 grid$z <- 3.2^(abs(grid$x-grid$y))
559 print(wireframe(z~x*y,grid,cuts=50,
561 scales=list(arrows=FALSE),
562 xlab=list("Average Vesicle Length",rot=30),
563 ylab=list("Monomer Length",rot=-35),
564 zlab=list("Length Backward",rot=93)))
567 <<fig=TRUE,echo=FALSE,results=hide,width=7,height=7>>=
568 grid <- expand.grid(x=seq(12,24,length.out=20),
569 y=seq(12,24,length.out=20))
570 grid$z <- to.kcal(3.2^(abs(grid$x-grid$y)))
571 print(wireframe(z~x*y,grid,cuts=50,
573 scales=list(arrows=FALSE),
574 xlab=list("Average Vesicle Length",rot=30),
575 ylab=list("Monomer Length",rot=-35),
576 zlab=list("Length Backward (kcal/mol)",rot=93)))
582 \subsubsection{Complex Formation Backward}
584 Complex formation describes the interaction between CHOL and PC or SM,
585 where PC or SM protects the hydroxyl group of CHOL from interactions
586 with water, the ``Umbrella Model''. PC ($CF1=2$) can interact with two
587 CHOL, and SM ($CF1=3$) with three CHOL ($CF1=-1$). If the average of
588 $CF1$ is positive (excess of SM and PC with regards to complex
589 formation), species with negative $CF1$ (CHOL) will be retained. If
590 average $CF1$ is negative, species with positive $CF1$ are retained.
591 An equation which has this property is
592 $CF1_b=a^{\left<CF1_\mathrm{ves}\right>
593 CF1_\mathrm{monomer}-\left|\left<CF1_\mathrm{ves}\right>
594 CF1_\mathrm{monomer}\right|}$, where difference of the exponent is
595 zero if the average $CF1$ and the $CF1$ of the specie have the same
596 sign, or double the product if the signs are different. A convenient
597 base for $a$ is $1.5$.
601 CF1_b=1.5^{\left<CF1_\mathrm{ves}\right> CF1_\mathrm{monomer}-\left|\left<CF1_\mathrm{ves}\right> CF1_\mathrm{monomer}\right|}
602 \label{eq:complex_formation_backward}
605 The most common $\left<CF1_\mathrm{ves}\right>$ is around $0.925$,
606 which leads to a range of $\Delta \Delta G^\ddagger$ from
607 $\Sexpr{format(digits=3,to.kcal(1.5^(0.925*-1-abs(0.925*-1))))}
608 \frac{\mathrm{kcal}}{\mathrm{mol}}$ for monomers with complex
610 $\Sexpr{format(digits=3,to.kcal(1.5^(0.925*2-abs(0.925*2))))}\frac{\mathrm{kcal}}{\mathrm{mol}}$
611 for monomers with complex formation $2$ to
612 $0\frac{\mathrm{kcal}}{\mathrm{mol}}$ for monomers with complex
616 <<fig=TRUE,echo=FALSE,results=hide,width=7,height=7>>=
617 grid <- expand.grid(x=seq(-1,3,length.out=20),
618 y=seq(-1,3,length.out=20))
619 grid$z <- 1.5^(grid$x*grid$y-abs(grid$x*grid$y))
620 print(wireframe(z~x*y,grid,cuts=50,
622 scales=list(arrows=FALSE),
623 xlab=list("Vesicle Complex Formation",rot=30),
624 ylab=list("Monomer Complex Formation",rot=-35),
625 zlab=list("Complex Formation Backward",rot=93)))
628 <<fig=TRUE,echo=FALSE,results=hide,width=7,height=7>>=
629 grid <- expand.grid(x=seq(-1,3,length.out=20),
630 y=seq(-1,3,length.out=20))
631 grid$z <- to.kcal(1.5^(grid$x*grid$y-abs(grid$x*grid$y)))
632 print(wireframe(z~x*y,grid,cuts=50,
634 scales=list(arrows=FALSE),
635 xlab=list("Vesicle Complex Formation",rot=30),
636 ylab=list("Monomer Complex Formation",rot=-35),
637 zlab=list("Complex Formation Backward (kcal/mol)",rot=93)))
645 % \bibliographystyle{plainnat}
646 % \bibliography{references.bib}