From: W. Trevor King Date: Thu, 5 Mar 2009 18:39:37 +0000 (-0500) Subject: Starting on version 0.6, with generalized discrete reactions. X-Git-Tag: v0.6^0 X-Git-Url: http://git.tremily.us/?a=commitdiff_plain;h=e0b5678c0d45b65919195b4f39e9e0e1ac8c7ed9;p=sawsim.git Starting on version 0.6, with generalized discrete reactions. Added domain-chain and reaction-graph figures. Added timescale section and cleaned up some of the overview text. --- diff --git a/src/sawsim.bib b/src/sawsim.bib index 9b6767b..713b3ea 100644 --- a/src/sawsim.bib +++ b/src/sawsim.bib @@ -3717,3 +3717,18 @@ doi = {10.1063/1.439715} note = "", project = "sawtooth simulation", } + +@article{Kroy07, + author={Klaus Kroy and Jens Glaser}, + title={The glassy wormlike chain}, + journal={New Journal of Physics}, + volume={9}, + number={11}, + pages={416}, + year={2007}, + abstract={We introduce a new model for the dynamics of a wormlike chain (WLC) in an environment that gives rise to a rough free energy landscape, which we name the glassy WLC. It is obtained from the common WLC by an exponential stretching of the relaxation spectrum of its long-wavelength eigenmodes, controlled by a single parameter \\boldsymbol{\\cal E} . Predictions for pertinent observables such as the dynamic structure factor and the microrheological susceptibility exhibit the characteristics of soft glassy rheology and compare favourably with experimental data for reconstituted cytoskeletal networks and live cells. We speculate about the possible microscopic origin of the stretching, implications for the nonlinear rheology, and the potential physiological significance of our results.}, + url={http://stacks.iop.org/1367-2630/9/416}, + eprint = "http://www.iop.org/EJ/article/1367-2630/9/11/416/njp7_11_416.pdf", + doi = "10.1088/1367-2630/9/11/416", + note = "Has short section on WLC relaxation time in the weakly bending limit.", +} diff --git a/src/sawsim.nw b/src/sawsim.nw index 1253c54..0d3ae8e 100644 --- a/src/sawsim.nw +++ b/src/sawsim.nw @@ -11,10 +11,15 @@ \usepackage[breaklinks,colorlinks]{hyperref} % for internal links, \phantomsection % breaklinks breaks long links % colorlinks colors link text instead of boxing it -\usepackage{amsmath} % for \text{}, \xrightarrow[sub]{super} +\usepackage{amsmath} % for \text{}, \xrightarrow[sub]{super} \usepackage{amsthm} % for theorem and proof environments \newtheorem{theorem}{Theorem} +\usepackage{subfig} % Support side-by-side figures +\usepackage{pgf} % Fancy graphics +\usepackage{tikz} % A nice, inline PGF frontend +\usetikzlibrary{automata} % Graph-theory library + \usepackage{doc} % BibTeX \usepackage[super,sort&compress]{natbib} % fancy citation extensions % super selects citations in superscript mode @@ -72,6 +77,9 @@ \today \\ \end{centering} \bigskip + +\tableofcontents + %%%%%%%%%%%%%%%%%%%%%%%%%%%% End LaTeX boilerplate %%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Introduction} @@ -136,15 +144,19 @@ line control of tension groups. Version 0.5 added the stiffness environmental parameter and it's associated unfolding models. +Version 0.6 generalized from two state unfolding to arbitrary +$N$-state rate reactions. This allows simulations of +unfolding-refolding, metastable intermediates, etc. + <>= -#define VERSION "0.5" +#define VERSION "0.6" @ \subsection{License} <>= sawsim - program for simulating single molecule mechanical unfolding. - Copyright (C) 2008, William Trevor King + Copyright (C) 2008-2009, William Trevor King This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as @@ -175,9 +187,57 @@ associated unfolding models. \section{Main} -The unfolding system is stored as a chain of \emph{domains}. Domains -can be folded, globular protein domains, unfolded protein linkers, AFM -cantilevers, or other stretchable system components. +The unfolding system is stored as a chain of \emph{domains} (Figure +\ref{fig.domain_chain}). Domains can be folded, globular protein +domains, unfolded protein linkers, AFM cantilevers, or other +stretchable system components. The system is modeled as graph of +possible domain states with transitions between them (Figure +\ref{fig.domain_states}). + +\begin{figure} +\begin{center} +\subfloat[][]{\label{fig.domain_chain} +\begin{tikzpicture}[->,node distance=2cm,font=\footnotesize] + \tikzstyle{every state}=[fill,draw=red!50,very thick,fill=red!20] + \node[state] (A) {domain 1}; + \node[state] (B) [below of=A] {domain 2}; + \node[state] (C) [below of=B] {.~.~.}; + \node[state] (D) [below of=C] {domain $N$}; + \node (S) [below of=D] {Surface}; + \node (E) [above of=A] {}; + + \path[-] (A) edge (B) + (B) edge node [right] {Tension} (C) + (C) edge (D) + (D) edge (S); + \path[->,green] (A) edge node [right,black] {Extension} (E); +\end{tikzpicture} +} +\qquad +\subfloat[][]{\label{fig.domain_states} +\begin{tikzpicture}[->,node distance=2.5cm,shorten <=1pt,shorten >=1pt,font=\footnotesize] + \tikzstyle{every state}=[fill,draw=blue!50,very thick,fill=blue!20] + \node[state] (A) {cantilever}; + \node[state] (C) [below of=A] {transition}; + \node[state] (B) [left of=C] {folded}; + \node[state] (D) [right of=C] {unfolded}; + + \path (B) edge [bend left] node [above] {$k_1$} (C) + (C) edge [bend left] node [below] {$k_1'$} (B) + edge [bend left] node [above] {$k_2$} (D) + (D) edge [bend left] node [below] {$k_2'$} (C); +\end{tikzpicture} +} +\caption{\subref{fig.domain_chain} Extending a chain of domains. One end + of the chain is fixed, while the other is extended at a constant + speed. The domains are coupled with rigid linkers, so the domains + themselves must stretch to accomodate the extension. + \subref{fig.domain_states} Each domain exists in a discrete state. At + each timestep, it may transition into another state following a + user-defined state matrix such as this one, showing a metastable + transition state and an explicit ``cantilever'' domain.} +\end{center} +\end{figure} Each domain contributes to the total tension, which depends on the chain extension. The particular model for the tension as a function @@ -192,9 +252,9 @@ following models have been implemented: \end{packed_item} The tension model and parameters used for a particular domain depend -on whether the domain is folded or unfolded. The transition rate from -the folded state to the unfolded state is also handled generally with -function pointers, with implementations for +on whether the domain's current state. The transition rates between +states are also handled generally with function pointers, with +implementations for \begin{packed_item} \item Null (Appendix \ref{sec.null_k}), \item Bell's model (Appendix \ref{sec.bell}), @@ -205,10 +265,11 @@ function pointers, with implementations for The unfolding of the chain domains is modeled in two stages. First the tension of the chain is calculated. Then the tension (assumed to -be constant over the length of the chain), is applied to each folded -domain, and used to calculate the probability of that subdomain -unfolding in the next timestep $dt$. Then the time is stepped -forward, and the process is repeated. +be constant over the length of the chain, see Section +\ref{sec.timescales}), is applied to each folded domain, and +used to calculate the probability of that subdomain unfolding in the +next timestep $dt$. Then the time is stepped forward, and the process +is repeated. <
>= int main(int argc, char **argv) @@ -513,16 +574,6 @@ int domain_unfolds(double F, double dt, environment_t *env, domain_t *domain) } @ [[happens]] is a random decision making function defined in Appendix \ref{app.utils}. -Only one domain can unfold in each timestep, because the timescale of -a domain unfolding $dt_u$ is assumed to be less than the simulation -timestep $dt$, so a domain will completely unfold in a single -timestep. We adapt our timesteps to keep the probability of a single -domain unfolding low, so the probability of two domains unfolding in -the same timestep is negligible. This approach breaks down as the -adaptive timestep scheme approaches $dt \sim dt_u$, but $dt_u \sim -1\U{$\mu$s}$ for Ig27-like proteins \citep{klimov00}, so this -shouldn't be a problem. To reassure yourself, you can ask the -simulator to print the smallest timestep that was used with TODO. <>= int random_unfoldings(list_t *domain_list, double tension, double dt, environment_t *env, @@ -543,18 +594,52 @@ int random_unfoldings(list_t *domain_list, double tension, } @ +\subsection{Timescales} +\label{sec.timescales} + +The simulation assumes that chain equilibration is instantaneous +relative to the simulation timestep $dt$, so that tension is uniform +along the chain. The quality of this assumption depends on your +particular chain. For example, a damped spring thermalizes on a +timescale of order $\tau = 1/\gamma$ where the damping ratio $\gamma +\equiv \omega_0(-\zeta \pm \sqrt{\zeta^2-1}$, the natural angular +frequency $omega_0 \equiv \sqrt{k/m}$, $\zeta \equiv b/2\sqrt{km}$, +and $b$ sets the drag $F_b = -bv$. For our cantilevers $\tau$ is +on the order of milliseconds, which is longer than a timestep. +However, the approximation is still reasonable, because there is +rarely unfolding during the cantilever return. You could, of course, +take cantilever, WLC, etc.\ response times into effect, but that +would significantly complicate a simulation that seems to work +well enough without bothering :p. For WLC and FJC relaxation times, +see the Appendix of \citet{evans99} and \citet{kroy07}. + +Besides assuming our timestep is much greater than equilibration +times, we also force it to be short enough so that only one domain may +unfold in a given timestep. For an unfolding timescale of $dt_u = +1/k$ we adapt our timesteps to keep $dt \ll dt_u$, so the probability +of two domains unfolding in the same timestep is negligible. This +approach breaks down as the adaptive timestep scheme approaches $dt +\sim dt_u$, but $dt_u \sim 1\U{$\mu$s}$ for Ig27-like proteins +\citep{klimov00}, so this shouldn't be a problem. To reassure +yourself, you can ask the simulator to print the smallest timestep +that was used with TODO. + \subsection{Adaptive timesteps} \label{sec.adaptive_dt} -We'd like to pick $dt$ so the probability of unfolding in the next -timestep is small. If we don't adapt our timestep, we risk breaking -our approximation that $F(x' \in [x, x+v \cdot dt]) = F(x)$ or that -only one domain unfolds in a given timestep. Because $F(x)$ is -monotonically increasing, excessively large timesteps will lead to -erroneously large unfolding forces. The simulation would have been -accurate for sufficiently small fixed timesteps, but adaptive -timesteps will allow us to move through low tension regions in fewer -steps, leading to a more efficient simulation. +We'd like to pick $dt$ so the probability of changing state +(e.g. unfolding) in the next timestep is small. If we don't adapt our +timestep, we also risk breaking our approximation that $F(x' \in [x, + x+v \cdot dt]) = F(x)$ or that only one domain changes state in a +given timestep. The simulation would have been accurate for +sufficiently small fixed timesteps, but adaptive timesteps will allow +us to move through low tension regions in fewer steps, leading to a +more efficient simulation. + +Consider the two state folded $\rightarrow$ unfolded transition. +Because $F(x)$ is monotonically increasing between unfoldings, +excessively large timesteps will lead to erroneously small unfolding +rates (an thus, higher average unfolding force). The actual adaptive timestep implementation is not particularly interesting, since we are only required to reduce $dt$ to somewhere