Kinetic Monte Carlo method for rule-based modeling of biochemical networks.
We present a kinetic Monte Carlo method for simulating chemical transformations specified by reaction rules, which can be viewed as generators of chemical reactions, or equivalently, definitions of reaction classes. A rule identifies the molecular components involved in a transformation, how these components change, conditions that affect whether a transformation occurs, and a rate law. The computational cost of the method, unlike conventional simulation approaches, is independent of the number of possible reactions, which need not be specified in advance or explicitly generated in a simulation. To demonstrate the method, we apply it to study the kinetics of multivalent ligand-receptor interactions. We expect the method will be useful for studying cellular signaling systems and other physical systems involving aggregation phenomena.
Chinese Academy of Sciences-Max Planck Society Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Shanghai 200031, China. yangjin@picb.ac.cn
Jin
J
Yang
Michael I
MI
Monine
James R
JR
Faeder
William S
WS
Hlavacek
D000465:Algorithms; D001665:Binding Sites; D001671:Biochemistry / Q000379:methods*; D001703:Biophysics / Q000379:methods*; D003198:Computer Simulation; D003201:Computers; D007700:Kinetics; D008024:Ligands; D015233:Models, Statistical; D009010:Monte Carlo Method; D015398:Signal Transduction; D012984:Software
D008024:Ligands