A computational tool for Monte Carlo simulations of biomolecular reaction networks modeled on physical principles.
Deciphering and designing complex biomolecular networks in the cell are the goals of systems and synthetic biology, respectively. The effects of localization, spatial heterogeneity, and molecular fluctuations in biomolecular networks are not well understood. We present a theoretical approach based on physical principles to accurately simulate biomolecular networks using the Monte Carlo method. Incorporating this theory, a computational tool named Monte Carlo biomolecular simulator (MBS) was developed, enabling studies of biomolecular kinetics with both spatial and temporal resolutions. The accuracy of MBS was verified by comparison against the classical deterministic approaches. Furthermore, the effects of localization, spatial heterogeneity, and molecular fluctuations were studied in three simulated model systems, showing their impact on the overall reaction kinetics. This work demonstrates the unique insights that can be discovered by considering the subtle effects that can be created by the spatial and temporal kinetics of biomolecular reaction networks.
Li
Isaac T S
IT
Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON M5S 3G9, Canada. isaac.li@utoronto.ca
Mills
Evan
E
Truong
Kevin
K
D020013:Calcium Signaling; D002477:Cells / Q000737:chemistry / Q000378:metabolism; D019295:Computational Biology / Q000379:methods*; D004247:DNA / Q000737:chemistry / Q000378:metabolism; D004058:Diffusion; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D009010:Monte Carlo Method; D011506:Proteins / Q000737:chemistry / Q000378:metabolism; D015398:Signal Transduction; D013269:Stochastic Processes
D011506:Proteins; D004247:DNA