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  • 标题:Reaction–diffusion systems for spatio-temporal intracellular protein networks: A beginner's guide with two examples
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  • 作者:Ján Eliaš ; Jean Clairambault
  • 期刊名称:Computational and Structural Biotechnology Journal
  • 印刷版ISSN:2001-0370
  • 出版年度:2014
  • 卷号:10
  • 期号:16
  • 页码:12-22
  • DOI:10.1016/j.csbj.2014.05.007
  • 语种:
  • 出版社:Computational and Structural Biotechnology Journal
  • 摘要:Spatio-temporal dynamics of a variety of proteins is, among other things, regulated by post-translational modifications of these proteins. Such modifications can thus influence stability and biochemical activities of the proteins, activity and stability of their upstream targets within specific signalling pathways. Commonly used mathematical tools for such protein–protein (and/or protein-mRNA) interactions in single cells, namely, Michaelis–Menten and Hill kinetics, yielding a system of ordinary differential equations, are extended here into (non-linear) partial differential equations by taking into account a more realistic spatial representation of the environment where these reactions occur. In the modelling framework under consideration, all interactions occur in a cell divided into two compartments, the nucleus and the cytoplasm, connected by the semipermeable nuclear membrane and bounded by the impermeable cell membrane. Passive transport mechanism, modelled by the so-called Kedem–Katchalsky boundary conditions, is used here to represent migration of species throughout the nuclear membrane. Nonlinear systems of partial differential equations are solved by the semi-implicit Rothe method. Examples of two spatial oscillators are shown. Namely, these are the circadian rhythm for concentration of the FRQ protein in Neurospora crassa and oscillatory dynamics observed in the activation and regulation of the p53 protein following DNA damage in mammalian cells.
  • 关键词:Michaelis–Menten kinetics ; Hill kinetics ; Intracellular protein signalling ; Spatial representation ; Reaction–diffusion PDE models ; Oscillations ; p53 ; Leloup–Goldbeter FRQ model
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