A generalized cellular automata approach to modeling first order enzyme kinetics

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• 作者：ABHISHEK DUTTA ; SAURAJYOTI KAR ; ADVAIT APTE ; INGMAR NOPENS ; DENIS CONSTALES
• 关键词：Cellular automata ; enzyme kinetics ; extended von ; Neumann neighborhood.
• 刊名：Sadhana
• 出版年：2015
• 出版时间：April 2015
• 年：2015
• 卷：40
• 期：2
• 页码：411-423
• 全文大小：714 KB
• 参考文献：Apte A, Cain J W, Bonchev D G and Fong S S 2008 Cellular automata simulation of topological effects on the dynamics of feed-forward motifs. J. Biol. Eng. 2(2): 1鈥?2
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• 作者单位：ABHISHEK DUTTA (1) (5)
  SAURAJYOTI KAR (2)
  ADVAIT APTE (3)
  INGMAR NOPENS (1)
  DENIS CONSTALES (4)
  
  1. BIOMATH, Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000, Ghent, Belgium
  5. Departement Materiaalkunde, KU Leuven, Kasteelpark Arenberg 44 bus 2450, B-3001, Heverlee-Leuven, Belgium
  2. Department of Biotechnology, National Institute of Technology, Durgapur, 713 209, India
  3. Biological Systems Engineering Department, Virginia Tech, Blacksburg, VA, 24061, USA
  4. Department of Mathematical Analysis, Ghent University, Galglaan 2, B-9000, Ghent, Belgium
  
• 刊物类别：Engineering
• 刊物主题：Engineering, general
  
• 出版者：Springer India, in co-publication with Indian Academy of Sciences
• ISSN：0973-7677

文摘

Biochemical processes occur through intermediate steps which are associated with the formation of reaction complexes. These enzyme-catalyzed biochemical reactions are inhibited in a number of ways such as inhibitors competing for the binding site directly, inhibitors deforming the allosteric site or inhibitors changing the structure of active substrate. Using an in silico approach, the concentration of various reaction agents can be monitored at every single time step, which are otherwise difficult to analyze experimentally. Cell-based models with discrete state variables, such as Cellular Automata (CA) provide an understanding of the organizational principles of interacting cellular systems to link the individual cell (microscopic) dynamics with a particular collective (macroscopic) phenomenon. In this study, a CA model representing a first order enzyme kinetics with inhibitor activity is formulated. The framework of enzyme reaction rules described in this study is probabilistic. An extended von Neumann neighborhood with periodic boundary condition is implemented on a two-dimensional (2D) lattice framework. The effect of lattice-size variation is studied followed by a sensitivity analysis of the model output to the probabilistic parameters which represent various kinetic reaction constants in the enzyme kinetic model. This provides a deeper insight into the sensitivity of the CA model to these parameters. It is observed that cellular automata can capture the essential features of a discrete real system, consisting of space, time and state, structured with simple local rules without making complex implementations but resulting in complex but explainable patterns.