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Nonlinear Analytics for Electrochemical Biosensor Design Using Enzyme Aggregates and Delayed Mass Action.

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Area of Science:

  • Biochemistry
  • Chemical Kinetics
  • Mathematical Modeling

Background:

  • Enzyme kinetics models often simplify time delays.
  • Brown's model provides a foundation for enzyme kinetic analysis.
  • Incorporating distributed delays enhances model realism.

Purpose of the Study:

  • To extend Brown's enzyme kinetics model to include distributed delays.
  • To develop and validate a model for multi-substrate, multi-inhibitor systems.
  • To compare the chemical adequacy of discrete versus distributed delay models.

Main Methods:

  • Construction of a multi-substrate, multi-inhibitor model with discrete and distributed delays.
  • Development of a parameter identification algorithm.
  • Experimental validation using solution conductivity data and Kohlrausch's law.
  • Optimization procedures for model and experimental parameters.

Main Results:

  • An algorithm for parameter identification was successfully developed and tested.
  • The distributed delay model demonstrated greater chemical adequacy than the discrete delay model.
  • Model and Kohlrausch's law parameters were estimated through optimization.

Conclusions:

  • Distributed delays offer a more chemically adequate representation in enzyme kinetics compared to discrete delays.
  • The developed methodology is applicable to complex multi-component systems.
  • Further generalization to multi-substrate, multi-inhibitor scenarios is feasible.