The role of stochastic gene switching in determining the pharmacodynamics of certain drugs: basic mechanisms

Krzysztof Puszynski1, Alberto Gandolfi2, Alberto d'Onofrio3

  • 1Institute of Automatic Control, Silesian University of Technology, Akademicka 16, Gliwice, Poland.

Insights

Gene switching significantly impacts drug response curves by influencing protein levels. Stochastic fluctuations can lead to cellular responses even at low drug concentrations, affecting pharmacodynamics.

Area of Science:

  • Biochemistry
  • Pharmacology
  • Systems Biology

Background:

  • Stochastic gene expression, where genes switch between ON and OFF states, is a fundamental biological process.
  • Understanding gene switching is crucial for analyzing drug pharmacodynamics and dose-response relationships.
  • Existing models often simplify gene expression, potentially missing key stochastic effects.

Purpose of the Study:

  • To investigate the impact of stochastic gene switching on drug pharmacodynamics.
  • To analyze the formation of in vitro dose-response curves using two molecular circuits.
  • To explore how gene switching rates and drug concentrations influence cellular responses.

Main Methods:

  • Numerical simulations of two molecular circuits involving gene transcription and protein translation.
  • Modeling a gene circuit with constant activation/deactivation rates.
  • Modeling a gene circuit with negative feedback via a protein transcription factor.
  • Simulating drug effects on protein elimination and therapeutic success criteria.

Main Results:

  • Gene switching plays a critical role in the sigmoidal shape of dose-response curves.
  • Slow gene switching allows cellular responses even without sufficient drug concentrations.
  • Non-responding cell fractions show complex behavior with varying gene switching rates and drug concentrations.

Conclusions:

  • Stochastic gene switching is a key determinant of pharmacodynamic variability.
  • Drug efficacy and cellular response are significantly modulated by the dynamics of gene expression.
  • The study highlights the limitations of deterministic models in predicting drug responses under stochastic conditions.

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