Modeling and optimization of the specificity in cell signaling pathways based on a high performance multi-objective evolutionary algorithm

  • Authors:

  • Xiufen Zou;Yu Chen;Zishu Pan

  • Affiliations:

  • College of Mathematics and Statistics, Wuhan University, Wuhan, China;College of Mathematics and Statistics, Wuhan University, Wuhan, China;College of Life Science, Wuhan University, Wuhan, China

  • Venue:
  • SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
  • Year:
  • 2006

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Abstract

A central question in cell and developmental biology is how signaling pathways maintain specificity and avoid erroneous cross-talk so that distinct signals produce the appropriate changes. In this paper, a model system of the yeast mating, invasive growth and stress-responsive mitogen activated protein kinase (MAPK) cascades for scaffolding-mediated is developed. Optimization with respect to the mutual specificity of this model system is performed by a high performance multi-objective evolutionary algorithm (HPMOEA) based on the principles of the minimal free energy in thermodynamics. The results are good agreement with published experimental data. (1) Scaffold proteins can enhance specificity in cell signaling when different pathways share common components; (2) The mutual specificity could be accomplished by a selectively-activated scaffold that had a relatively high value of dissociation constant and reasonably small values of leakage rates; (3) When Pareto-optimal mutual specificity is achieved, the coefficients, deactivation rates reach fastest, association and leakage rates reach slowest.