iScience
Volume 23, Issue 10, 23 October 2020, 101565
Journal home page for iScience

Article
Diverse Cell Stimulation Kinetics Identify Predictive Signal Transduction Models

https://doi.org/10.1016/j.isci.2020.101565Get rights and content
Under a Creative Commons license
open access

Highlights

  • Diverse kinetic cell stimulations result in distinct signaling response dynamics

  • Diverse kinetics compared with step stimulations better constrain model parameters

  • Diverse kinetic stimulations improve predictions of WT and mutant pathway responses

  • Diverse kinetic stimulations compared with steps discriminate competing signaling models

Summary

Computationally understanding the molecular mechanisms that give rise to cell signaling responses upon different environmental, chemical, and genetic perturbations is a long-standing challenge that requires models that fit and predict quantitative responses for new biological conditions. Overcoming this challenge depends not only on good models and detailed experimental data but also on the rigorous integration of both. We propose a quantitative framework to perturb and model generic signaling networks using multiple and diverse changing environments (hereafter “kinetic stimulations”) resulting in distinct pathway activation dynamics. We demonstrate that utilizing multiple diverse kinetic stimulations better constrains model parameters and enables predictions of signaling dynamics that would be impossible using traditional dose-response or individual kinetic stimulations. To demonstrate our approach, we use experimentally identified models to predict signaling dynamics in normal, mutated, and drug-treated conditions upon multitudes of kinetic stimulations and quantify which proteins and reaction rates are most sensitive to which extracellular stimulations.

Subject Areas

Bioinformatics
Complex System Biology
Systems Biology

Cited by (0)

8

Lead Contact