Computational Framework for Modeling Multiple Noncooperative Transcription Factor Binding and Its Application to the Analysis of Nuclear Factor Kappa B Oscillatory Response

Recent studies have shown that regulation of many important genes is achieved with multiple transcription factor (TF) binding sites with low or no cooperativity. Additionally, noncooperative binding sites are gaining more and more importance in the field of synthetic biology. Here, we introduce a computational framework that can be applied to dynamical modeling and analysis of gene regulatory networks with multiple noncooperative TF binding sites. We propose two computational methods to be used within the framework, that is, average promoter state approximation and expression profiles based modeling. We demonstrate the application of the proposed framework on the analysis of nuclear factor kappa B (NF-kappa B) oscillatory response. We show that different promoter expression hypotheses in a combination with the number of TF binding sites drastically affect the dynamics of the observed system and should not be ignored in the process of quantitative dynamical modeling, as is usually the case in existent state-of-the-art computational analyses.