Abstract
Cellular functions and responses to stimuli are controlled by complex regulatory networks that comprise a large diversity of molecular components and their interactions. However, achieving an intuitive understanding of the dynamical properties and responses to stimuli of these networks is hampered by their large scale and complexity. To address this issue, analyses of regulatory networks often focus on reduced models that depict distinct, reoccurring connectivity patterns referred to as motifs. Previous modeling studies have begun to characterize the dynamics of small motifs, and to describe ways in which variations in parameters affect their responses to stimuli. The present study investigates how variations in pairs of parameters affect responses in a series of ten common network motifs, identifying concurrent variations that act synergistically (or antagonistically) to alter the responses of the motifs to stimuli. Synergism (or antagonism) was quantified using degrees of nonlinear blending and additive synergism. Simulations identified concurrent variations that maximized synergism, and examined the ways in which it was affected by stimulus protocols and the architecture of a motif. Only a subset of architectures exhibited synergism following paired changes in parameters. The approach was then applied to a model describing interlocked feedback loops governing the synthesis of the CREB1 and CREB2 transcription factors. The effects of motifs on synergism for this biologically realistic model were consistent with those for the abstract models of single motifs. These results have implications for the rational design of combination drug therapies with the potential for synergistic interactions.
Highlights
Cellular functions are regulated by complex biochemical networks that incorporate large numbers of diverse molecular components and their interactions
The present study focused on one coherent feed-forward loop (FFL) variant (P-FFL), which is frequently observed in signaling pathways [29] (Fig. 1B1A), and one incoherent FFL variant (N-FFL) (Fig. 1B1B)
Perhaps the simplest model for studying synergism is a threenode model of two pathways that converge onto a single target
Summary
Cellular functions are regulated by complex biochemical networks that incorporate large numbers of diverse molecular components and their interactions. Distinct motifs appear to manifest specific dynamical features [10,13,14,15,16,17] and modeling studies describe how the responses of distinct motifs and the robustness of these responses vary with parameters [18,19,20] These studies are beginning to elucidate ways in which motif dynamics contribute to the functions and response properties of larger, more complex regulatory networks. As is investigated here, small network motifs can be used to examine the ways in which combinations of parameter changes act synergistically (or antagonistically) to alter the response to stimuli This later strategy may help guide the development of drug combination therapies that target disease-related dysfunction of a network motif
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