Simulated Evolution of Signal Transduction Networks

Abstract

Signal transduction is the process of routing information inside cells when receiving stimuli from their environment that modulate the behavior and function. In such biological processes, the receptors, after receiving the corresponding signals, activate a number of biomolecules which eventually transduce the signal to the nucleus. The main objective of our work is to develop a theoretical approach which will help to better understand the behavior of signal transduction networks due to changes in kinetic parameters and network topology. By using an evolutionary algorithm, we designed a mathematical model which performs basic signaling tasks similar to the signaling process of living cells. We use a simple dynamical model of signaling networks of interacting proteins and their complexes. We study the evolution of signaling networks described by mass-action kinetics. The fitness of the networks is determined by the number of signals detected out of a series of signals with varying strength. The mutations include changes in the reaction rate and network topology. We found that stronger interactions and addition of new nodes lead to improved evolved responses. The strength of the signal does not play any role in determining the response type. This model will help to understand the dynamic behavior of the proteins involved in signaling pathways. It will also help to understand the robustness of the kinetics of the output response upon changes in the rate of reactions and the topology of the network.

Modeling evolution of crosstalk in noisy signal transduction networks

“…Currently, much of the theory related to evolution of signal transduction networks focuses on changes at the phenotypic level (e.g. changing protein interactions directly) [25,26]. In this paper we adapt a sequence-based evolutionary model due to Zulfikar et al [27] that allows us to map from sequence space (genotype) to rate constant space (phenotype).…”

A Link Between Alzheimer's and Type II Diabetes Mellitus? Ca+2‐Mediated Signal Control and Protein Localization

“…Weak PPIs also facilitate transient and strong signaling activation that underlies robust biological responses. [55] Protein partitioning results in the production of multiple responses by activating signaling in the cytosol and at the membrane surface. In other words, unlike TCS, an input signal is “diluted” by protein partitioning to generate multiple biological responses including gene transcription, protein synthesis, and metabolism that allow organisms to make time- and energy-efficient adjustments, depending on external perturbations.…”

Systems approaches for synthetic biology: a pathway toward mammalian design

“…Known as evolutionary algorithms, these methods can predict state changes in the behavior of signaling pathways over time, through adaptation or random mutation, by modeling this rewiring directly (Hallinan et al, 2010; Chen et al, 2011; Mobashir et al, 2012). In the same vein, these methods allow for the de novo construction and optimization of genetic networks by way of simulation (Bloom and Arnold, 2009), “evolving” a set of viable pathway designs that meet the specified constraints (Hallinan et al, 2010).…”