Molecular Network Control Through Boolean Canalization

TL;DR

This paper explores how Boolean canalization influences the control of molecular networks, introducing methods to identify control edges to prevent undesirable states in biological systems.

Contribution

It presents novel methods for controlling Boolean molecular networks by leveraging canalization properties and estimating effects of edge modifications.

Findings

Identified control edges in cell-cycle and p53-mdm2 models.

Demonstrated methods can prevent undesirable state transitions.

Applied control strategies to real biological network models.

Abstract

Boolean networks are an important class of computational models for molecular interaction networks. Boolean canalization, a type of hierarchical clustering of the inputs of a Boolean function, has been extensively studied in the context of network modeling where each layer of canalization adds a degree of stability in the dynamics of the network. Recently, dynamic network control approaches have been used for the design of new therapeutic interventions and for other applications such as stem cell reprogramming. This work studies the role of canalization in the control of Boolean molecular networks. It provides a method for identifying the potential edges to control in the wiring diagram of a network for avoiding undesirable state transitions. The method is based on identifying appropriate input-output combinations on undesirable transitions that can be modified using the edges in the wiring diagram of the network. Moreover, a method for estimating the number of changed transitions in the state space of the system as a result of an edge deletion in the wiring diagram is presented. The control methods of this paper were applied to a mutated cell-cycle model and to a p53-mdm2 model to identify potential control targets.