Co-controllability of drug-disease-gene network

Abstract

Controllability of a single network often focuses on the determination of the network's minimum dominating set, which aims to elaborate how to control the whole network with minimum driver nodes. This paper proposes a new framework, co-controllability of multiple networks, which stresses the control of one network by another network as well as the mutual control characteristics of multiple networks based on minimum dominating sets. We take a drug-disease-gene network that consists of a drug-drug network, a disease-disease network and a gene-gene network as an example to study co-controllability of multiple networks. The results show that driver nodes tend to be conserved, e.g. diseases highly associated with driver nodes of the drug-drug network tend to be driver nodes in the disease-disease network compared with random networks. In addition, cocontrollability of multiple networks is probably associated with the networks' node degree, which is more stringent than controllability of a single network that is mainly determined by the network's degree distribution. We also find that diseases and drugs tend to be mapped as two different subnetworks of human protein-protein interaction (PPI) network, drugs are inclined to dominate diseases by controlling the PPI network, and the coded proteins of disease-related genes exhibit a low tendency to be drug targets for the control of diseases. The results in this paper not only play an important role in understanding co-controllability of multiple networks, but also are helpful for understanding the mechanisms of drug-disease-gene, disease treatments and drug design in a network-based framework.

Focus on the emerging new fields of network physiology and network medicine

“…Another line of investigations focuses on co-controllability of networks, identifying the minimal set of driver nodes that control an entire network and quantifying mutual control characteristics of multiple networks as encountered in the human interactome. A study by Sun [52] considers a drug-disease-gene network that consist of gene-gene, disease-disease and drug-drug networks to investigate co-controllability among these networks, and to uncover underlying mechanisms of the drug-disease-gene network with applications to disease treatment and drug design.…”

The Hidden Control Architecture of Complex Brain Networks

“…The important role of MD-nodes in network control is recognized both in theory (Nacher and Akutsu, 2012) and in various real-world networks (Nacher and Akutsu, 2013, Wan et al., 2002, Wuchty, 2014). In particular, the concept of MDSet has recently been adopted to analyze various biological networks, and the results showed that MD-nodes not only occupy strategic locations to control the networks but are also associated with various biological functions (Nacher and Akutsu, 2013, Nacher and Akutsu, 2016, Sun, 2015, Wakai et al., 2017, Wuchty, 2014, Zhang et al., 2016). Thus, we postulated that the composition of MD-nodes in a network represents its hidden control architecture.…”

Probabilistic controllability approach to metabolic fluxes in normal and cancer tissues

“…The networks were analysed using a minimum dominating set (MDS) approach to identify potential driver nodes reactions 5 . The MDS approach was proposed by Nacher and Akutsu 7 and has been used to analyse many biological systems and identify proteins associated to cancer 8–12 . However, the flux coupling approach uses a discrete definition of coupling between reactions and does not take into account the full range of possible flux distributions that the metabolic system is able to support.…”