Controllability in cancer metabolic networks according to drug targets as driver nodes

Yazdan Asgari, Ali Salehzadeh-Yazdi, Falk Schreiber, Ali Masoudi-Nejad

Résultats de recherche: Contribution à un journalArticleRevue par des pairs

56 Citations (Scopus)

Résumé

Networks are employed to represent many nonlinear complex systems in the real world. The topological aspects and relationships between the structure and function of biological networks have been widely studied in the past few decades. However dynamic and control features of complex networks have not been widely researched, in comparison to topological network features. In this study, we explore the relationship between network controllability, topological parameters, and network medicine (metabolic drug targets). Considering the assumption that targets of approved anticancer metabolic drugs are driver nodes (which control cancer metabolic networks), we have applied topological analysis to genome-scale metabolic models of 15 normal and corresponding cancer cell types. The results show that besides primary network parameters, more complex network metrics such as motifs and clusters may also be appropriate for controlling the systems providing the controllability relationship between topological parameters and drug targets. Consequently, this study reveals the possibilities of following a set of driver nodes in network clusters instead of considering them individually according to their centralities. This outcome suggests considering distributed control systems instead of nodal control for cancer metabolic networks, leading to a new strategy in the field of network medicine.

langue originaleAnglais
Numéro d'articlee79397
journalPLoS ONE
Volume8
Numéro de publication11
Les DOIs
étatPublié - 25 nov. 2013
Modification externeOui

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