title: An in silico target identification using Boolean network attractors: Avoiding pathological phenotypes.
abstract: Target identification aims at identifying biomolecules whose function should be therapeutically altered to cure the considered pathology. An algorithm for in silico target identification using Boolean network attractors is proposed. It assumes that attractors correspond to phenotypes produced by the modeled biological network. It identifies target combinations which allow disturbed networks to avoid attractors associated with pathological phenotypes. The algorithm is tested on a Boolean model of the mammalian cell cycle and its applications are illustrated on a Boolean model of Fanconi anemia. Results show that the algorithm returns target combinations able to remove attractors associated with pathological phenotypes and then succeeds in performing the proposed in silico target identification. However, as with any in silico evidence, there is a bridge to cross between theory and practice. Nevertheless, it is expected that the algorithm is of interest for target identification.
authors.affiliation: Novadiscovery, 60, avenue Rockefeller, 69008 Lyon, France; UMR CNRS 5558, 43, boulevard du 11-Novembre-1918, 69622 Villeurbanne cedex, France. Electronic address: arnaud.poret@gmail.com.
authors.forename: Arnaud
authors.initials: A
authors.lastname: Poret
authors.affiliation: Novadiscovery, 60, avenue Rockefeller, 69008 Lyon, France. Electronic address: jean-pierre.boissel@novadiscovery.com.
authors.forename: Jean-Pierre
authors.initials: JP
authors.lastname: Boissel
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000235:genetics; D002453:Cell Cycle / Q000502:physiology; D002468:Cell Physiological Phenomena; D003198:Computer Simulation / Q000706:statistics & numerical data*; D004260:DNA Repair; D055808:Drug Discovery / Q000379:methods*; D005199:Fanconi Anemia / Q000235:genetics; D005260:Female; D057166:High-Throughput Screening Assays / Q000295:instrumentation*; D006801:Humans; D008954:Models, Biological; D016571:Neural Networks, Computer; D010641:Phenotype
keywords: Anémie de Fanconi; Attracteurs; Attractors; Boolean networks; Drug discovery; Découverte de médicaments; Fanconi anemia; Identification de cibles; In silico; Phenotypes; Phénotypes; Réseaux booléens; Target identification