title: Systems biology tools for toxicology.
abstract: An important goal of toxicology is to understand and predict the adverse effects of drugs and other xenobiotics. For pharmaceuticals, such effects often emerge unexpectedly in man even when absent from trials in vitro and in animals. Although drugs and xenobiotics act on molecules, it is their perturbation of intracellular networks that matters. The tremendous complexity of these networks makes it difficult to understand the effects of xenobiotics on their ability to function. Because systems biology integrates data concerning molecules and their interactions into an understanding of network behaviour, it should be able to assist toxicology in this respect. This review identifies how in silico systems biology tools, such as kinetic modelling, and metabolic control, robustness and flux analyse, may indeed help understanding network-mediated toxicity. It also shows how these approaches function by implementing them vis-à-vis the glutathione network, which is important for the detoxification of reactive drug metabolites. The tools enable the appreciation of the steady state concept for the detoxification network and make it possible to simulate and then understand effects of perturbations of the macromolecules in the pathway that are counterintuitive. We review how a glutathione model has been used to explain the impact of perturbation of the pathway at various molecular sites, as would be the effect of single-nucleotide polymorphisms. We focus on how the mutations impact the levels of glutathione and of two candidate biomarkers of hepatic glutathione status. We conclude this review by sketching how the various systems biology tools may help in the various phases of drug development in the pharmaceutical industry.
authors.affiliation: Manchester Centre for Integrative Systems Biology, University of Manchester, UK.
authors.forename: Suzanne
authors.initials: S
authors.lastname: Geenen
authors.forename: Peter Neal
authors.initials: PN
authors.lastname: Taylor
authors.forename: Jacky L
authors.initials: JL
authors.lastname: Snoep
authors.forename: Ian D
authors.initials: ID
authors.lastname: Wilson
authors.forename: J Gerry
authors.initials: JG
authors.lastname: Kenna
authors.forename: Hans V
authors.initials: HV
authors.lastname: Westerhoff
mesh_terms: D000818:Animals; D003198:Computer Simulation; D005838:Genotype; D005978:Glutathione / Q000378:metabolism; D006801:Humans; D008658:Inactivation, Metabolic / Q000235:genetics; D008099:Liver / Q000187:drug effects* / Q000378:metabolism / Q000473:pathology; D055432:Metabolomics; D008954:Models, Biological; D010597:Pharmacogenetics; D010599:Pharmacokinetics; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D018570:Risk Assessment; D012307:Risk Factors; D049490:Systems Biology; D014116:Toxicology / Q000379:methods*
chemical_list: D005978:Glutathione