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1 ère Journée de Biologie Systémique Université Paris 5 La Biologie des Systèmes en Toxicologie Robert Barouki UMR-S 747 INSERM Université Paris 5 Pharmacologie.

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Presentation on theme: "1 ère Journée de Biologie Systémique Université Paris 5 La Biologie des Systèmes en Toxicologie Robert Barouki UMR-S 747 INSERM Université Paris 5 Pharmacologie."— Presentation transcript:

1 1 ère Journée de Biologie Systémique Université Paris 5 La Biologie des Systèmes en Toxicologie Robert Barouki UMR-S 747 INSERM Université Paris 5 Pharmacologie Toxicologie et Signalisation Cellulaire Centre des Saints Pères 22 Mai 2006

2 A variety of Systems in Toxicology Drug and polluants toxicity: differences and similarities Global systems The Organism as a system Cellular and molecular systems

3 Environmental Toxicology: a global system

4 Clinical response Preclinical response contaminants Internal contamination biomarkers New technologies Internal dose External contact exposure Environmental Toxicology: a global system sources Can we predict toxicity?

5 Drug Toxicity: the organism as a system Target tissues Toxicity

6 Impact de la toxicité des médicaments Drug Toxicity: a health and economical issue Can we predict toxicity?

7 High throughput technologies: the « omics » Lessons from molecular and cellular biology Analytical Methods Systems biology In silico prediction Paradise on earth low cost, high efficiency Predictive and Mechanistic Toxicology Can New Technologies help?

8 Invasion of Toxicology by the OMICS Structural genomics Functional genomics genome transcriptome proteome metabolome physiome Proteomics Metabonomics Metabolomics Just add Toxico-

9 Is it all in the gene structure?? Large scale detection of polymorphisms, in particular SNPs A fraction of toxicity can be explained by gene structure Individual susceptibility Pharmaco- and Toxico-genetics

10 25 000 genes The most powerful man in the world Not Surprised?? 20 000 genes The Worm C elegans The number of genes (1)

11 20 000 genes The Worm C elegans 25 000 genes René Descartes The number of genes (2) Complexity is not only related to the number of genes

12 Where does complexity come from? gene regulation (toxicogenomics) mRNA splicing (toxicogenomics) mRNA degradation (toxicogenomics) Protein stability (toxicoproteomics) Post translational regulation (toxicoproteomics) Protein-protein interaction (interactomes) connection of metabolic parthways (metabolomics) Systems biology: a comprehensive description

13 Xenobiotics are low molecular weight foreign Substances: Drugs Pollutants Nutrients Similar responses at the cellular level Exposure to xenobiotics is accompanied by a stress The Xenobiotics Stress System

14 What is a stress?? Stress: the word Physics:response of a metal Physiology: a defined set of responses to extreme situations (Selye) Cell biology: response of a cell to aggression Psychology-social sciences: response of an individual or of a group Stress is an adaptive response to a significant shift in cellular conditions This response has a cost

15 Xenobiotics stress Xenobiotics Enzymes (XMEs) and transporteurs: Metabolism and exits O-Conj Receptor: Detection and induction elimination Adaptation: 1- detection of xenobiotics and gene induction 2- transformation and elimination

16 Metabolism of Xenobiotics the Detoxication System Xenobiotic OH Phase I CYP Phase IIPhase III O-Conj GST UGT MDRMRP Receptor

17 Legitimate and Illegitimate Receptors for Xenobiotics Multiple Pathways and Dangerous Liaisons PPAR Xenobiotics Endocrine disruption ER lipidssteroid hormones Adaptation and stress possible toxicity Metabolic disruption Both legitimate and illegitimate liaisons can be dangerous AhRPXR - CAR Xenobiotics receptors

18 O O Cl TetraChloroDibenzoDioxin: TCDD - Lessons from the chemistry - Receptor: AhR, shared with other pollutants, xenobiotics and endogenous compounds - Induction of XMEs (CYP1A1): adaptation and stress response - Regulation of dozens of other genes: What for?? Dioxin

19 The Dioxin Receptor System: lessons from genomics Xenobiotics metabolism Hundreds maybe Thousands of ligands: xeno or endo Cell cycle Cell migration Lipid metabolism Large number of toxicogenomics studies; Marchand et al, Mol Pharmacol, 2005

20 TCDD Cell Morphology and Motility Diry et al, Oncogene, 2006,

21 The Dioxin Receptor System: lessons from protein interaction ARNT NFkB Rb Src HIF inflammation hypoxia proliferation Few large scale studies. Use of Protein interaction network in yeast Yao et al, PLOS Biology, 2004

22 The Dioxin Receptor System: lessons from metabolism BP OH CYP BP DNA adduct genotoxicity p53 The p53 system apoptosis H2O2H2O2 Oxidative stress Large scale studies: predictive pharmaco-metabonomic phenotyping using urinary samples (Clayton et al, Nature, 2006)

23 Consortia and databases in Toxicogenomics ILSI Health and Environmental Service Institute (collab European Bioinformatics Institute) Toxicogenomics Research Consortium (National Center for Toxicogenomics) COMET: Consortium for Metabonomics Technology EDGE: Environment, Drugs and Gene Expression PharmGKB: PharmacoGenomics Knowledge Base CEBS: Chemical Effect in Biological Systems Knowledge Base Protein Interaction Network

24 Structural biology Major breakthroughs in drug metabolism (CYP3A4) and drug inductioin (PXR)

25 Structural biology The promiscuity of the PXR revealed by its structure: 3 possible positions for a single molecule

26 In silico prediction Mosly developped for ADMET: Absorption, Distribution, Metabolism, excretion, Toxicity Data modelling: QSAR (Quantitative Structure Activity Relationship). Correlate a set of molecular or structural descriptors of a drug with a defined property (such a particular toxicity) Highly dependent on the quality of the data and the mathematical approach Molecular modelling: mostly based on structural information and modelling to predict ligand protein interaction

27 Iterative modelling for drug development integrating ADMET

28 A Systems Biology Approach Goal: build a model integrating all data: genomics, protein interaction, metabolic pathway, toxicity … Be as quantitative as possible Predict the consequences of perturbation in the system Can be more focused: gene regulation networks protein interaction networks Metabolic pathways….

29 A Systems Biology Approach: the case of 4-OH-tamoxifen Metadrug (http:/

30 Toxicology Systems Biology: a global approach

31 Systems Toxicology Molecular and global aspects: integrates systems biology as well as more traditional toxicological data Describes new mechanisms High Predictive power: development of safer drugs and safer chemicals (Reach protocol of the EU)

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