Viewing drug action as network perturbation in multiple scale systems.

Abstract

The biochemist view of drug action and chemical toxicity has traditionally focused on a single objective: find the target. This has indeed led to major discoveries in the field. However, we now know that target identification is not sufficient to predict the clinical fate of a drug. Chemical toxicity has also focused on identifying targets, but quickly enough biological pathways have also been considered. For example, in addition to the discovery of the dioxin target, the arylhydrocarbon receptor, scientists have identified the AhR gene battery, i.e., the collection of genes that were induced following the activation of this receptor. With the advent of omics technologies, we now know that many other genes are affected and that more than one pathway is altered [ 1 ]. A similar development has occurred with other targets of xenobiotics, notably the xenobiotic receptors PXR and CAR as described in this issue by Molnár et al. [ 2 ]. Systems biology has changed considerably our understanding of cell function in the last few years. Our view of a cell with more or less autonomous biological pathways has now to be reconsidered. The integration of large scale observations has lead to a new picture in which genes and proteins sharing functional or structural interactions are organized in networks. This is best illustrated by protein interactome studies which identified network of proteins based on physical interactions [ 3 ]. Similarly, gene expression studies have identified groups of genes sharing similar regulations. Integration of all those studies yields a complex picture of interaction between cellular components, indicating that different pathways may interact with each other in a time-dependent manner. This may help explain why modulating one pathway leads to much wider effects than expected and why cross-talks between pathways are readily observed. It is now believed that disease states are associated with cellular network alterations and that a genetic variation can disrupt these networks [ 4 ]. Drug effect and toxicity could also be viewed as resulting from the perturbation of cellular networks (as illustrated by Galizzi et al in this issue [ 5 ]). The advantage of such an approach is that not only the biological pathway directly connected to the drug target is considered, but also other pathways within the network. If a drug represses a protein, consequences are expected not only for those proteins immediately interacting with it, but also for more distal proteins through indirect interactions. As an example, if one considers the mechanisms of breast cancer resistance to tamoxifen chemotherapy, studies should not only focus on the estrogen receptor pathway but also on connected pathways involved in cellular proliferation and apoptosis, in addition to drug metabolism pathways [ 6 ]. Many other illustrations of perturbation of networks arise from pharmaco-metabolomics and pharmacogenomics studies. The concept of drugs acting by perturbing normal interactions is also true at the organism level as well as at the population levels. This is best illustrated by the action of endocrine disrupting compounds which, even at low doses, can alter complex endocrine physiological functions leading to deleterious long-term effects [7]. On a more global level, it is believed that the increase in chemical burden on the environment leads to a perturbation of ecosystem component interactions and consequently to toxicity. In conclusion, a better assessment of drug effects and toxicity in various systems will depend not only on the identification of targets but also on a better understanding of the perturbations induced in preexisting networks and interactions. This may provide a novel perspective for understanding variability in drug effects, vulnerability to toxicity and drug-drug interactions.