A NOVEL METHOD FOR VISUALIZING NUCLEAR HORMONE RECEPTOR NETWORKS RELEVANT TO DRUG METABOLISM

Abstract

The increasing generation of biological data represents a challenge to understanding the complexity of systems, resulting in scientists increasingly focused on a relatively narrow area of study, thereby limiting insight that can be gained from a broader perspective. In the field of drug metabolism and toxicology we are witnessing the characterization of many proteins. Most of the key enzymes and transporters are recognized as transcriptionally regulated by the nuclear hormone receptors such as pregnane X receptor, constitutive androstane receptor, vitamin D receptor, glucocorticoid receptor, and others. There is apparent cross talk in regulation, since multiple receptors may modulate expression of a single enzyme or transporter, representing one of many areas of active research interest. We have used published data on nuclear hormone receptors, enzymes, ligands, and other biological information to manually annotate an Oracle database, forming the basis of a platform for querying (MetaDrug). Using algorithms, we have demonstrated how nuclear hormone receptors alone can form a network of direct interactions, and when expanded, this network increases in complexity to describe the interactions with target genes as well as small molecules known to bind a receptor, enzyme, or transporter. We have also described how the database can be used for visualizing high-throughput microarray data derived from a published study of MCF-7 cells treated with 4-hydroxytamoxifen, to highlight potential downstream effects of molecule treatment. The database represents a novel knowledge mining and analytical tool that, to be relevant, requires continual updating to evolve alongside other key storage systems and sources of biological knowledge.