The Systems Biology of Drug Metabolizing Enzymes and Transporters: Relevance to Quantitative Systems Pharmacology.

ABSTRACT

Quantitative systems pharmacology (QSP) has emerged as a transformative science in drug discovery and development. It is now time to fully rethink the biological functions of drug metabolizing enzymes (DMEs) and transporters within the framework of QSP models. The large set of DME and transporter genes are generally considered from the perspective of the absorption, distribution, metabolism, and excretion (ADME) of drugs. However, there is a growing amount of data on the endogenous physiology of DMEs and transporters. Recent studies-including systems biology analyses of "omics" data as well as metabolomics studies-indicate that these enzymes and transporters, which are often among the most highly expressed genes in tissues like liver, kidney, and intestine, have coordinated roles in fundamental biological processes. Multispecific DMEs and transporters work together with oligospecific and monospecific ADME proteins in a large multiorgan remote sensing and signaling network. We use the Remote Sensing and Signaling Theory (RSST) to examine the roles of DMEs and transporters in intratissue, interorgan, and interorganismal communication via metabolites and signaling molecules. This RSST-based view is applicable to bile acids, uric acid, eicosanoids, fatty acids, uremic toxins, and gut microbiome products, among other small organic molecules of physiological interest. Rooting this broader perspective of DMEs and transporters within QSP may facilitate an improved understanding of fundamental biology, physiologically based pharmacokinetics, and the prediction of drug toxicities based upon the interplay of these ADME proteins with key pathways in metabolism and signaling. The RSST-based view should also enable more tailored pharmacotherapy in the setting of kidney disease, liver disease, metabolic syndrome, and diabetes. We further discuss the pharmaceutical and regulatory implications of this revised view through the lens of systems physiology.