title: Integrating systems biology sources illuminates drug action.
abstract: There are significant gaps in our understanding of the pathways by which drugs act. This incomplete knowledge limits our ability to use mechanistic molecular information rationally to repurpose drugs, understand their side effects, and predict their interactions with other drugs. Here, we present DrugRouter, a novel method for generating drug-specific pathways of action by linking target genes, disease genes, and pharmacogenes using gene interaction networks. We construct pathways for more than a hundred drugs and show that the genes included in our pathways (i) co-occur with the query drug in the literature, (ii) significantly overlap or are adjacent to known drug-response pathways, and (iii) are adjacent to genes that are hits in genome-wide association studies assessing drug response. Finally, these computed pathways suggest novel drug-repositioning opportunities (e.g., statins for follicular thyroid cancer), gene-side effect associations, and gene-drug interactions. Thus, DrugRouter generates hypotheses about drug actions using systems biology data.
authors.affiliation: Department of Genetics, Stanford University, Stanford, California, USA.
authors.forename: A
authors.initials: A
authors.lastname: Gottlieb
authors.affiliation: 1] Department of Genetics, Stanford University, Stanford, California, USA [2] Department of Bioengineering, Stanford University, Stanford, California, USA.
authors.forename: R B
authors.initials: RB
authors.lastname: Altman
mesh_terms: D000465:Algorithms; D016208:Databases, Factual; D004347:Drug Interactions / Q000235:genetics / Q000502:physiology; D058492:Drug Repositioning / Q000379:methods*; D053263:Gene Regulatory Networks; D006801:Humans; D010597:Pharmacogenetics; D010600:Pharmacology / Q000379:methods*; D015398:Signal Transduction / Q000187:drug effects; D049490:Systems Biology / Q000379:methods*