Understanding the downstream consequences of pharmacologically targeted proteins is essential to drug design. Current approaches investigate molecular effects under tissue-naïve assumptions. Many target proteins, however, have tissue-specific expression. A systematic study connecting drugs to target pathways in in vivo human tissues is needed. We introduced a data-driven method that integrates drug-target relationships with gene expression, protein-protein interaction, and pathway annotation data. We applied our method to four independent genomewide expression datasets and built 467,396 connections between 1,034 drugs and 954 pathways in 259 human tissues or cell lines. We validated our results using data from L1000 and Pharmacogenomics Knowledgebase (PharmGKB), and observed high precision and recall. We predicted and tested anticoagulant effects of 22 compounds experimentally that were previously unknown, and used clinical data to validate these effects retrospectively. Our systematic study provides a better understanding of the cellular response to drugs and can be applied to many research topics in systems pharmacology.
© 2018 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.