Development and implementation of a novel computational tool for an efficient construction of drug-target interactome

The application of network concepts to pharmacology has become popular and promising for better understanding the molecular mechanisms of drug actions. In this study, we developed a computational pipeline in order to construct the drug-target interactome, thereby facilitating these drug action investigations. The interactome includes drug-drug, drug-target and target-protein interaction networks. The pipeline first extracts human protein-protein interaction (PPI) data from the Protein Interaction Network Analysis (PINA) platform to obtain the cleaned human PPIs with experimental evidence. Next, the pipeline retrieves the drugs of interest, their targets and the adverse drug interactions from the DrugBank database. Based on the cleaned human PPIs and drug-related information, the pipeline finally generates three subnetworks involved in the drug-target interactome: drug-drug network, drug-target network, and target-protein interaction network. We implemented the pipeline within two Python packages. To illustrate how the pipeline works, we used schizophrenia as a keyword to obtain SZ-related drugs. The Python packages and example data are available at http://bioinfo.mc.vanderbilt.edu/software.html.