The pharmacology of drugs is often defined by more than one
protein target. This property can be exploited to use approved drugs to uncover new targets and signaling pathways in
cancer. Towards enabling a rational approach to uncover new targets, we expand a structural
protein-
ligand interactome () by scoring the interaction among 1000 FDA-approved drugs docked to 2500 pockets on
protein structures of the human genome. This afforded a drug-target network whose properties compared favorably with previous networks constructed using experimental data. Among drugs with the highest degree and betweenness two are
cancer drugs and one is currently used for treatment of
lung cancer. Comparison of predicted
cancer and non-
cancer targets reveals that the most
cancer-specific compounds were also the most selective compounds. Analysis of compound flexibility, hydrophobicity, and size showed that the most selective compounds were low molecular weight fragment-like heterocycles. We use a previously-developed screening approach using the
cancer drug
erlotinib as a template to screen other approved drugs that mimic its properties. Among the top 12 ranking candidates, four are
cancer drugs, two of them
kinase inhibitors (like
erlotinib). Cellular studies using
non-small cell lung cancer (NSCLC) cells revealed that several drugs inhibited
lung cancer cell proliferation. We mined patient records at the Regenstrief Medical Record System to explore the possible association of exposure to three of these drugs with occurrence of
lung cancer. Preliminary in vivo studies using the
non-small cell lung cancer (NCLSC) xenograft model showed that
losartan- and
astemizole-treated mice had
tumors that weighed 50 (p < 0.01) and 15 (p < 0.01) percent less than the treated controls. These results set the stage for further exploration of these drugs and to uncover new drugs for
lung cancer therapy.