PubChem as a source of polypharmacology.

Polypharmacology provides a new way to address the issue of high attrition rates arising from lack of efficacy and toxicity. However, the development of polypharmacology is hampered by the incomplete SAR data and limited resources for validating target combinations. The PubChem bioassay collection, reporting the activity of compounds in multiple assays, allows us to study polypharmacological behavior in the PubChem collection via cross-assay analysis. In this paper, we developed a network representation of the assay collection and then applied a bipartite mapping between this network and various biological networks (i.e., PPI, pathway) as well as artificial networks (i.e., drug-target network). Mapping to a drug-target network allows us to prioritize new selective compounds, while mapping to other biological networks enable us to observe interesting target pairs and their associated compounds in the context of biological systems. Our results indicate this approach could be a useful way to investigate polypharmacology in the PubChem bioassay collection.