Drug discovery is moving away from the single target-based approach
towards harnessing the potential of polypharmacological agents that
modulate the activity of multiple nodes in the complex networks of
deregulations underlying disease phenotypes. Computational network
pharmacology methods that use systems-level drug-response phenotypes,
such as those originating from genome-wide transcriptomic profiles, have
proved particularly effective for elucidating the mechanisms of action
of multitargeted compounds. Here, we show, via the case study of the
natural product pinosylvin, how the combination of two complementary
network-based methods can provide novel, unexpected mechanistic
insights. This case study also illustrates that elucidating the
mechanism of action of multitargeted natural products through
transcriptional response-based approaches is a challenging endeavor,
often requiring multiple computational-experimental iterations.