Predictive networks based on transcriptional-bioactivity data integration reveal the mode of action of stingray venoms

Animal venoms are potent drug leads, but mostly difficult to access and encountered in low quantity and purity. Modern integrative approaches could be the key to access challenging venom systems, bypassing costly traditional methods, and providing a first rough insight into their potential. Here, transcriptomic and phenotypic data from stingray venom were integrated into functional networks. These networks allow the identification of putatively interesting proteic candidates and the prediction of their mechanism of action from candidate-target interaction to the cellular response. The versatility of the integrated dataset allows the construction of multiple networks representing the mechanisms associated to toxin classes and envenomation effects as well as in interesting target systems.