Protocol to infer off-target effects of drugs on cellular signaling using interactome-based deep learning

Drugs that target specific proteins often have off-target effects. We present a protocol using artificial neural networks to model cellular transcriptional responses to drugs, aiming to understand their mechanisms of action. We detail steps for predicting transcriptional activities, inferring drug-target interactions, and explaining the off-target mechanism of action. As a case study, we analyze the off-target effects of lestaurtinib on FOXM1 in the A375 cell line. For complete details on the use and execution of this protocol, please refer to Meimetis et al.¹.