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

STAR Protoc. 2025 Mar 21;6(1):103573. doi: 10.1016/j.xpro.2024.103573. Epub 2025 Jan 16.

Abstract

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.

Keywords: bioinformatics; gene expression; health sciences; systems biology.

MeSH terms

  • Cell Line, Tumor
  • Deep Learning*
  • Forkhead Box Protein M1 / genetics
  • Forkhead Box Protein M1 / metabolism
  • Humans
  • Neural Networks, Computer
  • Signal Transduction* / drug effects

Substances

  • Forkhead Box Protein M1
  • FOXM1 protein, human