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

Journal: STAR protocols
PMID: 39823233

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..

Authors

  • Nikolaos Meimetis
    Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
  • Douglas A Lauffenburger
    Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. lauffen@mit.edu.
  • Avlant Nilsson
    Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.

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