Drug-Induced Expression-Based Computational Repurposing of Small Molecules Affecting Transcription Factor Activity

Area of Science:

• Oncology
• Computational Biology
• Drug Discovery

Background:

• Targeting oncogenes and tumor suppressors is crucial for cancer drug development.
• Many key cancer targets, particularly transcription factors, lack druggable pockets, posing a significant challenge.

Purpose of the Study:

• To present CRAFTT, a novel computational drug-repositioning strategy.
• To enable targeting of transcription factors, previously considered undruggable, for anticancer therapies.

Main Methods:

• CRAFTT integrates transcription factor target gene sets with drug-induced expression profiles.
• It identifies small molecules capable of modulating transcription factor activity.
• Network analysis is employed to calculate a modulation index (MI) for prioritizing drug candidates.

Main Results:

• The study describes the CRAFTT approach for identifying potential drug candidates.
• It provides a framework for perturbing transcription factor activity using small molecules.
• Prioritization of predictions is achieved through network analysis and a derived modulation index.

Conclusions:

• CRAFTT offers a broadly applicable computational method for drug repositioning against transcription factors.
• This approach addresses the challenge of targeting undruggable proteins in cancer therapy.
• The methodology facilitates the identification of novel therapeutic strategies by targeting transcription factor activity.