DeepTarget predicts anti-cancer mechanisms of action of small molecules by integrating drug and genetic screens.

ABSTRACT: Identifying the mechanisms of action (MOA) driving a drug's anti-cancer efficacy is critical for its clinical success, guiding the search for its best biomarkers, indications and combinations. Yet, systematically identifying MOAs remains challenging due to drugs often engaging multiple targets with varying affinities across different cellular contexts. Addressing this challenge, we present DeepTarget, a computational tool that integrates large-scale drug and genetic knockdown viability screens with omics data to predict a drug's MOAs driving its cancer cell killing. To test its performance, we curated eight datasets of high-confidence drug-target pairs focused on cancer drugs and benchmarked DeepTarget. We show that DeepTarget outperforms recent tools in predicting drug targets and their m

SUBMITTER: Sinha S 

PROVIDER: S-EPMC12589559 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature