2024
DOI: 10.21203/rs.3.rs-3494185/v1
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Machine Learning-Based Metabolic Pattern Recognition Predicts Mode of Action for Anti-Cancer Drug Candidates

Gerd Balcke,
Mohamad Saoud,
Jan Grau
et al.

Abstract: A bottleneck in the development of new anti-cancer drugs is the recognition of their mode of action (MoA). We combined metabolomics and machine learning to predict MoAs of novel anti-proliferative drug candidates, focusing on human prostate cancer cells (PC-3). As proof of concept, we studied 38 drugs with known effects on 16 key processes of cancer metabolism, profiling low molecular weight intermediates of the central carbon and cellular energy metabolism (CCEM) by LC-MS/MS. These metabolic patterns unveiled… Show more

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