Metabolomics-driven approaches for identifying therapeutic targets in drug discovery

This review is led by Professor. Tengfei Xu (Research Center for Clinical Pharmacy, College of Pharmaceutical Sciences, Zhejiang University) and Professor. Su Zeng (Research Center for Clinical Pharmacy, College of Pharmaceutical Sciences, Zhejiang University). The author emphasizes metabolomics’ critical role in advancing our understanding of disease mechanisms and accelerating targeted drug development, while acknowledging current challenges in the field.

Metabolomics, as a powerful tool, can captures phenotypic changes induced by exogenous compounds, offering a valuable approach for target identification beyond the traditional protein-level focus. With the deepen research, various metabolomics-based methods emerged for better discovery, including dose-response metabolomics, stable isotope-resolved metabolomics, and high-throughput metabolomics. These methods focus on the dose-dependent and spatiotemporal metabolite–drug interactions, emphasized for their ability to identify key enzymes and metabolic pathways affected by drugs. Emerging techniques, such as single-cell metabolomics, artificial intelligence, and mass spectrometry imaging, are also explored for their potential to enhance target discovery. With clear and detailed flow charts, the author describe in detail how these methods are used for target discovery.

“However, it has to be acknowledged that there are still many challenges in this field,” said Professor. Tengfei Xu, College of Pharmaceutical Sciences, Zhejiang University. Several limitations, including limited coverage of metabolites, lack of annotations for specific compounds, and potential degradation of active metabolites, obscure critical metabolites and pathways, hindering a comprehensive understanding of biological mechanisms. Therefore, strategy like multi-omics and technology like artificial intelligence were introduced in hopes of solving the current dilemma. The author summarized many articles to illustrate this process, while they believe that how to parse more metabolite information from complex spectrogram data is the real key. 

This review summarizes the commonly used target-finding methods and emerging technologies of metabolomics, and explains the technical barriers and analytical problems that coexist with them and need to be solved, paving the way for future related studies.

See the article: https://doi.org/10.1002/mco2.792