Metabolomics-driven approaches for identifying therapeutic targets in drug discovery

Shanshan Pan , Luan Yin , Jie Liu , Jie Tong , Zichuan Wang , Jiahui Zhao , Xuesong Liu , Yong Chen , Jing Miao , Yuan Zhou , Su Zeng , Tengfei Xu

MedComm ›› 2024, Vol. 5 ›› Issue (11) : e792

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MedComm ›› 2024, Vol. 5 ›› Issue (11) : e792 DOI: 10.1002/mco2.792
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Metabolomics-driven approaches for identifying therapeutic targets in drug discovery

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Abstract

Identification of therapeutic targets can directly elucidate the mechanism and effect of drug therapy, which is a central step in drug development. The disconnect between protein targets and phenotypes under complex mechanisms hampers comprehensive target understanding. Metabolomics, as a systems biology tool that captures phenotypic changes induced by exogenous compounds, has emerged as a valuable approach for target identification. A comprehensive overview was provided in this review to illustrate the principles and advantages of metabolomics, delving into the application of metabolomics in target identification. This review outlines various metabolomics-based methods, such as dose–response metabolomics, stable isotope-resolved metabolomics, and multiomics, which identify key enzymes and metabolic pathways affected by exogenous substances through dose-dependent metabolite–drug interactions. Emerging techniques, including single-cell metabolomics, artificial intelligence, and mass spectrometry imaging, are also explored for their potential to enhance target discovery. The review emphasizes metabolomics’ critical role in advancing our understanding of disease mechanisms and accelerating targeted drug development, while acknowledging current challenges in the field.

Keywords

artificial intelligence / drug development / metabolomics / single-cell metabolomics / target identification

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Shanshan Pan, Luan Yin, Jie Liu, Jie Tong, Zichuan Wang, Jiahui Zhao, Xuesong Liu, Yong Chen, Jing Miao, Yuan Zhou, Su Zeng, Tengfei Xu. Metabolomics-driven approaches for identifying therapeutic targets in drug discovery. MedComm, 2024, 5(11): e792 DOI:10.1002/mco2.792

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