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Updated: Nov 18, 2025

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
Published on: February 23, 2024
Metabolomics and In Silico Docking-Directed Discovery of Small-Molecule Enzyme Targets
Tengfei Xu1,2, Haoduo Zhao1, Mengjing Wang1
1School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798.
Abstract:
The identification of target proteins for small molecules is of great importance in drug discovery and for understanding the cellular mode of action (MOA) of toxicants. Herein, a "bottom-up" oriented target finding strategy is proposed based on the principle that the targeted enzymes can be inferred according to their phenotypic changes at the metabolome level. Meanwhile, computer-assisted in silico molecular docking analysis was performed to evaluate the binding affinities between the chemicals and the target enzymes to further rank the possible targets. In this study, triphenyl phosphate (TPhP) was used as an example to illustrate the workflow. After a comprehensive metabolome and lipidome analysis, 51 related metabolic enzymes were selected for ranking binding energies, wherein 25 proteins exhibited a higher affinity for TPhP than for their endogenous substrates. Two proteins, hydroxyacyl-coenzyme A dehydrogenase (HADH) and 3-hydroxyacyl-CoA dehydrogenase type-2 (HSD17B10), were further confirmed by surface phasma resonance (SPR) and isothermal titration calorimetry (ITC) analysis, displayed Kd values at low micromolar levels for TPhP. Overall, the proposed strategy has provided a feasible means for discovering enzymatic targets for the large-scale small-molecule sets, with the advantages of closely associating with the phenotype change, reducing the cost of groping, and improving the accuracy of target prediction.
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