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NADPHnet: a novel strategy to predict compounds for regulation of NADPH metabolism via network-based methods

Abstract

Identification of compounds to modulate NADPH metabolism is crucial for understanding complex diseases and developing effective therapies. However, the complex nature of NADPH metabolism poses challenges in achieving this goal. In this study, we proposed a novel strategy named NADPHnet to predict key proteins and drug-target interactions related to NADPH metabolism via network-based methods. Different from traditional approaches only focusing on one single protein, NADPHnet could screen compounds to modulate NADPH metabolism from a comprehensive view. Specifically, NADPHnet identified key proteins involved in regulation of NADPH metabolism using network-based methods, and characterized the impact of natural products on NADPH metabolism using a combined score, NADPH-Score. NADPHnet demonstrated a broader applicability domain and improved accuracy in the external validation set. This approach was further employed along with molecular docking to identify 27 compounds from a natural product library, 6 of which exhibited concentration-dependent changes of cellular NADPH level within 100 μM, with Oxyberberine showing promising effects even at 10 μM. Mechanistic and pathological analyses of Oxyberberine suggest potential novel mechanisms to affect diabetes and cancer. Overall, NADPHnet offers a promising method for prediction of NADPH metabolism modulation and advances drug discovery for complex diseases.

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Fig. 1: Schematic diagram of NADPHnet, including six parts.
Fig. 2: Analysis of APs and corresponding pathways in each layer.
Fig. 3: Results of network-based DTI related to NADPH metabolic models.
Fig. 4: Results of 27 compounds potentially regulating NADPH metabolism in vitro.
Fig. 5: Molecular docking of four natural products capable of regulating NADPH metabolism with predicted targets.

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Acknowledgements

This work was supported by the National Key Research and Development Program of China (Grant 2019YFA0904800), the National Natural Science Foundation of China (Grant U23A20530, 82173746 and 82104066), and the Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism (Shanghai Municipal Education Commission).

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YT, YZZ, and TL supervised the research project. FP designed and implemented the NADPHnet strategy. FP, ZHY, ZRW, ZW, SL, WHL, and GXL constructed network-based models, evaluated the performance of network-based models, performed network-based VS on NADPH metabolism, and analyzed the prediction results. CNW, YZZ, and TL performed in vitro experiments. FP, ZHY, CNW, TL, YT wrote the manuscript. All authors read and approved the final version of the manuscript.

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Correspondence to Ting Li or Yun Tang.

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Pan, F., Wang, Cn., Yu, Zh. et al. NADPHnet: a novel strategy to predict compounds for regulation of NADPH metabolism via network-based methods. Acta Pharmacol Sin (2024). https://doi.org/10.1038/s41401-024-01324-6

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